Data Scientist
The Data Scientist at Confidential Client is responsible for designing, building, and deploying predictive models to enhance decision-making across various business areas such as marketing and client retention. This role involves end-to-end project ownership, collaboration with cross-functional teams, and translating complex data insights into actionable business strategies while maintaining high standards of data security and privacy.
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, Insurance.
Applicants for this role may also receive access to additional matched opportunities through the Careertakes platform.
What You’ll Do
- Design, build, and deploy predictive models that impact business decisions (examples: staffing optimization, marketing attribution, demand forecasting, client retention).
- Lead end-to-end data science projects — from exploratory analysis and feature engineering to modeling, validation, and production deployment.
- Analyze large, complex datasets to uncover patterns and provide actionable insights that guide strategy.
- Partner with business stakeholders to translate questions into measurable data problems and define success metrics.
- Collaborate with data engineering to shape data pipelines and infrastructure that support scalable ML workflows.
- Create clear, compelling visualizations and reports for technical and non-technical audiences.
- Promote reproducibility and quality via model governance, code review, documentation, and testing.
- Mentor junior data scientists and contribute to team best practices.
- Follow data security and privacy policies; handle client and company data with high confidentiality.
- Stay current on machine learning, AI, and data tooling and bring new ideas to the team.
Qualifications
- 5+ years of professional experience in data science, analytics, or another quantitative field.
- Strong programming skills in Python and experience with libraries such as pandas and scikit-learn.
- Proficient SQL skills and experience working with large-scale relational databases.
- Experience developing and validating predictive models and measuring business impact.
- Solid data visualization experience (Tableau or equivalent) and strong story-telling skills to explain complex results to stakeholders.
- Demonstrated ability to own projects end-to-end and deliver measurable outcomes.
Preferred Qualifications
- Experience with cloud platforms (AWS, Azure) and distributed computing frameworks (Spark).
- Experience deploying machine learning models to production (CI/CD, monitoring, model ops).
- Familiarity with design, testing, and deployment of custom LLMs or generative AI workflows.
- Background in insurance, financial services, or other regulated industries.
- Experience with A/B testing, causal inference, or experimentation frameworks.
Benefits
- Voluntary health, vision, life, disability, and dental insurance options.
- 401(k) matching.
- Employee Stock Purchase Plan.
- Paid holidays, vacation, and sick leave.
- Corporate-sponsored wellness and financial programs.
About the Team & Environment
This role is with a Confidential Client in the Insurance industry. You’ll join a cross-functional analytics and data engineering team focused on practical, measurable outcomes. The team values technical rigor, clear communication, and a product-oriented approach to data science.
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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