Data Scientist

Straive; Bengaluru; Vor Ort; INR 280.000 - 420.000; Vollzeit

Zusammenfassung

Straive in Bengaluru is seeking Data Scientists to develop advanced pricing, demand-forecasting, promotion-effectiveness, and competitor-pressure models. The role translates complex retail data into interpretable recommendations that improve revenue, margin, price competitiveness, promotional effectiveness, and customer value.

The Data Scientist will work with transaction history, product hierarchies, prices, promotions, inventory, competitor prices, customer behaviour, seasonality, and external

Qualifikationen

• Strong Python and SQL skills.
• Experience with Pandas, NumPy, Scikit-learn and statistical modelling.
• Solid foundation in probability, hypothesis testing, regression and forecasting.
• Experience with time-series forecasting, feature engineering and model validation.
• Exposure to logistic/linear regression, random forests, XGBoost, LightGBM and ensemble methods.
• Understanding price elasticity, demand response and promotion analytics.
• Ability to explain findings to commercial stakeholders.
• Experience with large datasets on BigQuery, Spark or similar cloud platforms.

Aufgaben

• Develop pricing, demand-forecasting, promotion-effectiveness and competitor-pressure models.
• Translate complex retail data into interpretable recommendations to improve revenue and margins.
• Work with transaction history, product hierarchies, prices, promotions, inventory, and external factors.
• Validate models, tune hyperparameters and ensure robust performance.
• Communicate insights to commercial teams using visualizations.

Kenntnisse

Python

SQL

Pandas

NumPy

Scikit-learn

Time-series forecasting

Feature engineering

Model validation

Hyperparameter tuning

Probability & statistics

Regression modelling

Ensemble methods

Bayesian modelling

Explainability

Tools

BigQuery

Spark

GCP

Vertex AI

Tableau

Jobbeschreibung

Cloud Platform: Preferably Google Cloud Platform, AWS and Azure

Role Summary

Seeking Data Scientists to develop advanced pricing, demand-forecasting, promotion-effectiveness, and competitor-pressure models. The role will translate complex retail data into interpretable recommendations that improve revenue, margin, price competitiveness, promotional effectiveness, and customer value.

The Data Scientist will work with transaction history, product hierarchies, prices, promotions, inventory, competitor prices, customer behaviour, seasonality, and external factors to develop statistically defensible models and actionable insights. Competitor-pressure modelling may incorporate relative price indices, competitive price gaps, product-match confidence, price positioning, and competitive-response effect.

Mandatory Skills

Strong Python and SQL skills.

Proficiency in Pandas, NumX, Scikit-learn, statistical modelling, and

Strong foundation in probability, hypothesis testing, confidence intervals, regression, experimentation, and predictive modelling.

Experience with time-series forecasting, feature engineering, model validation, and hyperparameter tuning.

Knowledge of Logistic and Linear Regression, Random Forest, XGBoost, LightGBM, clustering, and ensemble methods.

Understanding of price elasticity, demand response, promotion uplift, and commercial performance metrics.

Experience handling seasonality, outliers, missing values, sparse data, class imbalance, and changing data distributions.

Ability to explain analytical findings to commercial and nontechnical stakeholders.

Experience working with large datasets on BigQuery, Spark, or another cloud

Preferred Experience

Retail pricing, merchandising, promotion analytics, assortment optimization, or revenue management.

Causal impact, uplift modelling, Bayesian modelling, or hierarchical forecasting.

Product matching and competitor-price analytics.

Mathematical optimization subject to margin, inventory, competitive, and Vertex AI, BigQuery ML, or GCP-based model-development experience.

Power BI, Tableau, or Looker for result communication.