Deputy Manager

Your work profile

Data Analytics

You will be part of a team that delivers complex analytics solutions designed to help SRT globally achieve clear differentiation and sustainable competitive advantage through improved decision-making.

Were looking for ambitious analytics professionals like you—people who are passionate about data, driven by insights, and eager to think differently about challenges and solutions.

In this role, you will have the opportunity to collaborate across teams within SRT and the wider firm. You’ll design and deliver data science solutions that integrate people, processes, data, and technology to drive strategic outcomes.

You will:

• Lead the definition, design, and development of data science solutions
• Support member firms and/or clients throughout the model development lifecycle
• Design, develop, and test models, considering various scenarios and sensitivities to enhance client decision-making
• Apply strong business diagnostic skills and a logical, analytical approach to problem-solving
• Work independently or as part of a team to deliver high-impact insights and solutions

Desired Qualifications

• Bachelors/ Master’s degree from a reputed institute in Computer Science, Information Systems (STEM) or similar quantitative discipline.
• 5+ years of overall professional IT experience
• Qualification in Data Science a plus, but must illustrate in-depth hands-on knowledge

Technical Skills

To be considered for the role, your competencies will cover the broad scope of analytics services, leveraging your professional background and skills such as:

Must have:

• Strong proficiency in hands-on AI work with either Python / R / SAS / SPSS
• Expertise in machine learning frameworks and tools, with a focus on practical implementation.
• Active contribution to the development and implementation of Machine Learning and Deep Learning models and techniques
• Extensive hands-on experience with Natural Language Processing (NLP) and Deep Learning modelling/Neural Network techniques
• Data Pre-processing / Data Mining & Management / Predictive Analytics / Machine Learning / Optimization / Business Rules Engines / Risk Scoring & Identification
• VS Code/MSFabric/Databricks / SQL / Azure Data Factory / Azure AI Studio
• Require hands-on experience with Generative AI models or LLMs and Prompt Engineering. This extends but not limited to Retrieval Augment Generation (RAG), Summarisation, Data Analysis, AI Agents etc.

Good to have:

• Experience with OpenAI based frameworks
• Experience with source control (git) and Azure DevOps
• 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
• Tableau / Power BI
• Experience with MLFlow and other MLOps pipeline
• Knowledge of existing and upcoming platforms and vendors in the market with and leveraging them creatively into wider business solutions

Soft & Preferred skills

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

Understanding existing and upcoming AI frameworks and realising them to appropriate assets/solutions

• Experiencein structuring, presenting, and communicating your work results

Proficiency in English and overall communication

• Strong appetite for innovation and emerging technologies

Provide guidance on best practices, project execution, and professional development.

• Demonstrate ability to think strategically about business, create technical solutions with end users in mind, motivate and mobilize resources, as well as deliver results
• Flexibility in terms of working hours and working on multiple tools and technologies
• Familiarity with Microsoft Azure services (e.g., Azure App Services, Azure Functions, Azure DevOps)

Location and way of working

• Base location:

  Mumbai

• This profile does not involve extensive travel for work.
• Hybrid is our default way of working. Each domain has customised the hybrid approach to

their unique needs.