Data Analytics Scientist

The Data Analytics Scientist will apply statistical methods, machine learning and AI tools to uncover insights that support business performance, risk management and internal audit. The role sits at the intersection of data science, risk and control, helping the organisation detect anomalies, measure control effectiveness and translate complex data into actionable recommendations. This is a hybrid role based in Mumbai, offering exposure to global stakeholders and multi-jurisdictional compliance requirements.

Our client is a leading global financial services organisation operating in the banking sector across multiple international markets. With a large, diverse workforce and a strong focus on governance, risk and innovation, they are investing heavily in advanced analytics to strengthen decision-making. The culture emphasises collaboration, continuous learning and responsible use of data.

Responsibilities

• Build and maintain data pipelines and analytical models using Python (Pandas, NumPy, Scikit-learn) or R, and SQL.
• Develop anomaly detection solutions using unsupervised machine learning to identify irregular patterns and potential risks.
• Apply descriptive and inferential statistics, hypothesis testing, regression and classification techniques to business problems.
• Design and deliver dashboards and reports using Tableau, Power BI or equivalent visualisation tools.
• Explore and apply AI tools and Large Language Models to improve analytical workflows and insight generation.
• Support enterprise risk management and internal audit processes by analysing control data and financial and performance metrics.
• Conduct survey design and psychometric analysis where required to inform organisational insights.
• Collaborate with risk, audit, technology and business teams to integrate data sources and communicate findings to stakeholders.

Requirements

• 2-5 years of experience in data analytics, data science or a related analytical role.
• Strong proficiency in Python (Pandas, NumPy, Scikit-learn) or R, and SQL.
• Hands-on experience with data visualisation tools such as Tableau, Power BI or equivalent.
• Solid grounding in statistics, hypothesis testing, regression and classification, and unsupervised machine learning.
• Familiarity with enterprise risk management, internal control frameworks and audit processes.
• Exposure to cloud analytics environments (AWS, Azure or GCP) and data warehousing concepts.
• Basic understanding of financial metrics and business performance indicators.
• Master's degree in Data Science, Statistics, Business Analytics or a related field; risk certifications (CRMA, CCSA or compliance-related) are an advantage.

Skills

Python (Pandas, NumPy, Scikit-learn) or R, SQL, Data visualisation (Tableau, Power BI, or equivalent), AI tools and Large Language Models (LLMs), Anomaly detection using unsupervised machine learning, Descriptive and inferential statistics, hypothesis testing, regression and classification, Survey methodology and psychometric analysis, Enterprise risk management and internal control frameworks, Audit processes, Risk certifications (CRMA, CCSA, or compliance-related), Data integration and warehousing concepts, Cloud analytics environments (AWS, Azure, GCP), Experience in global organisations with multi-jurisdictional compliance, Basic understanding of financial metrics and business performance indicators, Master's degree in Data Science, Statistics, Business Analytics, or related field