Senior IT Data Scientist

Centene Corporation

1d•Hybrid

About The Position

Designs and develops scalable solutions using AI tools and machine-learning models. Performs research and testing to develop machine learning algorithms and predictive models. Utilizes big data computation and storage tools to create prototypes and datasets. Conducts model training and evaluation. Integrates, tests, tunes, and monitors solutions. Participates in model brainstorming conversations with new potential internal customers interested in AI/ML capabilities. Works alongside internal customers that are requesting AI/ML capabilities to understand overall business objective & impact when requesting an AI/ML model. Analyzes use cases of ML algorithms and apply findings to enable business decisions by deriving insights through data visualization. Writing moderately complex SQL and Python/R code to extract data from a variety of databases and data sources. Explores and visualizes data to gain an understanding of it and verify data quality, and/or ensure data quality via data cleaning. Conduct exploratory data analysis from complex data sources and build key data sets to support company mission operational analysis. Builds ML/AI models using common methods within R and Python. Analyzes the ML algorithms that could be used to solve a given problem and rank them by their success probability. Analyzes errors of the model and design strategies to overcome errors. Develop logging, alerting, and mitigation strategies for handling model errors. Development of AI/ML models to distinguish relevant content or events and recognize patterns. Designs and develops AI/ML models to predict member outcomes or future impact of key member decisions. Evaluate and design experiments to monitor key model metrics and identify improvement opportunities. Participate in presentations and communicate results of research analysis and findings to non-technical business partners. Produces fairness review for each developed model, to ensure model is free of bias. Set up continuous integration/continuous deployment (CI/CD) pipelines used for model automation. Model deployment with containers such as Kubernetes and/or Docker. Produce clean & readable code that has been properly unit tested and optimized for performance. Completes proper deployment integration testing to ensure seamless deployment. Maintains and supports AI/ML patterns by reviewing and solving issues and running ML/AI models. Assists in leading team-wide initiatives that help develop templates and define best practices to improve model building and deployment workflow (ex. Model drift detection). Performs other duties as assigned. Complies with all policies and standards.

Requirements

A Bachelor's degree in a quantitative or business field (e.g., statistics, mathematics, engineering, computer science) and Requires 4 – 6 years of related experience Or equivalent experience acquired through accomplishments of applicable knowledge, duties, scope and skill reflective of the level of this position
4+ years experience with SQL required
4+ years experience in developing Machine Learning/AI/Predictive models in R or Python required
4+ years Intermediate knowledge of Git required
Experience leading and mentoring a team required
Experience with SQL
Experience with Machine Learning; Machine Learning Algorithms; Statistics
Knowledge of Python and/or R
Experience with Continuous Integration
Seeks to acquire knowledge in area of specialty
Ability to identify basic problems and procedural irregularities, collect data, establish facts, and draw valid conclusions
Ability to work independently
Demonstrated analytical skills
Demonstrated project management skills
Demonstrates a high level of accuracy, even under pressure
Demonstrates excellent judgment and decision making skills

Nice To Haves

Experience using Databricks Platform desired
Working knowledge of healthcare data preferred

Responsibilities

Designs and develops scalable solutions using AI tools and machine-learning models.
Performs research and testing to develop machine learning algorithms and predictive models.
Utilizes big data computation and storage tools to create prototypes and datasets.
Conducts model training and evaluation.
Integrates, tests, tunes, and monitors solutions.
Participates in model brainstorming conversations with new potential internal customers interested in AI/ML capabilities.
Works alongside internal customers that are requesting AI/ML capabilities to understand overall business objective & impact when requesting an AI/ML model.
Analyzes use cases of ML algorithms and apply findings to enable business decisions by deriving insights through data visualization.
Writes moderately complex SQL and Python/R code to extract data from a variety of databases and data sources.
Explores and visualizes data to gain an understanding of it and verify data quality, and/or ensure data quality via data cleaning.
Conducts exploratory data analysis from complex data sources and builds key data sets to support company mission operational analysis.
Builds ML/AI models using common methods within R and Python.
Analyzes the ML algorithms that could be used to solve a given problem and ranks them by their success probability.
Analyzes errors of the model and designs strategies to overcome errors.
Develops logging, alerting, and mitigation strategies for handling model errors.
Develops AI/ML models to distinguish relevant content or events and recognize patterns.
Designs and develops AI/ML models to predict member outcomes or future impact of key member decisions.
Evaluates and designs experiments to monitor key model metrics and identify improvement opportunities.
Participates in presentations and communicates results of research analysis and findings to non-technical business partners.
Produces fairness review for each developed model, to ensure model is free of bias.
Sets up continuous integration/continuous deployment (CI/CD) pipelines used for model automation.
Performs model deployment with containers such as Kubernetes and/or Docker.
Produces clean & readable code that has been properly unit tested and optimized for performance.
Completes proper deployment integration testing to ensure seamless deployment.
Maintains and supports AI/ML patterns by reviewing and solving issues and running ML/AI models.
Assists in leading team-wide initiatives that help develop templates and define best practices to improve model building and deployment workflow (ex. Model drift detection).
Performs other duties as assigned.
Complies with all policies and standards.