Job Title:  Assistant Manager | ICC | Mumbai | Data Analytics ICC

Assistant Manager | SRT- M&A Strategy ICC | Data Analytics ICC

·      Location:  Mumbai

The team

Data Technology and Analytics uses innovative tools to analyze vast amounts of data in order to proactively or reactively identify opportunities for revenue enhancement, cost optimization, risk mitigation and strategic advice for our clients. The group specializes in electronic data sourcing, optimization, analysis, interpretation, prediction and modelling.

We work as an extension of our Deloitte member firms’ analytics practices and provide dedicated support throughout the project lifecycle. Working on international assignments involving cross-border and cross-service line teams allows you to build your networks across the vast Global Deloitte network.

We also have an active international secondment program for our staff after they gain relevant experience, we believe this plays a crucial role in the overall career and personal development of our staff. Learn more about Strategy & Transactions

Your work profile

As an Assistant Manager (AI Scientist / Data Engineer) in the Data Technology & Analytics team, you will support the delivery of machine learning and AI‑driven analytics solutions across global engagements. Your primary focus will be on Customer Lifetime Value (CLTV) modelling, predictive analytics, and end‑to‑end design, development and deployment of ML/AI components within larger data and analytics programs.

You will play a critical role in shaping solution approaches and mentoring junior team members, if required. You will need to take ownership of model development, data engineering workflows, and quality assurance. The role requires strong hands‑on technical skills, a solid understanding of ML/AI techniques, and the ability to operationalize analytical solutions at scale.

In this role, you will:

·      Proactively engage with member firm / stakeholders to frame problems, propose solution architectures, and define delivery roadmaps.

·      Support the build of CLTV, propensity, cross‑sell, cross‑shop, and Next Best Action models as part of multi‑model program delivery.

·      Lead the design, development, and deployment of GenAI solutions across diverse business domains.

·      Support with the implementation of LLM‑based systems including RAG pipelines, agentic workflows, orchestration frameworks, and domain‑specific AI accelerators.

·      Ensure AI solutions are robust, explainable, scalable, and aligned with governance and ethical frameworks.

·      Perform data preparation, feature engineering, exploratory analysis, and variable selection.

·      Contribute to designing end‑to‑end model pipelines - including training, evaluation, and deployment.

·      Conduct testing, validation, A/B evaluation, and performance tracking for ML models.

·      Ensure models meet defined acceptance criteria, business objectives, and "definition of done".

·      Help design and implement production‑ready ML workflows, orchestration, and data pipelines.

·      Support deployment of final model versions into production environments.

·      Work with cross‑functional stakeholders to ensure robust, scalable, and maintainable ML solutions.

·      Work with business and technical teams to clarify model objectives and refine requirements.

·      Document model logic, assumptions, and validation results in a clear, structured manner.

·      Communicate complex technical concepts in a clear, structured manner to senior stakeholders and cross‑functional teams.

Key skills required: 

In order to be considered for the role, your competencies will cover the broad scope of business modelling services, leveraging your professional background and skills such as:

• Bachelors/ Master’s degree from a reputed institute in Computer Science, Data Science, Information Systems (STEM), Statistics or similar quantitative discipline.
• 3 to 6 years of overall professional IT experience
• 2 to 4 years of experience in ML/AI, data science, or data engineering roles
• Hands‑on experience delivering CLTV models or customer analytics solutions.
• Experience contributing to end‑to‑end ML lifecycle.
• Must have:
• Strong coding proficiency in Python and ML frameworks (scikit‑learn, XGBoost, TensorFlow/PyTorch).
• Good hands‑on experience with GenAI models, LLMs, and Agentic AI frameworks (OpenAI, Azure OpenAI, Google Gemini, Claude, etc.).
• Expertise in building and deploying LLM‑powered systems including RAG architectures, vector databases, embedding models, prompt engineering, and document intelligence.
• Hands‑on experience building ML pipelines, model training, evaluation, and tuning.
• Expertise in at least one cloud platform (Azure/AWS/GCP).
• Strong SQL and data engineering fundamentals.
• Experience with predictive modelling techniques including:
• survival and retention modelling
• buying propensity
• cross‑sell and segmentation
• CLTV and customer scoring
• Ability to translate business problem statements into analytical or ML approaches.
• Good to have:
• Experience with OpenAI based frameworks
• Experience with building chatbots
• Good understanding of the ETL framework and ability to build efficient ETL dataflows using ADF, MS SSIS, or Python
• Dataiku / DataRobot / AWS Sagemaker
• Experience with MLOps tools (MLflow, Dataiku, Databricks, Airflow).
• Experience with BI tools (Power BI, Tableau).
• Familiarity with git and DevOps pipelines.
• This role will also leverage additional skills such as:
• Ability to create advanced analytical models that are fit for purpose and scalable, to identify insightful trends and patterns from the data
• Ability to simplify complex AI concepts for business audiences and influence senior stakeholders.
• Demonstrated ability to mentor and develop talent across GenAI, ML, and data science capabilities.
• Strong stakeholder management capability with experience engaging cross‑functional and international teams.
• Experience in structuring, presenting, and communicating your work results
• Proficiency in English and overall communication
• Ability to present complex business and technology problems and solutions in a simple form to address the level of audience from C-level, executive sponsors, and business owners to engineering and operational teams
• Provide guidance on best practices, project execution, and professional development.
• Flexibility in terms of working hours and working on multiple tools and technologies
• This profile does not involve extensive travel for work.
• Hybrid is our default way of working. Each domain has customized the hybrid approach to their unique needs.