Data Scientist
The Data Scientist at Confidential Client is responsible for developing analytics and automation solutions primarily focused on healthcare patient claims data. This role involves applying advanced statistical and machine learning techniques to generate actionable insights that drive operational improvements, working closely with operations teams in a fast-paced, technology-driven environment.
About Careertakes
👉 Important disclosure: Careertakes is a third-party recruiting platform supporting this hiring process. If selected, you will be employed directly by our client, Pharmaceutical Manufacturing.
Applicants for this role may also receive access to additional matched opportunities through the Careertakes platform.
Key Responsibilities
- Partner with operations teams to identify analytics and automation opportunities tied to patient and claims workflows.
- Independently design, build, and maintain automation and analytics solutions using Python and/or R.
- Develop production-ready scripts, tools, and pipelines to automate recurring analysis and reporting.
- Analyze medical and pharmacy claims / patient-level datasets to generate actionable insights.
- Build, validate, and monitor machine learning and statistical models to support forecasting, segmentation, and predictive use cases.
- Translate model outputs and analytics into clear, data-driven recommendations for business stakeholders.
Minimum Qualifications
- Bachelor’s or M.Tech degree in Computer Science, Statistics, Data Science, Engineering, or a related field.
- Experience working in the Healthcare / Pharmaceutical domain, with exposure to patient claims data.
- High proficiency in Python; experience with R is a plus.
- Hands-on experience building and deploying machine learning models and analytic solutions.
- Proficient in SQL and familiar with relational database systems.
- Strong written and verbal communication skills in English.
- Experience with data visualization tools (Tableau, Power BI) is a plus.
Statistical Analysis & Modeling
- Solid understanding of descriptive and inferential statistics, hypothesis testing, confidence intervals.
- Experience with correlation, regression analysis, and probability distributions.
- Familiarity with sampling techniques, time series analysis, A/B testing, experimental design, and forecasting.
- Model validation, performance evaluation, and understanding of model assumptions/limitations.
- Ability to interpret statistical outputs and translate results into business recommendations.
Preferred Qualifications
- Strong problem-solving skills and the ability to deliver under tight deadlines.
- Flexibility to adapt to varied engagement types and working environments.
- Prior experience focused on patient analytics and claims-processing workflows.
- Positive drive and a collaborative mindset when working across cross-functional teams.
Compensation & Location
- Approximate annual base salary range: $90,000 to $100,000 (USD). The actual offer will be determined by experience, skills, geographic location, and internal equity, and may include benefits and other compensation components.
- This role is based in Morris Plains, NJ. Candidates must be located in the Morris Plains, New Jersey area to be eligible for this position. Candidates based in Los Angeles, California or Philadelphia, Pennsylvania are not eligible.
- Employment type: Full-time.
Notes on Hiring Process
- Careertakes will support application submission and screening as a third-party recruiting platform; final hiring decisions are made by our client.
- No fees are required to apply or participate in the hiring process.
Equal Opportunity & Hiring Transparency
Careertakes and our client are Equal Opportunity Employers committed to building a diverse and inclusive workforce. We prohibit discrimination or harassment of any kind. To support a fair and efficient hiring process, AI tools may be used to assist with application review or resume screening. These tools do not replace human decision-making. Final hiring decisions are made by people.
If you have questions about how your data is used, please contact us directly.
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