About the Role
The US Personal Banking Analytics (USPBA) Data Science team at Citi is expanding and actively seeking Data Science experts across various levels, with experience ranging from 5 to 15 years.
What We Do
The USPBA Data Science team leverages big data tools and advanced machine learning and AI techniques to analyze millions of prospects and billions of customer-level transactions. Our goal is to uncover opportunities to meet client financial needs and generate economic value for the bank. The team is responsible for extracting relevant insights, identifying business opportunities, converting business problems into modeling frameworks, building predictive models, implementing solutions, and designing go-to-market strategies for a wide array of business challenges.
What’s Expected From You?
We are looking for an experienced Data Science candidate who can demonstrate the following behaviors:
- Modeling and Tech Savvy: Stay current with the latest modeling use cases, machine learning, and deep learning algorithms, and share knowledge within the team.
- Statistical Mindset: Possess proficiency in basic statistics, hypothesis testing, segmentation, and predictive modeling.
- Communication Skills: Ability to translate and articulate technical thoughts and ideas to a broader audience, including influencing peers and senior management.
- Client Obsession: Create client-centric analytic solutions to business problems, maintaining a holistic view of multiple businesses.
- Analytic Project Execution: Own and deliver multiple complex analytic projects, understanding business context, converting problems into modeling frameworks, and implementing solutions.
- Domain Expert: Be a domain expert in your sub-field and have a holistic view of other business lines (new customer acquisition, existing customer management, customer retention, product development, pricing and payment optimization, digital journey, Customer experience, and control automation).
- Strategic Acumen: Ability to see the big picture, identify emerging trends, challenge the status quo, and design growth goals.
- Risk Assessment: Appropriately assess risk in business decisions, safeguarding Citigroup's reputation, clients, and assets by complying with applicable laws and regulations.
- People Management Role: For candidates with 7+ years of experience and at least 2+ years in a people management role, be prepared to understand team performance, make decisions regarding staffing, goal setting, performance evaluation, promotions, and terminations.
Skillset You Should Possess
Beyond a love for data and eagerness for new challenges, candidates should have the following:
Basic Qualifications
- Bachelors/Master’s Degree with 5+ years of experience in data analytics.
- Hands-on experience in Python or R programming along with strong experience in SQL.
- Comfortable working with packages such as Pandas and Numpy.
- Experienced in working with large and multiple datasets, data warehouses, and ability to pull data using relevant programs and coding.
- Well-versed with necessary data preprocessing and feature engineering skills.
- Experience implementing Machine learning algorithms such as Random Forest and Gradient Boosting in solving business problems like recommender systems.
- Experience implementing deep learning techniques like artificial neural networks, convolutional neural networks, and recurrent neural networks.
- Experience with Computer vision, text recognition (OCR), natural language processing, BERT, and word embeddings.
- Strong background in Statistical Analysis.
- Ability to identify, clearly articulate, and solve complex business problems, presenting them to management in a structured and simpler form.
- Strong People management skills.
- Experience working in onsite, offsite delivery models.
- Excellent communication and inter-personal skills.
- Strong process/project management skills.
- Multiple stakeholder management experience.
- Ability to guide and mentor juniors.
- Control-oriented and risk-aware.
Preferred Qualifications
- Experience in Credit Cards and Retail Banking.