Python Data Scientist Lead - Artificial Intelligence/Machine Learning (6-12 yrs)

Client Technology, established in 2017, transforms businesses through its software platform leveraging blockchain technology. Client, an ISO-certified company, has a strong and growing global presence, with clients and partners across countries. MiFiX is currently serving 170,000+ customers at INR 800+ crore of AUM. MiFiX is available for microfinance, loans against remittances, agri loans with, co-lending & securitization, trade finance, bank-in-a-box, and many others in the pipeline.

Industry Recognition

Winner of "Economic Times future-ready organizations award 2023-24".

Winner of the "Innovation in Blockchain" award at the 13th Aegis Graham Bell Awards (supported by the Ministry of Electronics & IT and NITI Aayog).

Winner of the "Deloitte Technology Fast 50 Award 2022 India"

Role : Python Data Scientist

Total experience :

- Pref in DS, Analytics, Software or related area

- Should be in Data Scientist role for 3 or more years Degree

- Pref. Masters / PhD. Or related specialization/certificate in DS / Computer Science - but good B.S. Candidates are okay too

- Candidate will have direct exposure to customers / partners / executives in SAI/CAI.

- Should be independent to work with minimal directions. Self-starter and self-motivated

Skills :

- Programming language - Object Oriented programming in Python (must). Java, R, C/C++ is additional.

- Data science skills

- OCR, Image processing and NLP, BERT and BERT like transformer models, Large Language models and recent development in LLM and Generative AI.

- Experience In Building Chat And Conversational Agents Are Required. Deep learning on language model are plus.

- Foundational knowledge of Statistics, Classical Machine Learning, Supervised and unsupervised algorithms are desired.

- Ability to define problem statement and plan of execution of data science projects Should have strong communication and presentation skills.

- Ability to translate analytic ideas into code using production-quality Python code