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 robust 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) 67 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, NumPy, Statsmodels, 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) LangChain / LlamaIndex 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 Solid data storytelling skills for non-technical stakeholders Ability to explain

statistical and predictive results clearly and confidently

Education Bachelors or Masters degree in

Statistics, Mathematics, Data Science, Computer Science Role Overview We are seeking a