Job Overview

Philips is hiring a Data Scientist - AI and LLMs - People Analytics for its People Analytics Development Pod in Bangalore. The role focuses on using data science, machine learning, statistics, artificial intelligence and large language models to turn People and business data into trusted insights, predictions and decision-support products.

The Data Scientist will work with business stakeholders, Data Engineers and Full Stack AI Application Engineers to translate complex or ambiguous questions into robust analytical approaches, models and AI-enabled product capabilities. The work is embedded in People Analytics while also supporting use cases across Philips.

Key Responsibilities

• Frame complex business questions as measurable analytical, statistical, machine-learning or AI problems.
• Explore, prepare and analyse data to identify insights, patterns, risks and opportunities.
• Design and develop predictive, descriptive, diagnostic and prescriptive models for People Analytics and broader Philips use cases.
• Apply statistical methods such as hypothesis testing, segmentation, forecasting, regression, classification, causal inference and experimentation where appropriate.
• Create analytical narratives, visualisations and recommendations that help business stakeholders make informed decisions.
• Identify suitable applications for GenAI, retrieval-augmented generation, semantic search, natural-language interfaces and automation.
• Prototype and evaluate LLM-enabled solutions using prompt design, retrieval approaches, grounding, citations, guardrails and human-in-the-loop workflows.
• Design structured evaluations for AI and LLM solutions, considering relevance, factuality, completeness, safety, fairness and user usefulness.
• Select suitable approaches across statistics, machine learning, GenAI, search, automation and rules-based logic.
• Work with Data Engineers to define data requirements, data-quality expectations and reusable analytical datasets.
• Collaborate with Full Stack AI Application Engineers to translate analytical and AI capabilities into scalable applications.
• Use Databricks and related data and AI capabilities to develop, test and operationalise analytical solutions where relevant.
• Apply privacy, security, responsible-AI and compliance requirements when working with sensitive employee or business data.
• Document methodologies, assumptions, model performance, evaluation results and limitations.
• Communicate technical findings, uncertainty, assumptions and trade-offs clearly to technical and non-technical stakeholders.

Required Skills

• Strong professional experience in data science, advanced analytics, statistics, machine learning or a comparable quantitative discipline.
• Strong hands-on Python and SQL skills for data analysis, modelling and reproducible analytical workflows.
• Strong knowledge of statistical analysis, model validation and experimental or quasi-experimental methods.
• Experience developing predictive or analytical models and translating their results into business decisions.
• Experience working with structured and unstructured data.
• Familiarity with machine-learning techniques and their appropriate use, limitations and evaluation.
• Practical experience with AI or LLM-enabled solutions, including prompt workflows, semantic search, RAG, text analytics or conversational interfaces.
• Understanding of LLM evaluation, including relevance, factuality, consistency, safety and business usefulness.
• Experience with modern data and AI platforms, preferably Databricks or an equivalent environment.
• Ability to communicate analytical concepts, uncertainty, assumptions and recommendations clearly to non-technical audiences.
• Strong business acumen, curiosity and the ability to turn ambiguous stakeholder questions into rigorous analytical work.
• Understanding of privacy, fairness, explainability and responsible-AI considerations.
• Ability to work independently while collaborating effectively in a global, matrixed environment.

Education

A bachelor's or master's degree in data science, statistics, economics, mathematics, computer science, engineering, behavioural science, quantitative social science or a related field is required.

Preferred Experience

• Experience with Databricks, including notebooks, SQL warehouses, MLflow, feature engineering, model serving or AI capabilities.
• Experience with workforce, talent, HR, commercial, operational or other business analytics.
• Experience with forecasting, workforce planning, optimisation, experimentation or causal inference.
• Experience with Azure OpenAI, Azure AI services or another enterprise GenAI platform.
• Experience with NLP, text analytics, embeddings, vector search or conversational systems.
• Experience designing human evaluation, feedback or adoption-measurement processes for AI products.
• Experience building analyses or models using sensitive or regulated data.
• Experience collaborating with product, engineering, privacy and compliance teams to bring analytical solutions into use.
• Experience working in global, matrixed organisations.

Technologies

• Python – Used for data analysis, modelling and reproducible analytical workflows.
• SQL – Used for analytical data work and modelling workflows.
• Machine Learning – Applied to predictive and analytical modelling and evaluated according to the problem context.
• Databricks – Used for developing, testing and operationalising analytical solutions where relevant.
• Large Language Models (LLMs) – Applied to AI-enabled solutions, evaluation, retrieval and natural-language use cases.
• Generative AI – Considered for practical business applications and automation.
• Retrieval-Augmented Generation (RAG) – Used as a retrieval approach for LLM-enabled solutions.
• Prompt Engineering – Applied through prompt design and prompt workflows.
• Natural Language Processing (NLP) – Relevant to text analytics and conversational systems.

Work Mode & Location

This is a full-time position based in Bangalore, Karnataka, India. The JD does not explicitly state a remote or hybrid work arrangement, so the configured SoftoJobs work mode is onsite.

Team & Collaboration

The position is part of the People Analytics Development Pod within the People Intelligence organisation. The pod develops digital products, AI-enabled applications, automations and analytics experiences.

The Data Scientist will work closely with the People Analytics Lead and People Intelligence Analytics Partners, Data Engineers, Full Stack AI Application Engineers, product owners, business stakeholders, Enterprise IT, cloud, architecture and security teams, as well as privacy, compliance and responsible-AI teams.

How to Apply

Apply now through SoftoJobs to explore this opportunity.