Description :

About the job :

Role : Senior Data Scientist

Exp : 10+ Years

Location : Bangalore

Immediate Joiners

Client is the corporate and investment banking arm of Group BPCE, second largest financial institution in France. Partnering with Business Lines and Support Functions, we dive into each domain and strive to deeply understand the pain-points and thereafter deliver bespoke data solutions with measurable business benefits.

As a Data Scientist, you will work closely with a fully decentralized international team (spread across APAC) of Solution Architects, Data Engineers, Product Managers, but also with business stakeholders and Fintech partners. You will bring in the latest ideas and concepts in deep learning for solving complex problems in different finance domains, specifically AI for financial analysis, using an AI multi-agent approach relying on dedicated tools (qualitative and quantitative) and data from annual report. You will be the subject matter expert on all things AI for India as well whole APAC platform and drive the AI practice in the region.

Main responsibilities and duties of the role :

- Build and incorporate appropriate AI tools for data retrieval (dynamic scraping), and data structuring of balance sheet, cash flow and income statements.

- Using appropriate agentic framework, propose and build a Gen AI multi-agent architecture to handle financial analysis at different steps (extraction, normalization, ratios, comparison overt time, to industry peers, ..)

- Apply AI techniques, including statistical analysis & modeling ML and DL algorithms, on complex prediction and NLP tasks in finance domain to enable data-driven decision making, increase business values and reduce operational costs

- Work on the latest Deep Learning architectures tweaking transformers and finetuning DL models from scratch

- Evaluate the results using appropriate tools and work on an iterative way to improve them.

- Write, debug and refine Ml and DL pipelines for efficient data preprocessing, model training, testing and error analysis. Write clean and production-ready codes to automate model (re-)training and deployment.

- Conduct in-depth analysis of subject-matter datasets through interactive visualization, data mining and statistical analysis

- Research and bring in the latest high-performant ML/DL concepts for finance-related problems C2

- Work on model explainability by experimenting and implementing state-of-the-art techniques

- Work with Data Engineers and Backend & Frontend Developers to integrate ML models into various enterprise products and solutions

- Document the approach and the results to be ready to be published and shared with banking peers

- Work closely with various stakeholders to promote AI awareness and adoption

Technical skill requirements :

- Experience in putting RAG systems, agentic workflows and autonoms agents orchestrations in production

- Knowledge of different agent frameworks (Langgraph, crewAI, AutoGen..)

- Good knowledge of LLMs in training, finetuning, inferencing and building LLM-powered applications

- Must have experience with building and training neural networks from scratch in any of these areas : CV, NLP, RL, Time Series.

- Sound theoretical and practical knowledge in machine learning, deep learning and statistics

- Expert in Deep Learning frameworks (preferably Pytorch) and NLP techniques like Word/Sent/Doc2Vec, BERT, GPT, as well as related frameworks like spaCy, Huggingface Transformers, Gensim etc.

- Expert in Python and data science related tools like Sklearn, Pandas, Matplotlib, Jupyter, etc.

- Strong Experience with structured (SQL) and unstructured (NoSQL) databases.

- Knowledge of basic software development and system

- And most importantly, you must be a passionate data scientist who really cares about applying ML/DL on solving real-world problems and is involved in the end-to-end model life cycle

Job Qualification (education, years of experience and other soft skills) :

- Preferably PhD in Computer science or related areas from a Tier-1 university

- Hands-on industry experience in building, refining, and deploying Deep Learning models in production

- Ability to take ownership and deliver within timelines

- Effective written and verbal communication skills

- Knowledge in finance and previously published research paper would be highly appreciated