ResponsibilitiesWe are looking to add a Data Scientist to our team of talented professionals.
The Data Scientist will operate in a fast‑paced innovation environment, rapidly developing and validating proof‑of‑concepts for advanced AI and machine learning use cases. The role centers on experimenting with cutting‑edge models, integrating them into a cloud‑based analytics ecosystem, and helping move successful concepts toward operational deployment.
Responsibilities include:
- Hands‑on data exploration, prototyping, workflow automation, and contributing to secure, well‑governed MLOps practices.
- The Data Scientist will work closely with engineering and product teams to evaluate emerging tools, build technical demonstrations, document integrations, and communicate platform updates in a highly collaborative setting.
Qualifications
Required Qualifications:
- 2 years of experience with a Bachelor’s degree, 0 Years experience with a Master’s 6 years experience with HS Diploma/equivalent
- Hands‑on programming experience in Python and SQL.
- Experience using MLflow to support model governance within the model development lifecycle.
- Familiarity with software development lifecycle fundamentals and version control using GitHub.
- Experience working within cloud‑based analytics or modeling environments (such as Snowflake, Databricks, or similar platforms).
- Understanding of high‑performance or distributed compute environments used for data processing and model development.
- Ability to work collaboratively in a team‑oriented environment.
- Strong communication skills for supporting internal development teams and external stakeholders.
- Ability to obtain and maintain a Public Trust clearance.
- US citizenship or Green Card holder is required. Must have been in US for 3 years.
Desired Qualifications:
- Experience working with large language models, natural language processing techniques, or agentic/automation frameworks.
- Familiarity with modern deep learning approaches or experimentation with emerging AI capabilities.
- Hands‑on experience performing deep data exploration, feature engineering, or statistical/data modeling.
- Exposure to innovative or experimental AI/ML methodologies.
- Experience integrating or operationalizing AI/ML workflows within cloud‑based or distributed analytics environments (e.g. Spark).
- Familiarity with containerization concepts and basic use of Docker for packaging and running applications.
- Experience in healthcare industry analytics and data, preferably Medicare or Medicaid.
Target Salary Range$80,000 - $128,000. This represents the typical salary range for this position. Salary is determined by various factors, including but not limited to, the scope and responsibilities of the position, the individual’s experience, education, knowledge, skills, and competencies, as well as geographic location and business and contract considerations. Depending on the position, employees may be eligible for overtime, shift differential, and a discretionary bonus in addition to base pay.
