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Lead Data Scientist - Forecasting

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Hybrid

Lead Data Scientist - Forecasting

Tredence Inc.

Lead Data Scientist - Forecasting

Skills

Google Cloud PlatformSQL QueriesData EngineeringDeep LearningE-commerce WebsitesPythonData SciencePyTorchTensorFlowRSnowflakeDatabricksData AnalysisMachine LearningAWSHadoopSupply ChainAzure

21 days ago

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Important information


Contract type:

Permanent

Location:

Bengaluru, Karnataka, India

Work mode:

Hybrid

Published on:

5 October 2026

What they need


Lead Data Scientist / Manager - Data Science (Forecasting)

Role Summary

We are seeking an experienced Lead Data Scientist / Manager - Data Science with strong expertise in forecasting, predictive analytics, machine learning, and statistical modeling.

The ideal candidate will lead the design and deployment of forecasting solutions that drive strategic business decisions across areas such as revenue planning, demand forecasting, workforce planning, supply chain optimization, and customer analytics.

This position requires a blend of technical excellence, business acumen, stakeholder management, and team leadership.

Key Responsibilities

Forecasting & Predictive Analytics-

  • Build and deploy forecasting models for business metrics such as sales, demand, revenue, customer growth, inventory, and workforce planning.

  • Develop time series forecasting models using techniques such as:

  • ARIMA/SARIMA

  • Prophet

  • Exponential Smoothing

  • XGBoost

  • Random Forest

  • Deep Learning models (LSTM, Transformer-based forecasting)

  • Evaluate forecast accuracy and continuously improve model performance.

  • Conduct scenario analysis and what-if simulations to support business planning.

Data Science Leadership

  • Lead a team of data scientists, analysts, and ML engineers.
  • Mentor and coach team members on advanced analytics and machine learning techniques.
  • Define project roadmaps, priorities, and delivery timelines.
  • Establish best practices for model development, validation, and deployment.

Stakeholder Management

  • Collaborate with business leaders to understand forecasting requirements.
  • Translate business problems into analytical solutions.
  • Present insights, recommendations, and forecasts to senior leadership.
  • Drive adoption of data-driven decision-making across the organization.

Machine Learning & Model Development

  • Design end-to-end ML solutions from data preparation to production deployment.
  • Develop predictive and prescriptive analytics solutions.
  • Monitor model performance and ensure model governance standards are followed.
  • Work with engineering teams to productionize models.

Data Engineering & Analytics

  • Work with large-scale structured and unstructured datasets.
  • Build feature engineering pipelines and data quality frameworks.
  • Ensure scalable and efficient data processing using cloud platforms and distributed computing frameworks.

Required Qualifications Education

  • BE/BTech / MSc Statistics/ Phd

Experience

  • 8-12+ years of overall analytics/data science experience.
  • 3-5+ years leading data science teams.
  • Strong hands-on experience in forecasting and predictive modeling.
  • Experience delivering forecasting solutions in production environments.

Technical Skills-

Programming

  • Python
  • SQL
  • R (preferred)

Forecasting & Statistics

  • Time Series Analysis
  • Forecast Accuracy Metrics (MAPE, RMSE, WAPE)
  • Statistical Modeling
  • Econometrics
  • Experimental Design

Machine Learning

  • Scikit-learn
  • XGBoost
  • LightGBM
  • TensorFlow/PyTorch

Cloud Platforms

  • Azure
  • AWS
  • GCP

Data Technologies

  • Databricks
  • Spark
  • Snowflake
  • Hadoop (preferred)

Preferred Industry Experience

  • Retail
  • FMCG
  • E-commerce
  • Manufacturing
  • Supply Chain
  • Banking & Financial Services
  • Technology

Leadership Competencies

  • Team Leadership
  • Strategic Thinking
  • Stakeholder Management
  • Executive Communication
  • Problem Solving
  • Project Management
  • Cross-functional Collaboration

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