About this role

The Senior Data Scientist will play a pivotal role in our Data Science team, reporting directly to the Head of Data Science and collaborating closely with other data scientists, medical coding specialists, solutions managers, and digital marketing specialists. In this role, you will be responsible for researching, developing, and deploying machine learning algorithms aimed at identifying and prioritizing needs for various medical services. Additionally, you will optimize outreach efforts to enhance member engagement, promote utilization of medically appropriate services, and reduce churn and acquisition costs.

What you’ll do

• Machine Learning Algorithm Development:
  • Research, create, and deploy advanced machine learning algorithms to identify and prioritize medical service needs, optimizing outreach efforts for increased member engagement.
• Medical Code Proficiency:
  • Utilize expertise in medical codes, including ICD-10, CPT, PCS, along with non-medical data like SDoH and digital marketing data.
• Collaboration with Data Engineering and Product Teams:
  • Work closely with Data Engineering and Product teams to develop robust pipelines for data acquisition and model deployment.

• Data-Driven Decision-Making:
  • Advocate for data-driven decision-making by collaborating with stakeholders to translate business needs into data science questions.

• Promotion of Data-Centric Culture:
  • Serve as a data science advocate across the organization, assisting business leaders in understanding data science capabilities, identifying new use cases, and fostering a data-centric, evidence-based culture.

• Best Practices in Agile Project Management:
  • Model best practices in agile project management, code development, review, testing, deployment, and monitoring within the Data Science organization.

What we’re looking for

• Education:
  • Bachelor's or master's degree in computer science, Statistics, Mathematics, Data Science, or a related field.
• Experience:
  • 5 years of hands-on experience in developing and deploying machine learning models in a production environment.
• Skills and Abilities:
  • Strong focus on data-driven decision-making and problem-solving skills.
  • Ability to collaborate with stakeholders to translate business needs into data science questions.
  • Expertise in Python and machine learning libraries, including sklearn and TensorFlow.
  • Successful deployment of supervised, unsupervised, and reinforcement learning models to production.
  • Expert in SQL, Experience with no-SQL and semi-structured data
  • Familiarity with natural language processing techniques including modern transformer based LLMs.
  • Experience with data science platforms such as Snowflake, Databricks, Sagemaker, MLFlow, AWS EC2, S3, and Spark.
• Statistical Techniques:
  • Expert in statistical techniques, including hypothesis testing, experiment design, and online learning.
• Problem-Solving:
  • Strong problem-solving skills and the ability to work both independently and collaboratively within a team environment.
• Communication Skills:
  • Excellent written and verbal communication skills, facilitating effective collaboration and communication across teams.