Godrej Enterprises Group

Godrej Enterprises Group (comprising Godrej & Boyce and its subsidiaries) has a significant presence across diverse consumer and industrial businesses spanning Aerospace, Aviation, Defence, Engines and Motors, Energy, Locks & Security Solutions, Building Materials, Green Building Consulting, Construction and EPC Services, Heavy Engineering, Intralogistics, Tooling, Healthcare Equipment, Consumer Durables, Furniture, Interior Design, Architectural Fittings, IT solutions and Vending Machines

Digital:

Corporate Digital team oversees G&B's Digital strategy, designing & architecting critical Digital services & systems (both customer-facing and internal) and nurturing the organization's Digital culture. The team also enables and supports the Technology teams in various BUs and Functions.

KRA:

• Contribution to data ai, gen ai platform & product aspects in terms of ability to perform data science analysis and build AI systems
• Research , Select/Develop, deliver and deploy models for ML/AI use cases
• Contribute towards defining required AI frameworks to ensure Quality & compliance of AI models and systems
• Support departmental & organizational Initiatives related to analytics and AI

Description:

Senior Data Scientist will be required to build hypothesis, research, prototype, design, develop, and help implement enterprise level ML/ AI/Gen AI models for projects to transform and improve company’s business results and competitive position & ensure alignment to the overall digital, data & AI strategy and current and future business objectives.

Contribution to Data & AI Platform and Products

• Work within Digital Data AI Team in development of data science & AI capabilities and features to support delivery on defined objectives around platform aspects
• Design, implement, and evolve robust, secure and quality solutions that operate for the business ecosystem.

Research, design & development of High Quality Data, AI and analytical systems

• Define exploratory data analysis (EDA) keeping in line with problem necessities
• Ensure the development of quality procedures and standards products and supervising tests.
• Work on various data correction problems such as data cleansing, sourcing and integrating from multiple platforms to make the good data available for data analysis , data science & AI development

Provide and help deliver the Solutions

• Hands on contribution to provide solutions and POCs , working in cross- functional or agile teams to develop and deliver significant aspects of the models and systems.
• Lead and mentor junior data scientists and ensure availability of necessary data and analysis as needed by business requirement and use cases.
• Conduct diagnostic across existing data and make future state recommendations in regular intervals.
• Collaborate with Business Analyst, Data scientists, Data Engineers and Data Analysts to ensure understanding and alignment between business needs and technical implementation.
• Monitor performance of existing solutions across use cases to identify and drive optimization.
• Oversee and Research, develop and analyse NLP, Gen AI , computer vision algorithms in Various use cases. Ensure model robustness, model generalization, accuracy, testability, and efficiency. Write product or system development code.
• Contributing via understanding of machine learning techniques and algorithms, including clustering, anomaly detection, optimization, neural network etc
• Responsible for deploying AI/ML models (ML Ops) in standalone and cloud based systems and services.

Support Projects and Initiatives

• Help in Collaboration with business unit heads and corporate functions to identify and assist in providing data analysis support across different projects
• Identify data from legacy systems, to build new solutions based on requirement
• Provide necessary technical support in new and ongoing digital initiatives to ensure seamless data solutioning.

Essential Qualification/Experience:

• B.E Computer/IT - with min 10 Years of Experience with of experience in data analytics & data science, building, and maintaining various ML models. Good know how of emerging small and larger models
• 3 to 5 + years of experience in each of the Data Science specialization like NLP, Demand Forecasting, ML Ops
• Should be able to present portfolio of data science work or use cases

Preferred:

• PhD or minimum M Tech in Computer Science/ IT/ Data Science/ with persuasion of PhD
• Good Data Science or Data Engineer Certification ( minimum 1 year programs etc)
• Sound understanding of Data analysis to support the preparatory work
• Experience working in the agile Environment.
• Know how/ Familiarity in all aspects of MLOps (source control, continuous integration, deployments, etc.)
• Experience/ Exposure with Cloud data services like AWS or Azure

Special Skills Required:

Functional:

• Excellent understanding of machine learning techniques and algorithms, including clustering, anomaly detection, optimization, neural network etc.
• Strong hands-on coding skills in Python, processing large-scale data set and developing machine learning models. Experience programming in Python, R, and SQL
• Expertise in developing ML models and deployment of the same
• Hands on working on developing NLP models using transformers and computer vision.
• Know-how of deploying AI/ML models (ML Ops) in standalone and cloud-based systems and services.
• Comfortable working with DevOps: Jenkins, Bitbucket, CI/CD
• SQL Server experience required
• Understanding of, dimensional data modelling, structured query language (SQL) skills, data warehouse and reporting techniques
• Data Governance & Ethics

Leadership:

• Strong analytical skills, ability to ask right questions, analyse data and draw conclusion by making appropriate assumptions, to solve and model complex business requirements
• Ability to lead team of junior data scientists, get into the details of the problem and ability to code the solution hands on as and when needed
• Planning & Organizing
• Present complex data analysis in consumable way and Engage the stakeholders
• Ability to collaborate with different teams and clearly communicate solutions to both technical and non-technical team members