Manager - Data Science - Financial Services Risk Management

Key Responsibilities :

- Demonstrate strong technical capabilities and knowledge of machine learning algorithms, optimization algorithms, and data handling techniques.

- Design solutions for challenges facing our clients using pattern mining/detection, big data analytics and predictive modelling.

- Lead initiatives across risk domains to identify opportunities for improving efficiency on client engagements and internal practices through the application of advanced analytics.

- Stay updated with current trends in the field of advanced analytics relevant to the client's business

- Guide the team in advanced statistics, modelling, machine learning and AI methodologies

- Lead large scale client engagements while consistently delivering quality client services

- Monitor progress, manage risk, and effectively communicate with key stakeholders regarding status, issues and key priorities to achieve expected outcomes

Qualifications, Certifications and Education :

Must-have :

- M.Sc./M.Tech or Ph.D. in statistics, mathematics, econometrics, computer science, physics or related field.

- Significant experience and expertise in the following (preferably in the field of finance):

a. Developing/validating Machine learning (random forests, SVMs, SGB and unsupervised learning, etc.) models

b. Developing/validating Artificial intelligence (neural networks, NLP, probabilistic inference, computational statistics, etc.) models

c. Exposure to Big Data platforms like Hadoop and its eco-system

- Prior experience of leading teams in building predictive models preferably in the field of finance

- Strong hands-on skills in sourcing, cleaning, manipulating and analyzing large volumes of structured and unstructured data, data at rest and data in motion

- Relevant programming experience in high-level languages such as SAS, R, Python, Java etc.,

- Excellent analytical (including problem solving), risk and team management skills

- Previous project management experience.

Good-to-have :

- Big data/ML/AI solution implementation in the financial services domain

- Certifications in finance such as FRM, CFA, PRM

- Knowledge of mathematical concepts related to pricing derivatives for any of the asset classes such as fixed income, equities, credit, interest rates, FX, and commodities

- Risk management knowledge in market risk and/or counterparty credit risk

- Regulatory knowledge/experience in areas such as Basel, CCAR, FRTB

- Risk management system knowledge/experience - Calypso, SunGard Adaptiv, Murex etc.,

- Willingness to travel to meet client needs