Role : Consultant - Data Scientist | 4 - 7 Years | Bangalore

Hiring a hands-on Data Scientist with strong experience in Machine Learning, Python, GenAI, Feature Engineering, and production-grade model development. This is an excellent opportunity for professionals who enjoy working with raw, unstructured, behavioural, and financial data and building advanced AI/ML solutions from experimentation through production.

Location : Bangalore

Experience : 4 - 7 Years

Your Future Employer :

A leading global AI and Analytics organization offering an opportunity to work on advanced Data Science, Artificial Intelligence, Generative AI, and analytics solutions for global clients.

Responsibilities :

- Build and validate advanced Machine Learning and statistical models using structured, unstructured, behavioural, and transactional data.

- Engineer meaningful features from raw data and evaluate their incremental predictive value beyond existing models.

- Apply LLM-based extraction and GenAI techniques to convert unstructured data into structured, machine-readable signals.

- Work with advanced modelling techniques including XGBoost, Random Forest, sequence/trajectory modelling, survival/hazard modelling, and Bayesian methods.

- Take analytical solutions from experimentation to production-grade deliverables, including APIs, libraries, reproducible pipelines, and monitored services.

- Develop and maintain Python codebases using Git/GitHub, version control, and CI/CD workflows.

- Collaborate closely with data, engineering, and client teams to develop scalable and reliable AI/ML solutions.

- Contribute reusable frameworks, methodologies, and learnings to the organization's AI and Data Science Center of Excellence.

Requirements :

- 4 - 7 years of hands-on experience in Data Science, Machine Learning, or AI.

- Strong proficiency in Python, Machine Learning, Statistics, and Feature Engineering.

- Hands-on experience with GenAI, LLM-based solutions, or AI/agentic workflows.

- Strong knowledge of advanced ML techniques such as XGBoost, Random Forest, HDBSCAN, HMMs, sequence modelling, survival analysis, and Bayesian modelling.

- Experience taking models from experimentation to production, rather than working only with notebooks.

- Strong experience with Git/GitHub, CI/CD, and production ML workflows.

- Ability to work with raw, unstructured, behavioural, or transactional datasets.

- Strong analytical, problem-solving, and communication skills.

- Experience in financial services, lending, credit bureau, risk analytics, or transaction data will be an advantage.

- Experience with AI evaluation, observability, model monitoring, drift detection, or hallucination checks will be a plus.

What is in it for you :

- Opportunity to work on advanced AI, GenAI, Machine Learning, and Data Science use cases.

- Exposure to complex financial, behavioural, transactional, and unstructured datasets.

- Opportunity to build and deploy production-grade ML solutions using modern AI/ML practices.

- Opportunity to collaborate with global clients and contribute to reusable AI and Data Science frameworks.