Senior Data Scientist

Jobtailor; Bengaluru; On-site; INR 3,500,000 - 6,500,000; Full time

Job summary

Jobtailor in Bengaluru, India seeks a senior data science professional to build the next-gen forecast platform for global automotive demand and supply chain. You will architect transparent, AI-driven decision logic and develop a unified forecasting ecosystem that blends econometrics with advanced machine learning.

You will also build simulation engines, model price elasticity, and mentor junior team members while collaborating with senior data scientists on complex predictive systems.

Qualifications

• Master’s in data science, CS, econometrics, or statistics.
• 5+ years of professional experience developing ML models and predictive systems.
• Strong proficiency in Python, including scikit-learn and TensorFlow/PyTorch.
• Experience with ensemble methods such as XGBoost and Random Forest.
• Hands-on experience with LLMs and RAG architectures.
• Experience with demand forecasting, price elasticity modelling, or time-series analysis.
• Ability to explain complex logic to business stakeholders and turn it into transparent insights.
• Automotive sector experience is a plus.

Responsibilities

• Build the Next Gen Forecast Platform for global automotive demand and supply chain.
• Architect transparent, explicable, and rigorous AI-generated decision logic.
• Develop a unified forecasting ecosystem combining econometrics and AI.
• Build simulation engines using market drivers, price, and volume inputs.
• Develop demand-elasticity algorithms using pricing shifts and macro-economic indicators.
• Use machine learning for competitive-sector pattern recognition.
• Refine and scale hybrid rule-based and LLM systems for natural-language data querying.
• Implement MCP for data lineage and output explicability.
• Build LLM-driven agents translating natural-language intent into mathematical adjustments for scenario simulation.
• Design constraint-based feasibility logic respecting infrastructure, regulatory, and production limitations.
• Contribute to supply-chain optimization solvers balancing sales demand and supply constraints.
• Mentor junior talent and collaborate with senior data science team members.

Skills

ML model development

Demand forecasting

Time-series analysis

Python proficiency

LLMs

RAG architectures

Ensemble methods

Explainability

Automotive domain

Education

Master's in Data Science

Master's in Computer Science

Master's in Econometrics

Master's in Statistics

Tools

Python

Scikit-learn

TensorFlow

PyTorch

XGBoost

Random Forest

LLMs

RAG architectures

Job description

• Build the Next Gen Forecast Platform for global automotive demand and supply chain
• Architect transparent, explicable, and rigorous AI-generated decision logic
• Develop a unified forecasting ecosystem combining advanced econometrics and AI
• Build simulation engines using market drivers, price, and volume inputs
• Develop demand-elasticity algorithms using pricing shifts and macro-economic indicators
• Use machine learning for competitive-sector pattern recognition
• Refine and scale hybrid rule-based and LLM systems for natural-language data querying
• Implement Model Context Protocol (MCP) for data lineage and output explicability
• Build LLM-driven agents that translate natural-language intent into mathematical adjustments for scenario simulation
• Design constraint-based feasibility logic respecting infrastructure, regulatory, and production limitations
• Contribute to supply-chain optimization solvers balancing sales demand and supply constraints
• Mentor junior talent and collaborate with senior data science team members

Requirements

• Master’s in data science, Computer Science, Econometrics, or Statistics
• 5+ years of professional experience developing machine learning models and predictive systems
• Strong proficiency in Python, including scikit-learn and TensorFlow/PyTorch
• Experience with ensemble methods such as XGBoost and Random Forest
• Hands‑on experience with LLMs and RAG architectures
• Experience with demand forecasting, price elasticity modelling, or time-series analysis
• Ability to explain complex logic to business stakeholders and turn it into transparent insights
• Automotive sector experience is a plus

Core Competencies

Expertise in developing machine learning models and predictive systems, with a strong focus on demand forecasting and price elasticity modeling. Proficient in Python and familiar with advanced econometrics, AI-driven decision logic, and supply chain optimization.

Highest-signal resume keywords

• Machine Learning Model Development
• Demand Forecasting
• Python Proficiency
• LLM Experience
• Econometrics Expertise

ATS Optimization Keywords

Hard Skills

• Machine Learning
• Predictive Systems
• Demand Forecasting
• Price Elasticity Modeling
• Time-series Analysis
• Econometrics
• Algorithm Development
• Data Querying
• Simulation Engines
• Ensemble Methods

Soft Skills

• Mentoring
• Collaboration
• Communication

Certifications & Qualifications

• Master’s in Data Science
• Master’s in Computer Science
• Master’s in Econometrics
• Master’s in Statistics

Industry Keywords

• Automotive Sector
• Supply Chain Optimization
• Data Lineage
• Regulatory Compliance

Tools & Technologies

• Python
• Scikit‑learn
• TensorFlow
• PyTorch
• XGBoost
• Random Forest
• LLMs
• RAG Architectures