Position
Specialist - Data Science
Company
Asian Paints Limited
Location
Mumbai Metropolitan Region, Maharashtra, India
Job Type
Full-time
Job Mode
On-site
Job Requisition ID
15479
Years of Experience
0 - 3 Years
Company Description
Historical Legacy and Leadership: Asian Paints has been a pioneer in the paint and decor industry since its inception in 1942, transforming empty spaces into beautiful homes and holding the position of India’s largest paint company for nearly five decades.
Global Footprint: Ranked among the top 10 decorative paint manufacturers globally, the organization maintains active business operations across 14 countries and operates 27 state-of-the-art manufacturing facilities worldwide.
International Subsidiaries: The company's global presence is strengthened by renowned international subsidiaries including Berger International, Scib Paints, Taubman, Apco Coatings, and Ess Ess.
Strategic Joint Ventures: Asian Paints collaborates through high-impact joint ventures with PPG Industries for automotive and industrial coatings, as well as Sleek International for modern modular kitchen solutions.
Comprehensive Product Portfolio: Offers an extensive spectrum of surface coating products ranging from high-end luxury enamels to cost-effective economy distempers, engineered to satisfy diverse aesthetic and protective requirements.
Expansion Beyond Paints: The business has successfully expanded its footprint into home decor verticals, encompassing the Nilaya luxury wallpaper range, designer wall stencils, premium wood finishes, construction chemicals, and advanced waterproofing solutions.
End-to-End Home Decor Services: Provides comprehensive, hassle-free painting and decor execution services, offering direct-to-consumer color consultancy at home, online design assistance, and experiential Colour Idea Stores across major metropolitan centers.
Commitment to Innovation: Consistently drives technological and operational innovation to elevate customer experience, streamline manufacturing processes, and pioneer eco-friendly product formulations.
Sustainability and Community Impact: Dedicated to reducing environmental impact through sustainable operational practices and carrying out extensive community outreach initiatives that uplift society.
Corporate Values and Culture: Built on a foundation of passion, integrity, and relentless innovation, fostering a collaborative work environment that encourages employees to achieve excellence and set industry benchmarks.
Profile Overview
Business Problem Translation: Actively engage with cross-functional business stakeholders to comprehend operational challenges and translate complex corporate requirements into scalable Data Science, Machine Learning, and Generative AI frameworks.
Hands-On Solution Development: Execute end-to-end development of advanced predictive models, statistical algorithms, and artificial intelligence applications to optimize key business functions across manufacturing, supply chain, retail, and marketing.
Predictive Modeling Mastery: Design, implement, train, and validate robust classification, regression, clustering, recommendation engines, and time-series forecasting models tailored to real-world decor and industrial data streams.
Generative AI Applications: Architect, build, and evaluate modern Large Language Model (LLM) applications by leveraging sophisticated prompt engineering techniques, Retrieval-Augmented Generation (RAG) architectures, semantic embeddings, and vector search engines.
Agentic Framework Implementation: Design and execute complex multi-agent AI systems utilizing contemporary agentic frameworks to automate decision-making processes, autonomous workflow execution, and interactive business intelligence systems.
Model Context Protocol (MCP) Integration: Develop, configure, deploy, and maintain custom Model Context Protocol (MCP) servers and MCP-driven tools to facilitate seamless interoperability between foundation models, local tools, and enterprise databases.
Azure AI Cloud Infrastructure: Utilize Azure’s cloud ecosystem—including Azure OpenAI, Azure ML, and related data services—to design, train, deploy, and scale production-ready AI tools within a highly secure enterprise environment.
Feature Engineering and Data Preparation: Lead and mentor technical teams in designing feature stores, cleansing structured and unstructured enterprise datasets, engineering informative variables, and establishing rigorous validation methodologies.
Cross-Functional Collaboration: Partner closely with data engineers, cloud architects, cybersecurity specialists, software developers, and business units throughout the enterprise software development lifecycle, from initial requirement gathering through UAT to final production release.
Production Model Governance and Monitoring: Continuously monitor deployed machine learning models and Generative AI pipelines for predictive accuracy, system reliability, inference latency, drift detection, and cloud resource cost optimization.
Technical Documentation and Standardization: Maintain clear, organized technical documentation, promote reusability of codebase modules, establish software engineering standards, and institutionalize best practices across the data science organization.
Supply Chain Optimization: Apply statistical modeling to forecast raw material demand, optimize inventory management across warehouses, and reduce delivery turnaround times across retail distribution networks.
Personalized Customer Experience: Build recommendation algorithms and personalization tools that suggest complementary color palettes, decor products, and service offerings to consumers based on preference mapping.
Quality Assurance Automation: Leverage computer vision and advanced analytics to detect defects in paint manufacturing, packaging, and surface application, ensuring consistent product quality across production lines.
Qualifications
Educational Background: Bachelor’s degree, Master’s degree, or Ph.D. in Computer Science, Data Science, Statistics, Mathematics, Information Technology, or a closely related quantitative field.
Core Programming Competency: Strong proficiency in Python, SQL, and data science libraries (such as Pandas, NumPy, Scikit-Learn, SciPy, and Statsmodels) for data manipulation, algorithmic development, and analysis.
Machine Learning Fundamentals: Solid practical knowledge of supervised and unsupervised learning techniques, including Linear/Logistic Regression, Decision Trees, Random Forests, Gradient Boosting Machines (XGBoost, LightGBM), SVMs, and K-Means Clustering.
Deep Learning Frameworks: Familiarity with deep learning architectures and libraries such as TensorFlow, PyTorch, or Keras, with an understanding of Neural Networks, CNNs, and Transformer models.
Generative AI Expertise: Hands-on experience or academic project work involving Large Language Models (LLMs), prompt design, fine-tuning methodologies, RAG pipelines, and vector database management (e.g., FAISS, Pinecone, Qdrant, ChromaDB).
Agentic Framework Knowledge: Exposure to or practical understanding of autonomous AI agent development using frameworks such as LangChain, LlamaIndex, AutoGen, CrewAI, or Semantic Kernel.
Model Context Protocol (MCP) Awareness: Familiarity with the concepts of Model Context Protocol (MCP), server setup, tool integrations, and context-sharing standards across AI applications.
Cloud Platform Familiarity: Practical knowledge or certification in cloud-based data science platforms, specifically Azure AI services, Azure Machine Learning Studio, Azure Cognitive Search, and Databricks.
Data Engineering and Database Proficiency: Proficiency in writing complex SQL queries, working with relational databases (PostgreSQL, MySQL), non-relational storage systems (MongoDB), and understanding ETL/ELT pipeline principles.
Software Engineering Best Practices: Working knowledge of code versioning tools (Git/GitHub), containerization (Docker), API development (FastAPI, Flask), and basic CI/CD automated deployment workflows.
Analytical and Quantitative Thinking: Exceptional problem-solving abilities, structured analytical thinking, and the capacity to decompose abstract business problems into actionable quantitative tasks.
Communication and Presentation Skills: Excellent verbal and written communication skills to articulate complex technical methodologies and data insights clearly to non-technical business leaders.
Team Collaboration: Demonstrated ability to work effectively in a team-oriented environment, contributing to collective project goals while demonstrating ownership of assigned deliverables.
Additional Info
Dynamic Work Environment: Join a high-performing digital transformation unit within a market-leading enterprise that blends traditional manufacturing excellence with modern software engineering practices.
Career Growth Pathways: Access clearly defined technical and managerial career progression tracks designed to accelerate professional growth through continuous skill enhancement and merit-based advancement.
Comprehensive Learning Ecosystem: Benefit from continuous upskilling initiatives, enterprise cloud certifications, access to research journals, attendance at global AI conferences, and internal innovation hackathons.
Mentorship and Leadership Exposure: Work under the guidance of seasoned data scientists, engineering leaders, and enterprise architects, acquiring practical insight into large-scale enterprise deployments.
High-Impact Projects: Direct involvement in scalable, business-critical projects that impact millions of homeowners, thousands of retail distributors, and multi-country operational hubs.
Innovative Culture: Flourish in an open corporate culture that encourages experimentation, promotes technological curiosity, rewards creative problem-solving, and values diverse technical perspectives.
State-of-the-Art Workspace: Work from the Mumbai Metropolitan Region headquarters, equipped with modern technology infrastructure, high-performance computing clusters, and collaborative workspaces.
Work-Life Integration: Enjoy competitive employee wellness benefits, structured paid leaves, health insurance coverage, and team-building initiatives designed to support overall personal well-being.
Equal Opportunity Employer: Asian Paints is committed to building a diverse, inclusive, and accessible workplace where all employees are treated with dignity, respect, and fairness regardless of background.
Structured Onboarding Program: Transition smoothly into the corporate environment via a thorough orientation process, dedicated peer buddy systems, immersive business domain training, and hands-on codebase orientation.
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