URGENT HIRING / Senior Data Scientist (Finance Domain) / 10+ years experience / Immediate – 30 Days

About the Job:

About Senzcraft:

Founded by IIM Bangalore and IEST Shibpur Alumni, Senzcraft is a hyper-automation company. Senzcraft vision is to Radically Simplify Today's Work. And Design Business Process For The Future. Using intelligent process automation technologies.

We have a suite of SaaS products and services, partnering with automation product companies.

Please visit our website - for more details

Our AI Operations SaaS platform

Senzcraft on linkedin ->

Senzcraft is awarded by Analytics India Magazine in its report State of AI in India as a Niche AI startup. Senzcraft is also recognized by NY based SSON as a top hyper-automation solutions provider.

About the Role (Senior Data Scientist - Finance Domain) :

We are seeking a Senior Data Scientist to drive advanced AI initiatives across our APAC platform. You will work with a fully decentralized international team of Solution Architects, Data Engineers, Product Managers, business stakeholders, and FinTech partners .

In this role, you will bring cutting-edge Deep Learning and Generative AI concepts to solve complex problems in financial analysis, particularly using AI multi-agent architectures and data extracted from company annual reports . You will act as the AI subject-matter expert for India and the wider APAC region , shaping and scaling the AI practice across the platform.

Key Responsibilities

• Design and build AI-driven tools for:
• Dynamic data retrieval and scraping
• Structuring financial data from balance sheets, cash flow statements, and income statements
• Propose, architect, and implement GenAI multi-agent systems using agentic frameworks to perform:
• Financial data extraction and normalization
• Ratio analysis
• Trend analysis over time
• Benchmarking against industry peers
• Apply Machine Learning, Deep Learning, NLP, and statistical modeling to complex prediction and financial analysis use cases
• Work on state-of-the-art Deep Learning architectures , including:
• Fine-tuning transformer models
• Training neural networks from scratch
• Evaluate model performance using appropriate metrics and improve results through iterative experimentation
• Develop, debug, and optimize ML/DL pipelines for data preprocessing, training, testing, deployment, and error analysis
• Write clean, scalable, production-ready code to automate model retraining and deployment
• Perform in-depth analysis using interactive visualizations, data mining, and statistical techniques
• Research and introduce high-performance ML/DL innovations tailored to finance-related problems