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  1. Opportunity
  2.  
  3. Pager is looking to hire a Machine Learning Engineer to build and deploy Machine Learning models into the company's core services. You'll be working in a fast-paced collaborative environment and contribute to our team's mission: Turn the complex world of healthcare into a simple and beautiful experience using Machine Learning.
  4.  
  5. Responsibilities
  6. Define, prototype, develop, deploy, and maintain Machine Learning models: From Natural Language Understanding to Predictive Clustering.
  7. Participate as a member of an interdisciplinary team that includes engineers, data scientists, product team members and clinicians to identify and plan new features and solve problems
  8. Ensure high quality of code
  9. Mentor your peers and stay up to date in your knowledge
  10.  
  11. You'll be a good fit if
  12. You know data science:
  13. Have a strong hands-on knowledge of machine learning algorithms, both deep and shallow
  14. Are comfortable using machine learning stacks and can make good decisions about which to use to solve a particular problem
  15. Hands-on experience with machine learning tools and libraries including (not limited to) Numpy, Scipy, Scikit-learn, SpaCy
  16. Are familiar with data cleaning, sanitization and adequate handling of sensitive information
  17. You know computer science and engineering:
  18. Have a strong CS background to choose the right algorithms, systems approaches and patterns to solve problems: you won't reinvent the wheel
  19. Have a proven track record designing and implementing data driven products
  20. Write production quality code and tests
  21. Build APIs that expose ML models
  22. You can hit the ground running:
  23. M.Sc. or Ph.D. in computer science, engineering, statistics, computational linguistics, or other quantitative field, or equivalent professional experience
  24. 2+ years of experience in a production data science environment
  25. Experience working with AWS and Docker
  26. You have a sense of ownership:
  27. Take responsibility for your projects and pride in your work
  28. You come up with novel solutions to a diverse set of problems:
  29. Ask hard questions and challenge assumptions to ensure that we're solving the right problems
  30. Have flexibility to work on the team's most pressing problems
  31.  
  32. Nice to haves
  33. Experience dealing with health system partners data (e.g. EHRs, HIEs, ADT feeds, claims/pre-auth feeds, …)
  34. Experience with storage models coming from the SQL (PostgreSQL, MySQL) and NoSQL (MongoDB, Elasticsearch, Redis, Graph based storage)
  35. RabbitMQ and NodeJS experience
  36. Understanding and exposure to some ML topics: pattern detection; entity recognition; semantic role labeling; and clustering and classification models, neural networks
  37. Experience using Docker containers and configuration management systems
  38. Experience in Tensorflow, Keras
  39.  
  40.  
  41. About Pager
  42.  
  43. Pager is re-inventing the traditional patient experience. A leader in the healthcare industry with its innovative tech solutions to help patients access care, Pager is a multi-faceted care navigation platform. Patients can access a wide range of services from connecting with providers directly through the app and getting answers to general health care questions (from the comfort of their home) to scheduling in-home visits. Pager has partnered with top-tier health plans, health systems and provider networks across the U.S.
  44.  
  45. Founded by an experienced team of serial entrepreneurs from successful startups (Uber, Teladoc, Gilt, One Medical Group, Buzzfeed), we are passionate about improving access to high quality and personal health care.
  46.  
  47. From long days of perfecting a great product to long nights of happy hours and group dinners, we are looking for someone smart, energetic, and fun to join our tight-knit and growing team.
  48.  
  49. A passion for health care is not necessary to apply; however, a passion for improving the lives of people and living a better life through technology is a must.
  50.  
  51. At Pager, we value diversity and always treat all employees and job applicants based on merit, qualifications, competence, and talent. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status.
  52. Seniority Level
  53. Entry level
  54.  
  55. Industry
  56. Computer Software Internet Hospital & Health Care
  57. Employment Type
  58. Full-time
  59.  
  60. Job Functions
  61. Engineering Information Technology
  62.  
  63.  
  64. The front page of the internet," Reddit brings over 330 million people together each month through their common interests, inviting them to share, vote, comment, and create across thousands of communities. Come for the cats, stay for the empathy.
  65.  
  66. Monetization is often the most data-heavy, latency sensitive and technically demanding part of any online business. We’ve expanded our ads engineering team to New York to work on focus on problems around prediction and yield optimization.
  67.  
  68. We are looking for machine learning engineers to build and improve Reddit’s ad serving pipelines and predictive models. This team will focus on modeling to serve relevant ads to users utilizing Reddit’s rich dataset.
  69.  
  70. If you appreciate real technical challenges and you'd like to be part of the team that turns Reddit into a sustainable, long-term business, come join us!
  71.  
  72. Responsibilities
  73. Build and maintain Reddit's machine learning and feature engineering pipelines for ad serving.
  74. Understand Reddit user behavior and ad quality to optimize ad performance and user experience.
  75. Use the scientific method to improve our models, relying on quantitative analysis and experimentation to ensure we’re moving in the right direction.
  76.  
  77.  
  78. Qualifications
  79. Significant experience developing production models / pipelines.
  80. Software development experience in one or more general purpose programming languages (e.g. Go, Python, Java, C++, etc.).
  81. Familiar with large-scale data pipelines and ML / AI techniques. Spark / MLib / Tensorflow experience a plus.
  82. Entrepreneurial and self-directed, innovative, biased towards action in fast-paced environments.
  83. Able to take complete ownership of a feature or project.
  84. Able to communicate and discuss complex topics with technical and non-technical audiences.
  85. Industry
  86. Marketing & Advertising Computer Software Internet
  87. Employment Type
  88. Full-time
  89.  
  90. Job Functions
  91. Engineering Information Technology
  92.  
  93. Who We Are
  94.  
  95. HBC is a diversified global retailer, focused on driving the performance of high quality stores and their all-channel offerings, growing through acquisitions, and unlocking the value of real estate holdings.
  96.  
  97. Founded in 1670, HBC is the oldest company in North America. Our portfolio today includes formats ranging from luxury to premium department stores to off price fashion shopping destinations, with more than 480 stores and over 66,000 employees around the world.
  98.  
  99. Our leading banners across North America and Europe include Hudson�s Bay, Lord & Taylor, Saks Fifth Avenue, Gilt, Saks OFF 5TH, Galeria Kaufhof, the largest department store group in Germany, and Belgium�s only department store group Galeria INNO.
  100.  
  101. We have significant investments in real estate joint ventures. HBC has partnered with Simon Property Group Inc. in the HBC Global Properties Joint Venture, which owns properties in the United States and Germany. In Canada, HBC has partnered with RioCan Real Estate Investment Trust in the RioCan-HBC Joint Venture.
  102.  
  103. A truly global corporate citizen, HBC is committed to responsible business practices to bring about positive change, and we work hard to shape a sustainable future for people and the planet. Our philanthropic initiatives are dedicated to improving lives by enhancing physical and mental health through education, access, research, and empowerment, and we strive to create innovative programs and resources that provide flexibility for work-life balance to ensure HBC remains a great place to work.
  104.  
  105. What This Position Is All About
  106.  
  107. Be a member of the founding ML team at HBC, ready to tackle a variety of business problems from customer service and personalization to inventory optimization. Create ML solutions to these spanning the entire organization using various supervised and unsupervised methods. Help HBC�s data team to create a data culture, pioneer embracement of new concepts, and develop a team that has learning at its core.
  108.  
  109. As The Machine Learning Engineer, You Will
  110. Apply algorithms to our business to improve customer experience, create operational efficiency and enable our workforce. Make recommendations as to best algorithms to use for different use cases
  111. Test validate, and deploy algorithms into production ready status. Ensure models maintain explain-ability to make decisions and choices around predictions and impact on the business
  112. Collect the right data for predictive modeling and algorithm development.
  113. Work closely with business intelligence and data engineering to deliver on projects.
  114.  
  115. You Also Have
  116.  
  117.  
  118. Bachelor�s degree in quantitative field
  119. 1-3+ years of data science experience
  120. 1-3+ years of working in SQL or other programming languages
  121. Expert programming capability in Python
  122. Experience in building and deploying Machine Learning systems
  123. Experience with data cleaning and preparation.
  124.  
  125. Your Life And Career At HBC
  126. Be part of a world-class team; work with an adventurous spirit; think and act like an owner- operator!
  127. Gain exposure to rewarding career advancement opportunities, from retail to supply chain, to digital or corporate.
  128. Join a culture that promotes a healthy, fulfilling work/life balance
  129. Receive a benefits package available for all eligible full-time employees
  130. Enjoy an amazing employee discount
  131.  
  132. Thank you for your interest with HBC. We look forward to reviewing your application.
  133.  
  134. HBC provides equal employment opportunities (EEO) to all employees and applicants for employment without regard to race, color, religion, sex, national origin, age, disability or genetics. In addition to federal law requirements, HBC complies with applicable state and local laws governing nondiscrimination in employment in every location in which the company has facilities. This policy applies to all terms and conditions of employment, including recruiting, hiring, placement, promotion, termination, layoff, recall, transfer, leave, compensation and training.
  135.  
  136. HBC welcomes all applicants for this position. Should you be individually selected to participate in an assessment or selection process, accommodations are available upon request in relation to the materials or processes to be used.
  137. Seniority Level
  138. Entry level
  139.  
  140. Industry
  141. Marketing & Advertising Apparel & Fashion Retail
  142. Employment Type
  143. Full-time
  144.  
  145. Job Functions
  146. Engineering Information Technology
  147.  
  148. Company Description
  149.  
  150. We believe everyone should be able to participate and thrive in the economy. So we’re building tools that make commerce easier and more accessible to all. We started with a little white credit card reader but haven’t stopped there. Our new reader helps our sellers accept chip cards and NFC payments, and our Cash app lets people pay each other back instantly. We’re empowering the independent electrician to send invoices, setting up the favorite food truck with a delivery option, helping the ice cream shop pay its employees, and giving the burgeoning coffee chain capital for a second, third, and fourth location. Let’s shorten the distance between having an idea and making a living from it. We’re here to help sellers of all sizes start, run, and grow their business—and helping them grow their business is good business for everyone.
  151.  
  152. Job Description
  153.  
  154. The Knowledge Platform team is seeking senior machine learning engineers to join our engineering team. Square is seeking senior machine learning engineers to build a company-wide state-of-the-art knowledge platform. Our goal is to provide tooling, infrastructure, and guidance to unify and level up the 50-100 engineers and data scientists working on ML at Square and work on advanced ML solutions that are applicable across the company. The ideal candidate will have industry experience in solving and optimizing large-scale machine learning problems. We are looking for passionate and self-driven innovators to help us build this V1 platform from the ground up and be part of a fast-paced team. You will be expected to contribute in building ML systems/tooling and building advanced ML models that scale. You will have a wide impact across the company with opportunity to publish papers, contribute to open-source, influence and collaborate with the data science community across Square.
  155.  
  156. You Have
  157.  
  158. Qualifications
  159. Experience in many of the following areas is highly desired - AutoML, Knowledge Graphs, recommendation systems, NLP and AI Agents.
  160. Experience with cloud computing platforms, such as AWS, Google Cloud or Azure.
  161. Experience in designing and productionizing large-scale distributed systems built around machine learned models and big data.
  162. Experience or familiarity with interpretable machine learning is a plus.
  163. Ability to produce scalable and robust production-quality code incorporating testing, evaluation, and monitoring.
  164. An advanced degree (PhD or MS) in Computer Science
  165.  
  166. Technologies We Use
  167. Java, Python, Google Cloud Platform, AWS, Snowflake
  168. Python ML stack (pandas, scikit-learn, etc.)
  169.  
  170. Additional Information
  171.  
  172. At Square, we value diversity and always treat all employees and job applicants based on merit, qualifications, competence, and talent. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status. We will consider for employment qualified applicants with criminal histories in a manner consistent with the requirements of the San Francisco Fair Chance Ordinance. Applicants in need of special assistance or accommodation during the interview process or in accessing our website may contact us by sending an email to assistance(at)squareup.com. We will treat your request as confidentially as possible. In your email, please include your name and preferred method of contact, and we will respond as soon as possible.
  173.  
  174. Requirements
  175.  
  176. Job Requirements:
  177. Strong background in parallel programming and image processing algorithm design;
  178. Strong background in Computer Vision, Machine Learning and data mining;
  179. Solid experience in C#, C/C++ programming;
  180. Experience in feature extraction/ selection, classifier design is essential;
  181. Knowledge in computer architecture or familiar with semiconductor equipment development is a plus.
  182. 0GaoMEpbyE
  183. Seniority Level
  184. Entry level
  185.  
  186. Industry
  187. Information Technology & Services Computer Software Financial Services
  188. Employment Type
  189. Full-time
  190.  
  191. Job Functions
  192. Engineering Information Technology
  193.  
  194. Are you an engineer who’s interested in tackling very challenging adversarial problems and passionate about defending online users against abuse, spam, and manipulation? Do you love working on challenging problems that require a multi-disciplinary approach, creative solutions, and rapid product iterations? Will you be proud to work on a real-time, scalable system that serves millions of users daily? If so, you should join us.
  195.  
  196. Who We Are
  197.  
  198. The Health ML engineering team is responsible for building scalable detection systems that keep spam, manipulation, and abuse at bay. We use ML and relevance techniques to make Twitter safer and to limit the spread of misinformation on the platform. Our team works across the product to detect abusive and spammy users and content, increase action on bad actors, drive changes in user behavior, and detect and remediate accounts that are violating the terms of service on Twitter.
  199.  
  200. We develop, maintain, and contribute to several machine learning models and systems, including:
  201. Models that detect unwanted interactions
  202. Models to prioritize human review of accounts violating Twitter's policies to more quickly take action and limit their damage
  203. Detection of bots that misuse the platform or spread misinformation
  204. Detection of repeat abusive offenders who create new accounts after being suspended
  205. Real-time rule engines and clustering systems to identify and action on clusters of bad actors at scale
  206.  
  207. What You’ll Do
  208.  
  209. Although you will work on cutting-edge problems, this position is not a pure research position. You will participate in the engineering life-cycle at Twitter, including designing distributed systems, writing production code and data pipelines, conducting code reviews and working alongside our infrastructure and reliability teams. You’ll apply data science, machine learning, and/or graph analysis techniques to a variety of modeling and relevance problems involving users, their social graph, their tweets, and their behavior.
  210.  
  211. Who You Are
  212.  
  213. You’re a relevance engineer, applied data scientist, or machine-learning engineer who wants to work on exciting algorithmic and deep infrastructure issues to improve the health of the public conversation on Twitter. You’re experienced at solving large scale relevance problems and comfortable doing incremental quality work while building brand new systems to enable future improvements.
  214. You are knowledgeable in one or more of the following: machine learning (including deep learning), information retrieval, recommendation systems, social network analysis.
  215. You are a strong technical advocate with a background in Java, C++, or Scala, and Python.
  216. You strive to find the right balance between moving fast to deliver quality improvements to users and accumulating technical debt that drags down productivity.
  217. You have a collaborative working style with a strong focus on disciplined execution and results.
  218. You like to ground decisions in data and reasoning and solve root causes of problems rather than surface issues.
  219. You are adept at communicating relevant information clearly and concisely.
  220. You look ahead to identify opportunities and thrive in a culture of innovation.
  221.  
  222. Here’s All The Legal Good Stuff
  223.  
  224. We are committed to an inclusive and diverse Twitter. Twitter is an equal opportunity employer. We do not discriminate based on race, ethnicity, color, ancestry, national origin, religion, sex, sexual orientation, gender identity, age, disability, veteran, genetic information, marital status or any other legally protected status.
  225.  
  226. San Francisco applicants: Pursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.
  227.  
  228. By applying for this role, you could choose to work in the following locations:
  229. US - Remote US
  230. New York City
  231. Industry
  232. Internet
  233. Employment Type
  234. Full-time
  235.  
  236. Job Functions
  237. Engineering
  238.  
  239. Who We Are
  240.  
  241. Ocrolus is a growth stage company whose core competency is a proprietary set of workflows that use attended (or human-in-the-loop) machine learning and crowdsourcing for deep financial review (i.e. fraud, risk scoring, cash flow), data digitization, and automated decisioning of semi & unstructured documents. Because of our speed and accuracy, we are an industry standard in the FinTech lending space. Ocrolus can analyze and verify data across bank statements, paystubs, tax documents, and other financial records with over 99% accuracy and in minutes rather than days or weeks. Ocrolus has raised over $30 million from firms like Oak HC/FT, FinTech Collective, Bullpen Capital, and QED Investors, among others
  242.  
  243. Ocrolus has a diverse body of visual and language based tasks that could benefit from the application of modern machine learning methods. To this end, Ocrolus is looking to hire a Machine Learning Engineer to help identify where application of AI would make the most impact, and to deliver solutions in the identified areas.
  244.  
  245. Responsibilities
  246. Work with Product and Operations to understand the business, and the different problem spaces at play.
  247. Identify areas where ML could achieve disproportionate lift.
  248. Coordinate with Operations to describe data collection needs, and prescribe collection methodology.
  249. Design solutions that employ modern ML techniques for the purpose of performing image classification, image localization/ segmentation, natural language processing, and more.
  250. Deliver solutions that are highly performant and lead to a higher degree of automation across the Company.
  251.  
  252. Requirements
  253. BA./S. CompSci or CompEng or comparable Engineering degree.
  254. 3 years of applied machine learning experience.
  255. Fluency in Python.
  256. Expertise in at least one modern ML framework such as Keras, TensorFlow, or PyTorch.
  257. Why Ocrolus?
  258. We’re a seasoned team of engineers and operators, that understand the value of clean high quality data gathering. You will never feel alone in the trenches during the course of your work.
  259. We have a very mature data gathering operation already in place. Disseminating training materials and collection methodology is painless.
  260. There is a high degree of variety in the problems that are available to tackle.
  261. Our size and culture means a high degree of personal autonomy inherent in the day to day.
  262. Flexibility. We’re not married to an approach, framework, or provider. We’re willing to change when provided with compelling data.
  263.  
  264. We’re a young and rapidly growing FinTech company - if you have ever wanted to jump on a rocket ship as it’s taking off, now is your chance!
  265. Seniority Level
  266. Entry level
  267.  
  268. Industry
  269. Information Technology & Services Computer Software Financial Services
  270. Employment Type
  271. Full-time
  272.  
  273. Job Functions
  274. Engineering Information Technology
  275.  
  276.  
  277.  
  278. Who are we?
  279.  
  280. Ribbon is a first of its kind real estate technology company transforming the real estate transaction by delivering certainty, transparency and joy to the home buying process. Consumers and realtors deserve a better experience, and we have designed an open platform that welcomes everyone in the ecosystem to participate.
  281.  
  282. As members of the Ribbon team, we live out our mission every day through our core values:
  283. Be an invited guest to dinner - Everything we do is in the service of the customer.
  284. Be a (home) owner - If we see a problem, we address it head on without assuming someone else will do it.
  285. Break new ground - We challenge conventional wisdom to create clever solutions and break down the walls.
  286. Foster greatness - We grow and inspire the team around us to constantly make Ribbon better.
  287. Engage with intellectual humility - We become our best selves through rigorous debate and adjusting opinions based on new information.
  288.  
  289.  
  290. How You'll Help Make Homeownership Achievable
  291. Build production grade models on large-scale datasets by utilizing advanced statistical modeling, machine learning, or data mining techniques
  292. Leverage models to address key challenges such as improving home valuation accuracy, matching homebuyers with homes, and risk modeling.
  293. Work closely with product engineering to generate datasets based off of Ribbon product activity and propose new product features to collect unique data to help make the homebuying experience more magical for our customers.
  294. Conceptualize, design and build data-fueled insights to help improve analytics for prospects and customers
  295.  
  296.  
  297. What We're Looking For
  298. Communication - Strong written and verbal communication skills.
  299. Excellent judgment - We're an early stage start up and need to move fast, but home transactions are high stakes and we need to be compliant. We need you to understand when to move faster and when to take the time to get it right.
  300. Craftsmanship - You care about writing good code and building great software. You understand the trade-offs when we have to move faster, but you know what perfect means and how to get there when we need to.
  301. Ownership mentality - Every engineer & product at Ribbon will rely on the APIs and services you'll build. You're excited about working with engineering stakeholders to build robust and reliable services.
  302.  
  303.  
  304. You Have
  305. Knowledge of and experience using one or more of machine learning frameworks such as Tensorflow, Keras, sklearn, pytorch to build production-ready models
  306. Experience building and optimizing data pipelines, architectures and data sets is a plus
  307. Knowledge of and experience using data tools such as Spark and Airflow for bonus points
  308. Ability to design and implement novel analytical approaches in response to open-ended problems
  309. Experience in driving real world product or feature decisions based on your analysis
  310.  
  311. Interested? Read more about our engineering culture here!
  312.  
  313. Even if you don't meet all the requirements, we encourage you to apply! If you'd be excited to show up for work each day, we'd be excited to have you on our team.
  314.  
  315. Here at Ribbon we're not scared of differences. It's how we break new ground. As we scale and we help families from every walk of life, the team we build must be reflective of the diversity that we serve. Together, we've built and will continue to grow, a diverse and inclusive culture where everyone has a seat at the table and the space to be their most authentic self. Ribbon is an Equal Opportunity Employer and we support, celebrate, and cherish all the things that make our teammates who they are.
  316. Seniority Level
  317. Entry level
  318.  
  319. Industry
  320. Internet Financial Services Real Estate
  321. Employment Type
  322. Full-time
  323.  
  324. Job Functions
  325. Engineering Information Technology
  326.  
  327.  
  328. We are seeking a highly-experienced ML Engineer to join our team building advanced Business Intelligence, Machine Learning, and Data Processing applications.
  329.  
  330. Your Impact
  331.  
  332. As a Backend Engineer, you will develop advanced tools that allow our customers to build highly-sophisticated Business Intelligence applications for their stakeholders. You will work as a member of an engineering “feature team,” responsible for delivering value to our customers. In this role, you will design, implement, and deliver enterprise-grade machine learning applications for both internal- and external-facing consumers. You will be part of a dynamic team of engineers who are developing cutting edge technology that fuels the premier BI platform in the industry. Your work will be deployed to production and used by dozens of major corporations such as FedEx, US Bank, and Mastercard to help drive their business goals and service their customers.
  333.  
  334. While mostly focusing in ML models productizing and data processing you will be expected to contribute to the model development. You believe that good design is the key to good coding -- “measure twice, cut once.” You write excellent-quality code (if you do say so yourself), and understand how to best practices of SW architecture, development and testing.
  335.  
  336. Responsibilities
  337. Collaborate with the product owner, technical lead, product designer, and other stakeholders to design, prototype and develop enterprise-class data intensive applications.
  338. Maintain existing code and make improvements to increase maintainability, performance, and scalability.
  339. Support software rollouts to production.
  340. Constantly improve code quality and test coverage.
  341. Understand full-stack dependencies to minimize regressions and attain improved designs.
  342. Guide and mentor junior engineers. Serve as team lead if appropriate.
  343.  
  344.  
  345. Qualifications
  346. BS/MS degree in Computer Science, Computer Engineering, or a related subject.
  347. 5+ years of demonstrated experience in Python.
  348. In-depth knowledge of Python data processing and machine learning libraries.
  349. Experience with and understanding of the Python ML frameworks such as TensorFlow and PyTorch
  350. Experience with API design & development
  351. Understanding of the data layer integration (both SQL and no-SQL)
  352. Experience with cloud deployments is a plus
  353. Understanding AWS / Azure / GCP data ETL capabilities is a plus
  354. Experience with C/C++, Java and/or Scala plus.
  355. Passion for writing well structured, testable code with a focus on readability and maintainability.
  356. Experience with open source CI tools is a plus.
  357. Data modeling experience is a plus.
  358. Excellent communication skills.
  359.  
  360. Information Builders helps organizations transform data into business value. Our software solutions for business intelligence and analytics, integration, and data integrity empower people to make smarter decisions, strengthen customer relationships, and drive growth. Our dedication to customer success is unmatched in the industry. That’s why thousands of leading organizations rely on Information Builders to be their trusted partner. Founded in 1975, Information Builders is headquartered in New York City, with offices around the world, and remains one of the largest independent, privately held companies in the industry.
  361.  
  362. Information Builders, Inc. is an Equal Opportunity Employer: All qualified applicants will receive consideration for employment and will not be discriminated against based on their race, gender, disability, veteran status, or other protected classification.
  363.  
  364. Seniority Level
  365. Entry level
  366.  
  367. Industry
  368. Computer Software Information Technology & Services
  369. Employment Type
  370. Full-time
  371.  
  372. Job Functions
  373. Engineering Information Technology
  374.  
  375. Our client Seres D client based in New York is looking for a Machine Learning engineer with practical experience writing production-quality code to join our growing team, working to address the challenge of understanding how differing messaging-based interactions between therapists and patients lead to differing behavioural health outcomes.
  376.  
  377. You will join a team of data scientists responsible for analyzing all aspects of Talkspace’s data to understand customer engagement, therapist quality of service, and clinical outcomes and develop data-driven product features that aim to continually improve behavioural health outcomes.
  378.  
  379. Who You Are
  380. You are comfortable working in a fast-paced startup environment.
  381. You are passionate about data and can communicate effectively with both data scientists, product managers, other engineers, and clinicians to discuss requirements, design, and expectations.
  382. You are excited about learning new tools/approaches that aren’t already a part of your toolkit.
  383. You can work independently and manage a list of priorities.
  384.  
  385. Skills
  386. Master’s degree, preferably in Computer Science, Data Science or an Engineering-related discipline
  387. 2+ years of work experience developing and deploying production-quality code
  388. Fluent in Python scripting, strong working knowledge of SQL
  389. Foundational knowledge of commonly used machine learning techniques, such as cluster analysis, classification methods, and linear and nonlinear regression modelling
  390. Experience developing applications using Natural Language Processing techniques.
  391. Excellent communication and interpersonal skills
  392. Experience working with cross-functional teams in a dynamic environment
  393.  
  394. Benefits
  395.  
  396. Monthly team outings, happy hours, in-house family-style lunches, office snacks, unlimited PTO, access to products, ping pong table, and competitive benefits are just some of the benefits on offer
  397. Seniority Level
  398. Entry level
  399.  
  400. Industry
  401. Information Technology & Services Computer Software Internet
  402. Employment Type
  403. Full-time
  404.  
  405. Job Functions
  406. Engineering Information Technology
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