SUMMARY
The Data Scientist Manager is a hands-on technical and people leader responsible for design, development, and deployment of machine learning solutions that turn enterprise data into actionable predictions and recommendations. This hands-on role advances the Data Management team’s predictive analytics capabilities and deliver measurable improvements across operations, finance, workforce, and quality using= modern tech stack (Azure, Snowflake, dbt and Python)
The role provides technical direction and mentorship to an emerging AI/ML team, including analytics engineers transitioning into machine learning. Partners with business stakeholders, enterprise architecture, data engineering, and analytics teams to develop reliable, reusable AI data products.
ESSENTIAL JOB FUNCTIONS
To perform this job successfully, an individual must be able to satisfactorily perform each essential function listed below.
- Translate business opportunities into clearly defined ML use cases, success measures, and delivery priorities.
- Develop forecasting, classification, anomaly detection, and optimization solutions for use cases such as census and admissions forecasting, revenue cycle performance, and incident risk analysis.
- Identify and validate leading indicators, external influences, and operational drivers that improve predictions.
- Perform exploratory analysis, feature engineering, and assessment of data suitability in partnership with data engineers and business subject matter experts.
- Establish baseline models and evaluate alternatives using appropriate statistical methods, time-based validation, and business impact measures.
- Prevent data leakage and assess model bias, explainability, uncertainty, and performance across relevant populations.
- Deploy and maintain models using approved Snowflake and Azure capabilities, partnering with engineering and operations on production integration.
- Establish model versioning, experiment tracking, monitoring, retraining criteria, and reproducible development practices.
- Communicate model findings, limitations, and recommend business actions to technical and executive audiences.
- Collaborate with cross-functional teams including analysts, data engineers, and business leaders to embed models into dashboards, workflows
- Lead and mentor assigned team members, review technical work, and establish practical AI/ML development standards.
- Partner with Front End Developer to incorporate predictive outputs into agents and business applications.
- Perform other related duties and activities as required.
SUPERVISORY RESPONSIBILITIES
- Manages assigned personnel. Completes performance evaluations, orientation, and training. Makes decisions on employee hires, transfers, promotions, salary changes, discipline, terminations, and similar actions. Resolves employee problems within position responsibilities.
Minimum Knowledge and Skills required for the Job
The requirements listed below are representative of the knowledge, skill, and/or abilities required to perform the job.
Education and Experience:
- Bachelor’s degree in data science, statistics, mathematics, computer science, or a related field, or equivalent practical experience. Master’s degree preferred (or equivalent industry experience)
- 5 years in applied data science or machine learning experience, including deployment of models into production
- Strong Python and SQL skills and experience with common statistical and machine learning libraries.
- Demonstrated expertise in time series forecasting, feature engineering, model evaluation, and statistical analysis.
- Experience working with cloud data platforms and production ML workflows.
- Ability to connect analytical results to business decisions and measurable outcomes.
- Experience providing technical leadership, mentoring engineers or data scientists, and collaborating across teams.
- Experience with Snowflake, Snowpark, Azure Machine Learning, dbt, and MLflow preferred
- Experience with healthcare services, financial operations, workforce analytics, or other regulated environments.
Other Requirements:
- Travel as needed
Physical Requirements:
- Sedentary work. Exerting up to 10 pounds of force occasionally and/or negligible amount of force frequently or constantly to lift, carry, push, pull or otherwise move objects, including the human body. Sedentary work involves sitting most of the time. Jobs are sedentary if walking and standing are required only occasionally and all other sedentary criteria are met.
Sevita is a leading provider of home and community-based specialized health care. We believe that everyone deserves to live a full, more independent life. We provide people with quality services and individualized supports that lead to growth and independence, regardless of the physical, intellectual, or behavioral challenges they face.
We’ve made this our mission for more than 50 years. And today, our 40,000 team members continue to innovate and enhance care for the 50,000 individuals we serve all over the U.S.
As an equal opportunity employer, we do not discriminate on the basis of race, color, religion, sex (including pregnancy, sexual orientation, or gender identity), national origin, age, disability, genetic information, veteran status, citizenship, or any other characteristic protected by law
Bachelor's degree in data science, statistics, mathematics, computer science or related field; 5+ years applied data science/ML experience; strong Python and SQL; production ML workflows; technical leadership and mentoring; travel as needed.
Key Responsibilities
- developing machine learning models
- mentoring team members
- deploying models
Skills & Tools
Python, SQL, Azure, Snowflake, dbt, MLflow, Azure Machine Learning, Snowpark
Job Details
- Category: Data and Analytics
- Seniority: Senior Level
- Commitment: Full Time
- Workplace: Remote — United States
- Languages: English
About Sevita
A leading provider of home and community-based specialized health care. — Industry: Healthcare