Requirements: Skills

 A Bachelor’s degree in data science, statistics, computer science, or a similar field

 2+ years industry experience working in a data science role, such as statistics, machine learning,

deep learning, quantitative financial analysis, data engineering or natural language processing

 Domain experience in Financial Services (banking, insurance, risk, funds) is preferred

 Have and experience and be involved in producing and rapidly delivering minimum viable products,

results focused with ability to prioritize the most impactful deliverables

 Strong Applied Statistics capabilities. Including excellent understanding of Machine Learning

techniques and algorithms

 Hands on experience preferable in implementing scalable Machine Learning solutions using Python /

Scala / Java on Azure, AWS or Google cloud platform

 Experience with storage frameworks like Hadoop, Spark, Kafka etc

 Experience in building &deploying unsupervised, semi-supervised, and supervised models and be

knowledgeable in various ML algorithms such as regression models, Tree-based algorithms,

ensemble learning techniques, distance-based ML algorithms etc

 Ability to track down complex data quality and data integration issues, evaluate different algorithmic

approaches, and analyse data to solve problems.

 Experience in implementing parallel processing and in-memory frameworks such as H2O.ai Skills:- Data Science, Natural Language Processing (NLP), Machine Learning (ML) and Deep Learning