Manager - Data Science - Bank

Job Description

In this role, you will be expected to work with our lead data scientist and the team executive as well as our internal analytics, technology, product and policy partners to deploy advanced analytical solutions with the goal of reducing fraud losses, reducing false positive declines at the point-of-sale, improving client experience, and ensuring the Bank minimizes its total cost of fraud.

Responsibilities -

Some tasks that this role may be responsible for include (but are not limited to):

- Model development (Regression, Tree based algorithms and neural network)

- Extensive experience in PySpark and other Big Data methods

- Good experience in Supervised and Unsupervised learning.

- Unsupervised learning methods to augment existing supervised models, or detect portfolio anomalies

- Robotic process automation to reduce the need for manual, repeatable processes

- In addition, the role will be expected to work with the lead data scientist and the team executive and stakeholders to help develop the data strategy for client protection to ensure the organization has the proper data to make the right decisions, with a priority on data availability in real-time, and generating true customer-level views able to make intelligent fraud decisions leveraging the entirety of our interactions with a customer.

Requirements:

Education:

- Advanced degree, preferably in Statistics/Mathematics, Applied Sciences, Engineering from a premier institute

Certification:

- Technical certifications in SQL, Hive, Python, PySpark preferred

Experience:

- 6 - 9 years of relevant experience in field of analytics including 2 + years in data science

- 3+ years of experience in engineering, extensive experience in PySpark and other big data methods, experience owning and optimizing a codebase

Foundational Skills:

- Python, PySpark and Hive

- U.S financial services experience preferable

- Have strong statistical knowledge

- Understanding of business domains like Fraud/Compliance/Risk preferable

- Bachelor's degree in a quantitative discipline such as mathematics, engineering, economics, finance, business, computer science. Master's degree or higher preferred. In lieu of a specific degree, advanced certifications in combination with strong experience will also be considered.

- The candidate must be at an advanced to expert level on SQL and Statistical knowledge

- Must have 6 - 9 years of relevant experience in field of analytics including 2 + years in data science, with preference working in financial services. Strong preference to experience in fraud or cybersecurity.

- Candidate must have a proven track record of building and deploying analytical solutions that have resulted in material financial results and extensive management experience. Ability to work in a fast-paced, dynamic environment is critical. Must have exceptional organizational, project management and communications skills.

Desired Skills:

- Solid knowledge of Python or Spark and various commercial and model generation software. Should additionally have familiarity with other tools such as HUE, Hive, and other data gathering tools