Applied Data Scientist

Walmart Global Tech India; Bengaluru; Presencial; INR 2 500 000 - 4 000 000; Tempo integral

Resumo da oferta

Walmart Global Tech India in Bengaluru is seeking an experienced ML/AI data scientist to analyze commerce data and build scalable models for advertising, pricing and product listings.

You will lead research initiatives from problem framing to production deployment, identify learning opportunities, and collaborate with engineering, analytics and product teams to deliver measurable impact.

Ideal candidates have strong Python, SQL and statistics, with a plus for experience with LLMs.

Qualificações

• 4+ years in applied ML/AI and data science.
• Deep proficiency in Python, SQL, statistics, and data analysis.
• Hands-on experience deploying end-to-end lifecycle of machine learning models.
• Experience with LLMs, fine-tuning, AI agents, optimization, or sequential decision systems.
• Exposure to e-commerce, marketplaces, advertising, or pricing data is valuable but not essential.
• Strong problem-solving and communication skills; ML research experience is a plus.

Responsabilidades

• Analyze commerce data to derive insights and identify gaps and opportunities.
• Develop scalable ML models and optimization strategies for advertising, pricing, and listings.
• Define and lead science initiatives from problem framing through production deployment in a high-ambiguity environment.
• Identify and build sequential feedback loops that improve decisions over time.
• Design evaluation frameworks to measure quality and business impact at scale.
• Collaborate with engineering, analytics, and product teams to deploy models to production.

Conhecimentos

ML/AI experience

Python

SQL

Statistics

Data analysis

End-to-end ML lifecycle

LLMs / AI agents

Formação académica

Master's or PhD in quantitative field

Descrição da oferta de emprego

Responsibilities:

• Conduct deep analysis of commerce data to derive insights and identify gaps and new opportunities.
• Develop scalable and effective machine-learning models and optimization strategies to solve business problems across advertising, pricing, and listings.
• Define and lead science initiatives from problem framing through production deployment in a high-ambiguity environment.
• Identify and build the sequential feedback loops that make decisions improve over time.
• Design evaluation frameworks to measure the quality and business impact at scale.
• Work closely with engineering, analytics, and product teams to take models from experimentation into production.

Requirements:

• 4+ years in applied ML/AI and data science. A master's or PhD in a quantitative field is a plus.
• Deep proficiency in Python, SQL, statistics, and data analysis.
• Hands-on experience developing, deploying, and maintaining the end-to-end lifecycle of machine learning models.
• Experience with LLMs, fine-tuning, AI agents, optimization, or sequential decision systems is a strong plus.
• Exposure to e-commerce, marketplaces, advertising, or pricing data is valuable but not essential.
• Strong problem-solving and communication skills; ML research experience is a plus.