About BNP Paribas Group

BNP Paribas is a top-ranking bank in Europe with an international profile. It operates in 71 countries and has almost 199 000 employees. The Group ranks highly in its three core areas of activity: Domestic Markets and International Financial Services (whose retail banking networks and financial services are grouped together under Retail Banking & Services) and Corporate & Institutional Banking, centred on corporate and institutional clients. The Group helps all of its clients (retail, associations, businesses, SMEs, large corporates and institutional) to implement their projects by providing them with services in financing, investment, savings and protection. In its Corporate & Institutional Banking and International Financial Services activities, BNP Paribas enjoys leading positions in Europe, a strong presence in the Americas and has a solid and fast-growing network in the Asia/Pacific region.

About BNP Paribas India Solutions

Established in 2005, BNP Paribas India Solutions is a wholly owned subsidiary of BNP Paribas SA, a leading bank in Europe with an international reach. With delivery centers located in Bengaluru, Chennai and Mumbai, we are a 24x7 global delivery center. India Solutions services three business lines: Corporate and Institutional Banking, Investment Solutions and Retail Banking for BNP Paribas across the Group. Driving innovation and growth, we are harnessing the potential of over 6000 employees, to provide support and develop best-in-class solutions.

About Business Line/Function

GM Data & AI Lab leverages the power of Machine Learning and Deep learning to drive innovation in various business lines. Our primary goal is to harness the potential of vast amounts of structured and unstructured data to improve our services and provide value. Today we are a team of around 40+ Data Scientists based in Paris, London, Frankfurt, Lisbon, New York, Singapore and Mumbai.

Job Title

Data Scientist (Quant Research)

Date

Department:

Front Office Support

Location:

Mumbai

Business Line / Function

Global Markets – Data & AI Lab

Reports To

(Direct)

Grade

(if applicable)

(Functional)

Number Of Direct Reports

NA

Directorship / Registration

NA

Position Purpose

Your work will center on designing and deploying AI solutions for time series forecasting, financial modeling, anomaly detection and other Quant related usecases. We use AI to discover patterns, classify information, and predict likelihoods. Our team works on building, refining, testing, and deploying these models to support various business use cases, ultimately driving business value and innovation.

As a Data Scientist on our team, you can expect to work on challenging projects, collaborate with stakeholders to identify business problems, and have the opportunity to learn and grow with our team. A typical day may involve working on model development, meeting with stakeholders to discuss project requirements/updates, and brainstorming/debugging with colleagues on various technical aspects.

At the Lab, we're passionate about staying at the forefront of AI research, bridging the gap between research & industry to drive innovation and to make a real impact on our businesses.

Responsibilities

Develop and maintain AI models on time series & financial date for predictive modelling, including data collection, analysis, feature engineering, model development, evaluation, backtesting and monitoring.
Identify areas for model improvement through independent research and analysis, and develop recommendations for updates and enhancements.
Working with expert colleagues, Quant and business representatives to examine the results and keep models grounded in reality.
Documenting each step of the development and informing decision makers by presenting them options and results.
Ensure the integrity and security of data.
Provide support for production models delivered by the Mumbai team but potentially as well for other models to any of the Asian/EU/US time zones.

Technical & Behavioral Competencies

Bachelor’s or Master’s degree in a numeric subject with understanding of economics and markets (eg.: Economics with a speciality in Econometrics, Finance, Computer Science, Applied Maths, Engineering, Physics)
Knowledge of key concepts in Statistics and Mathematics such as Statistical methods for Machine learning, Probability Theory and Linear Algebra.
Knowledge of Monte Carlo Simulations, Bayesian modelling & Causal Inference.
Experience with Machine Learning & Deep Learning concepts including data representations, neural network architectures, custom loss functions.
Proven track record of building AI models on time-series & financial data.
Programming skills in Python and knowledge of common numerical and machine-learning packages (like NumPy, scikit-learn, pandas, PyTorch, PyMC, statsmodels).
Ability to write clear and concise code in python.
Intellectually curious and willing to learn challenging concepts daily.

Skills Referential

Behavioural Skills:

Ability to collaborate / Teamwork

Critical thinking

Communication skills - oral & written

Attention to detail / rigor

Transversal Skills

Analytical Ability

Education Level

Bachelor Degree or equivalent

Experience Level

At least 2 years

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