Data Scientist – Analytics & Prediction

Experience:

5–6 Years

Location:

[Hybrid / Remote / Onsite]

Employment Type:

Full-time

Role Overview

We are seeking a high-impact Senior Data Scientist with deep expertise in statistics, data analytics, and predictive modeling. This role is analytics-first and outcome-driven, requiring strong ownership of data interpretation, forecasting, and decision support. The ideal candidate can independently solve complex business problems using statistical rigor and build reliable prediction models. Exposure to machine learning and GenAI (RAG) is a strong advantage.

Core Responsibilities

- Own end-to-end analytics and prediction workflows from problem framing to business recommendations
- Perform deep statistical analysis to identify trends, correlations, and causal drivers
- Build, validate, and maintain predictive and forecasting models (time-series, regression-based, multivariate)
- Apply inferential statistics (hypothesis testing, confidence intervals, variance analysis) to support decisions
- Conduct EDA, feature engineering, and data preprocessing for high-quality predictions
- Translate ambiguous business questions into quantifiable analytical and predictive frameworks
- Deliver clear, data-backed insights to senior leadership with strong storytelling
- Ensure model accuracy, stability, and explainability over time

Must-Have Skills (Non-Negotiable)

- 5–6 years of hands-on experience in Data Science / Advanced Analytics
- Strong mastery of Statistics
- Descriptive & inferential statistics
- Regression analysis & Probability distributions
- Hypothesis testing
- Proven experience in Data Prediction & Forecasting
- Time-series analysis (trend, seasonality)
- KPI, demand, revenue, or operational prediction
- Advanced Python skills (Pandas, Num Py, Stats models, Scikit-learn)
- Strong SQL for complex analytical queries and data validation
- Ability to independently drive analytical projects and influence decisions

Strong Good-to-Have (ML & GenAI Exposure)

- Experience with machine learning models (classification, clustering, ensemble methods)
- Understanding of model evaluation, bias, and explainability
- Exposure to LLMs and RAG architectures, including:
- Embeddings and semantic search
- Vector databases (FAISS, Pinecone, Chroma)
- Lang Chain / Llama Index frameworks
- Experience integrating analytics outputs with AI-driven applications
- Cloud-based data & analytics environments (AWS / Azure)

Visualization & Communication

- Experience creating executive-level dashboards and analytical reports
- Strong data storytelling skills for non-technical stakeholders
- Ability to explain statistical and predictive results clearly and confidently

Education

- Bachelor’s or Master’s degree in Statistics, Mathematics, Data Science, Computer Science

What Sets This Role Apart

- Analytics and prediction are core responsibilities, not support functions
- High ownership and visibility with leadership
- Opportunity to extend traditional analytics into ML and GenAI (RAG) use cases
- Work on real, high-impact business problems