Sr Data Scientist, Machine Learning (ML) Engineer
Work at Home, United States
Full Time Senior-level / Expert USD 120K - 150K
- Remote-first
- Website
- @EvolentHealth 𝕏
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Evolent
Evolent Health's family of brands is coming together under a single name — simply "Evolent" — to improve outcomes for people with the most complex and costly health conditions.Your Future Evolves Here
Evolent partners with health plans and providers to achieve better outcomes for people with most complex and costly health conditions. Working across specialties and primary care, we seek to connect the pieces of fragmented health care system and ensure people get the same level of care and compassion we would want for our loved ones.
Evolent employees enjoy work/life balance, the flexibility to suit their work to their lives, and autonomy they need to get things done. We believe that people do their best work when they're supported to live their best lives, and when they feel welcome to bring their whole selves to work. That's one reason why diversity and inclusion are core to our business.
Join Evolent for the mission. Stay for the culture.
What You’ll Be Doing:
What You Will Be Doing:
Design, develop, and deploy advanced machine learning models and algorithms to primarily improve the performance of our prior authorization platforms
Construct advanced SQL queries, perform preprocessing, feature engineering, and transformations to analyze healthcare data and ensure high quality input for model training
Collaborate with Product and Engineering teams to integrate and deploy ML models into development and production environments, spread across various locations in the US and India
Work closely with clinicians and stakeholders to drive the development, efficacy, and improvement of our ML models
Work with Infrastructure and Architecture teams to drive model efficiency, reliability, and scalability
Leverage Azure DevOps for continuous integration and continuous deployment (CI/CD) of ML models
Lead Machine Learning Operations (MLOps) to streamline the process of bringing a machine learning model into production, maintain, monitor, and identify opportunities for improvement
Perform data mining as necessary to uncover insights, drive decision-making, and determine best channel approaches to drive automation across our platforms
Implement feature flagging to rapidly pilot model enhancements, exception handling, and performance optimization
Translate complex technical details into clear, actionable insights for stakeholders by telling stories through data
Stay current with the latest advancements in ML and AI; testing and integrating new techniques into existing applications
Mentor and guide junior engineers, fostering a culture of continuous learning and improvement
Required Qualifications:
Bachelor’s Degree in Computer Science, Machine Learning, Data Science, or a related field requires; Master’s Degree or Ph.D. in Computer Science, Machine Learning, Data Science, or a related field is preferred
Proficiency in Python for constructing data pipelines, and using ML frameworks and libraries such as Keras, PyTorch, Scikit-Learn, TensorFlow, and XGBoost
Expertise in statistical methods, data structures, algorithms, feature engineering, transformations, and data mining
2+ years advanced experience in SQL, including experience writing new and efficient SQL queries for complex analytical tasks
2+ years of experience developing in a cloud environment (AWS, GCS, Azure)2+ years of experience with Github, Github Actions, CI/CD, and source control
2+ years working within an Agile environment
Proven experience with developing and deploying ML systems into production environments
Healthcare experience, particularly using administrative and prior authorization data, with a passion for solving problems within healthcare that have tangible impacts on healthcare operations and patient lives
Excel in solving ambiguous and complex problems, being able to navigate through uncertain solutions, breaking down complex challenges into manageable components, and developing innovative solutions
Experience working with Product, Engineering, Infrastructure, and Architecture teams
Proficiency using Azure cloud-based services and infrastructure, Azure ML Studio, and Azure MLOps is preferred
Experience with deep learning, reinforcement learning, NLP, and LLMs is preferred
Experience with feature flagging is preferred
Publications or contributions to the machine learning community is preferred
Technical Requirements:
We require that all employees have the following technical capability at their home: High speed internet over 10 Mbps and, specifically for all call center employees, the ability to plug in directly to the home internet router. These at-home technical requirements are subject to change with any scheduled re-opening of our office locations.
Evolent is an equal opportunity employer and considers all qualified applicants equally without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, veteran status, or disability status. If you need reasonable accommodation to access the information provided on this website, please contact recruiting@evolent.com for further assistance.
The expected base salary/wage range for this position is $120,000 - 150,000. This position is also eligible for a bonus component that would be dependent on pre-defined performance factors. As part of our total compensation package, Evolent is proud to offer comprehensive benefits (including health insurance benefits) to qualifying employees. All compensation determinations are based on the skills and experience required for the position and commensurate with experience of selected individuals, which may vary above and below the stated amounts.Tags: Agile Architecture AWS Azure CI/CD Computer Science Data Mining Data pipelines Deep Learning DevOps Engineering Excel Feature engineering GitHub Keras LLMs Machine Learning ML models MLOps Model training NLP Pipelines Python PyTorch Reinforcement Learning Scikit-learn SQL Statistics TensorFlow Testing XGBoost
Perks/benefits: Career development Health care Insurance
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