bluCognition - Data Science Role

Data Science

Data Scientist - Zip Co.

About bluCognition:

bluCognition is an AI/ML based start-up specializing in risk analytics, data conversion and data enrichment capabilities. Founded in 2017, by some very named senior professionals from the financial services industry, the company is headquartered in the US, with the delivery centre based in Pune. We build all our solutions while leveraging the latest technology stack in AI, ML and NLP combined with decades of experience in risk management at some of the largest financial services firms in the world.

Our clients are some of the biggest and the most progressive names in the financial services industry. We are entering a significant growth phase and are looking for individuals with entrepreneurial mindset who wants us to join in this exciting journey.

The Role is with Zip Co. Our client Zip.Co for whom we are hiring extensively - Zip Co, a major global player in the consumer - buy now pay later segment with HQ in Sydney, Australia. The group has presence in multiple countries including USA, Australia, New Zealand, UK and Canada and is increasingly expanding into newer markets. The company is listed on the Australian Stock Exchange as Zip Co, with a market capitalization of $5Bn. With a customer base of 4.5 million customers and 30,000 merchants, the company generates in excess of $5Bn in annual payments globally.

Position: Data Scientist

About the role:

- As Data Scientist, you will leverage your creative and critical thinking skills to develop best-in-class models that have a meaningful impact on the Zip team. These models will support our credit and fraud risk, customer experience, marketing and beyond.

- Having you aboard will enable us to have more models released to production, quicker iteration, and broader coverage of addressing business problems through scientific methods.

- Core KPIs for this position correspond to extra revenue generated/costs saved from releases.

- The role is also meant to support compliance, documentation, and knowledge sharing in regards to model governance & review.

What you'll do:

- Develop, validate and deploy ML models, optimization solutions, inference techniques to solve complex problems and communicate ideas to internal stakeholders

- Extract and explore data, validate data integrity, perform ad hoc analysis, evaluate new data sources to improve models

- Maintain robust documentation of approach and techniques used; including objectives, assumptions, performance, weaknesses, and limitations

- Be ready to adapt to new tools/libraries/technologies/platforms

- Actively partner with engineers to validate & deploy scalable solutions

- Collaborate to gather insight from partners across the organization

- Further develop expertise in data science and engineering through self-study, project exposure and guidance of senior team members

What you'll bring:

- Degree in a quantitative field (e.g., computer science, data science, engineering, economics, mathematics, etc.). Advanced degree preferred.

- 3+ years of Data Science experience

- 2+ years in financial services

- Deep knowledge of Machine Learning Modeling.

- Experience building and implementing models in production is preferred.

- Proficient with Python

- Proficient with SQL

- Practical experience using Spark is a plus

- Understanding Deep Learning methods is a plus

- Technical understanding of algorithm complexity, probability& statistics

- Self-driven with an aptitude for independent research & problem-solving

- Ability to multi-task in a fast-paced environment is essential

- Experience with Git