Junior Data Scientist

Overview

Junior Data Scientist

 

The Junior Data Scientist will apply modern programming, statistical, and machine learning techniques to healthcare claims data, supporting the detection of fraud, waste, and abuse (FWA). This role is designed for an early-career professional who combines strong technical skills with a desire to learn the nuances of healthcare analytics and compliance. You will contribute directly to protecting healthcare programs by uncovering fraudulent or wasteful billing practices, working alongside experienced investigators and data scientists. This position reports to the Data Supervisor and is 100% remote.

Responsibilities/ Requirements

 Responsibilities:

• Analyze large healthcare claims datasets to identify anomalies, fraud indicators, and suspicious billing practices.
• Write efficient, production-quality code in Python, R, and SQL for data cleaning, transformation, and modeling.
• Build and evaluate predictive and anomaly detection models to generate leads for investigative teams.
• Develop, document, and automate repeatable workflows in Databricks or similar platforms.
• Collaborate with investigators, compliance staff, and law enforcement partners by translating analytic results into actionable case insights.
• Create dashboards and visualizations in Tableau, Power BI, or Sigma to communicate findings clearly.
• Maintain proper documentation, confidentiality, and chain of custody for all datasets and analysis.
• Stay current with fraud schemes, healthcare regulations, and analytic methods; proactively contribute new approaches.

 

Required Qualifications:

• Proficiency with database and analytic programming languages such as SQL, Python, R and/or other applications to perform diverse types of data analysis and/or data science.

• Bachelor’s degree in Data Science, Statistics, Mathematics, Computer Science, or a related field.

• Minimum 1 year of professional or academic experience analyzing large datasets (internship or research acceptable).
• Proficiency in Python, R, and SQL with examples of prior projects (portfolio or code samples encouraged).
• Hands-on experience with data wrangling and feature engineering for structured datasets.
• Demonstrated ability to work with relational databases and query optimization.
• Strong written and verbal communication skills to explain complex results to non-technical audiences.
• Proven problem-solving and critical-thinking abilities.

Preferred Qualifications:

• Experience with healthcare claims data (Medicare, Medicaid, Commercial).
• Knowledge of coding systems (ICD-9/10, CPT, HCPCS, DRG).
• Familiarity with fraud detection techniques such as outlier analysis, clustering, and predictive modeling.
• Exposure to Databricks or other distributed computing platforms.
• Experience building visualizations and reports in Tableau, Power BI, or Sigma.
• Graduate degree (MA/MS) in a quantitative discipline.

 

Educational/Experience Qualifications:

• Bachelor’s Degree in Mathematics, Statistics, Healthcare Administration, Data Science, or related discipline with preference given to MA or MS recipients, and/or relevant work experience as a data analyst (Or similar position)
• Strong SQL skills and proven proficiency with analytic platforms such as Python, R, SAS, or similar.
• Knowledge of various database management systems in order to input, extract or manipulate information.
• Experience and knowledge of healthcare information (health claims data; specifically, , ICD-9-CM and ICD-10-CM codes, CPT, HCPCS, DRG, 837P, etc.) is a plus.

Benefits

• Medical, Dental, Vision plans
• Life, LTD and STD paid by the employer
• 401(k) with company match up to 4%
• Paid Time Off and company paid holidays
• Tuition assistance after 1 year of service

 

The salary range for this role is $75,000 to $90,000 annually.  This is the lowest to highest salary we in good faith believe we would pay for this role at the time of this posting. We may ultimately pay more or less than the posted range, and the range may be modified in the future.  An employee’s pay position within the salary range will be based on several factors including, but not limited to, relevant education, qualifications, certifications, experience, skills, geographic location, performance, and business or organizational needs.