Data Scientist

Job Overview :

We are looking for an experienced Data Scientist to drive data-driven decision-making, predictive analytics, and AI-led business solutions.

The ideal candidate will have a strong understanding of statistical modelling, machine learning, advanced analytics, and Generative AI, along with the ability to translate complex data into meaningful business insights.

The role involves working closely with business leaders, analytics teams, and technology stakeholders to identify business opportunities, develop predictive models, evaluate emerging AI applications, and support strategic business decisions.

Key Responsibilities :

- Lead data analysis and modelling initiatives to identify business trends, patterns, opportunities, and performance gaps.

- Apply statistical analysis, predictive modelling, and machine learning techniques to address complex business challenges.

- Develop analytical models and forecasting approaches to support business planning and strategic decision-making.

- Work with structured and unstructured datasets to generate actionable insights and business recommendations.

- Identify opportunities to leverage AI, Machine Learning, and Generative AI across business functions.

- Develop and evaluate LLM-based applications and AI solutions for enterprise business use cases.

- Explore applications of Natural Language Processing (NLP), Retrieval-Augmented Generation (RAG), and Agentic AI to improve business processes.

- Collaborate with business stakeholders to understand requirements, define analytical objectives, and recommend data-driven solutions.

- Evaluate model performance, accuracy, reliability, and business effectiveness, recommending improvements wherever required.

- Work with data engineering and technology teams to ensure data availability, quality, and consistency for analytical initiatives.

- Establish appropriate approaches for model evaluation, monitoring, explainability, and governance.

- Prepare analytical reports, dashboards, presentations, and management-level insights.

- Present complex analytical findings in a clear and structured manner to senior leadership and non-technical stakeholders.

- Identify opportunities for process automation, productivity improvement, and business optimization through advanced analytics.

- Support responsible AI adoption by ensuring data privacy, transparency, fairness, and compliance with organizational policies.

- Evaluate emerging data science and AI technologies and recommend their adoption based on business value.

Required Skills and Qualifications :

- Experience in Data Science, Machine Learning, Artificial Intelligence, or Advanced Analytics.

- Strong understanding of statistical modelling, predictive analytics, forecasting, and data science methodologies.

- Proficiency in Python for data analysis, modelling, and analytical applications.

- Experience with machine learning frameworks such as Scikit-learn, TensorFlow, or PyTorch.

- Understanding of Generative AI, Large Language Models (LLMs), and Natural Language Processing.

- Familiarity with RAG architectures, prompt engineering, embeddings, and vector databases.

- Understanding of Agentic AI, AI agents, and intelligent workflow automation.

- Experience in data exploration, feature engineering, model validation, and performance evaluation.

- Exposure to cloud platforms such as Microsoft Azure or AWS.

- Knowledge of Databricks, Apache Spark, and large-scale data processing.

- Understanding of MLOps, LLMOps, model monitoring, and model governance.

- Knowledge of Responsible AI, model explainability, and data security practices.

- Strong business acumen and the ability to connect analytical findings with business objectives.

- Excellent communication, stakeholder management, analytical, and problem-solving skills.

Good to Have :

- Experience working on enterprise-level data science and AI transformation initiatives.

- Exposure to business intelligence and visualization tools such as Power BI or Tableau.

- Experience in predictive forecasting, customer analytics, operational analytics, or business performance modelling.

- Familiarity with enterprise AI adoption, automation, and digital transformation initiatives.

- Experience collaborating with global business teams and working in a Global Capability Center (GCC).

Skills

Data Science, Machine Learning, Artificial Intelligence, Python, Generative AI, NLP, Tensorflow, PyTorch, Apache Spark, Agentic AI