Über
Build, maintain, and support ETL/data pipelines to ensure reliable, accurate, and timely data delivery (SQL, Python).
Assist with testing, validation, and refinement of statistical and analytical models.
Conduct advanced analyses and validation checks on datasets and model outputs to ensure trustworthiness.
Identify data quality issues, anomalies, and inconsistencies and implement corrective solutions.
Collaborate with data engineering, product, and business partners to translate requirements into analytic solutions.
Write clear, maintainable analytical code, documentation, and unit tests following best practices.
Follow established data science standards, compliance requirements, and data governance practices.
Communicate findings and insights to stakeholders to inform strategy, product, and operations.
Minimum Qualifications
Bachelor’s degree in a quantitative/technical field OR 1+ year of relevant professional experience.
1+ years working with SQL and intermediate Python (pandas, numpy) for data manipulation and analysis.
Experience building data models and applying analytical methods beyond descriptive analytics.
Strong problem-solving skills, attention to data quality, and ability to work collaboratively in cross‑functional teams.
Clear written and verbal communication skills for presenting technical findings to non‑technical stakeholders.
Preferred / Nice‑to‑Have
Master’s degree in a quantitative field.
Experience in healthcare, health insurance, or other regulated industries (claims, clinical data).
Exposure to statistical modeling, machine learning workflows, or large‑scale data processing (Spark, Hadoop).
Familiarity with cloud platforms (AWS, GCP) and data orchestration tools (Airflow).
Experience with data visualization tools (Looker, Tableau) and A/B testing frameworks.
Knowledge of software engineering best practices, CI/CD, and productionizing models.
Compensation & Benefits
Base salary range: $119,200 – $156,450 per year.
Eligible for employee benefits, participation in an unlimited vacation program (or similar), company equity grants, and annual performance‑based bonuses.
Final offer within the posted range will depend on relevant skills, experience, and location.
Work Location & Schedule
Typical arrangement: hybrid schedule with on‑site days each week (commonly 3 days/week, including a core team meeting day). Confirm final worksite, hybrid requirements, and office location during the interview 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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Sprachkenntnisse
- English
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