Senior Analyst - Data Science at Eaton USA

Pune, maharashtra, India -

Full Time

Start Date

Immediate

Expiry Date

24 Mar, 26

Salary

0.0

Posted On

24 Dec, 25

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Data Science, Statistical Modeling, Causal Inference, Experimental Design, Machine Learning, Natural Language Processing, Python, R, SQL, Power BI, Data Visualization, Analytical Rigor, Documentation Excellence, Communication, Storytelling, Problem Solving

Industry

electrical;Appliances;and Electronics Manufacturing

Description

What you’ll do: Overview Are you ready to shape the future of workforce strategy through data? As a Senior Analyst (Data Science) in our Workforce Insights Team, you’ll lead high-impact, end-to-end analytics initiatives that drive smarter, more strategic decisions across HR and business functions. This role is ideal for someone who thrives at the intersection of advanced statistical modeling, causal inference, and real-world problem solving. You’ll architect robust analytical solutions, from framing complex workforce challenges to designing scalable models and experiments that deliver actionable insights. We’re looking for a data science professional who: • Translates complex datasets into clear, compelling narratives for stakeholders. • Designs and implements high-quality, reproducible models with lasting business impact. • Champions analytical rigor, documentation excellence, and solution scalability. If you’re passionate about using data to unlock workforce potential and influence enterprise-wide decisions, this is your opportunity to make a measurable difference. What you’ll do Data science & experimentation • Frame ambiguous workforce problems into testable hypotheses; choose fit‑for‑purpose methods and clearly communicate assumptions and limitations. • Apply statistical techniques like hypothesis testing, regression, causal inference, survival/time‑series, and ensemble methods to drive actionable recommendations. • Use ML/NLP across structured and unstructured HR data (e.g., text from surveys or talent profiles); design A/B or quasi‑experiments where appropriate. Build & operate • Develop production‑ready pipelines and models in Python/R with SQL; publish decision‑ready visuals in Power BI (or equivalent). • Establish reproducibility (versioning, environments, modular code) and monitoring (drift, performance, fairness) with clear runbooks and documentation. • Partner with data engineering on ETL/ELT and analytics engineering best practices to ensure scalability and reliability. Governance & responsible AI • Handle HR data with care: follow Eaton’s Data Protection standards for PII/SPII, privacy‑by‑design, access controls, and model transparency. Stakeholder partnership & impact • Co‑create problem statements, success metrics, and acceptance criteria with HR and business leaders; communicate insights for non‑technical audiences. • Connect insights into decisions and outcomes (e.g., quality of hire, retention, productivity, org health); quantify impact and document learning. • Lead medium‑to‑large analytics projects with minimal oversight; coach peers on methods and code quality; contribute re‑usable components and standards. Qualifications: • Bachelor’s degree in Statistics, Data Science, Engineering, Computer Science, or related field or equivalent practical experience; master’s preferred. • 6-8 years of applied data science/advanced analytics, ideally in People/Workforce Analytics or adjacent domains with sensitive data. Skills: • Proficiency in Python (pandas, scikit‑learn/statsmodels), R, and dashboards in Power BI (or similar). • Strong grounding in statistical modeling, causal inference, experimental design, and time‑series. • Demonstrated ability to translate complex analyses into clear recommendations for senior stakeholders. • Excellent communication and storytelling.

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Responsibilities

The Senior Analyst will lead analytics initiatives that drive strategic decisions across HR and business functions. This includes framing workforce problems, applying statistical techniques, and developing scalable analytical solutions.