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Data Science, Lead

2 weeks ago

Bengaluru, Karnataka, India Bread Financial Full time ₹ 12,00,000 - ₹ 24,00,000 per year

**Every career journey is personal. That's why we empower you with the tools and support to create your own success story.*
Be challenged. Be heard. Be valued. Be you ... be here.
*Job Summary
The Data Science team delivers best in class actionable business insights through cutting-edge predictive models and data science techniques. The Lead Data Scientist is responsible for generating data-driven insight using advanced analytics and machine learning techniques to support enterprise data science needs within Bread Financial, and researching state-of-art advanced analytics techniques to continuously improve the Data Science team's competence within the analytics industry. Additionally, this role manages the design and innovation of market differentiators within the Data Science team. The Lead Data Scientist works autonomously with additional responsibility of leading projects and may also mentor and onboard data scientists on the team.

Essential Job Functions

  • Create and Design - Create machine-learning based tools or processes for data mining and data analytics. Extend data with third party sources of information when needed. Translate business problems into statistical problems, develop machine learning models and customized analysis to support business needs.
  • Analytics – Contribute to and guide the team to extract and sample data, conduct data integrity checks and applicable data pre-processing such as treatment of missing values and outliers. Conduct exploratory data analysis for preliminary data insights to drive the selection of modeling approach that best addresses the business problem. Reveal hidden data patterns by data mining using unsupervised learning techniques such as clustering analysis and factor analysis. Conduct feature engineering to create/derive model predictors with strong predictive power and train classification/regression models by applying supervised learning techniques such as generalized linear models assuming applicable underlying distributions such as logit and gamma, tree-based models such as decision trees, random forest, boosted trees, etc., and neural net models. Conduct proper model test/validation, diagnose and fix model issues (e.g., over-fitting) when applicable. Size the impact of using the models in production as part of the current strategy. Present results and business case to manager. Provide support for implementation and monitoring of solutions that are implemented.
  • Collaboration – Contribute and guide the team to, translate analytical results into useful recommendations for review with manager. Demonstrate strong verbal and written communication skills when working with internal partners and when presenting results to various audiences. Develop foundational knowledge of credit card operations, banking, financial, loyalty rewards, retail, and credit card regulations while working with the business. Collaborate with other data scientists in the organization to share best practices and data science innovations.
  • Model Risk Management - Develop foundational knowledge and also guide the team on common model risks and related regulatory requirements. Apply proper first line of defense controls during model development process to minimize model risk. Create comprehensive model governance documentation and archive model data, scripts, and result. Collaborate with model risk management partners to complete model validation/auditing. Complete remediation as required by model governance process.
  • Coaching and Development - Manage and coach the team to ensure delivery excellence, sustainability and scalability. This team assists the organization by providing end to end predictive solutions for marketing and credit teams which helps to understand customer behaviour and target the right customer at the right time. Will have direct reports in associate mentoring/on-boarding, is a proxy for direct manager and will contribute to talent evaluation process.
  • Data Science Innovation – Research industry trends in data science of new tools, emerging algorithms, advanced platforms, and alternative data to enhance modeling effectiveness and efficiency. Conduct use case testing for new tools/techniques/platforms/data and provide user input/feedback. Conduct research to continuously improve predictive modeling methodology to achieve better outcomes.
  • Leadership - Demonstrate leadership by providing thought leadership, mentorship, and training to junior data scientists in the department. Participate in business diagnostic, problem definition, solution proposal, project design, and resource planning. Independently lead analytical projects to completion, collaborate with stakeholders and utilize excellent communication skills to gain consensus on the recommendation.

Reports To
Manager or higher

Direct Reports
Up to 2

Working Conditions/ Physical Requirements

  • Normal office environment. Hybrid environment.
  • Some travel may be required.

Minimum Qualifications

  • Bachelor's degree in statistics, mathematics, engineering, data science, economics, computer science, or another related quantitative field.
  • 8+ years of experience in the software industry.
  • 4+ years of experience in building and deployment of machine learning models.

Preferred Qualifications

  • Master's degree in statistics, mathematics, engineering, data science, economics, or computer science.
  • Experience conducting data mining to solve business problems.
  • Experience in extracting and processing large files/data sets.
  • Experience interpreting model results and translating insights into business recommendations.

Knowledge, Skills And Abilities

  • Team Management
  • Data Analytics
  • Data Mining
  • Data Science
  • Machine Learning
  • Pivot Tables
  • PowerPoint Presentations
  • Predictive Modeling
  • Python
  • Spark SQL
  • Statistical Concepts
  • Cloud Experience (AZURE/AWS)
  • Structured Query Language (SQL)
  • Good Communication skills
  • SAS
  • Financial Services
  • Natural Language Processing (NLP)
  • Time Series Forecasting
  • R Programming

Other Duties
This job description is illustrative of the types of duties typically performed by this job. It is not intended to be an exhaustive listing of each and every essential function of the job. Because job content may change from time to time, the Company reserves the right to add and/or delete essential functions from this job at any time.

About Bread Financial
At Bread Financial, you'll have the opportunity to grow your career, give back to your community, and be part of our award-winning culture. We've been consistently recognized as a best place to work nationally and in many markets and we're proud to promote an environment where you feel appreciated, accepted, valued, and fulfilled—both personally and professionally. Bread Financial supports the overall wellness of our associates with a diverse suite of benefits and offers boundless opportunities for career development and non-traditional career progression.

Bread Financial (NYSE: BFH) is a tech-forward financial services company that provides simple, personalized payment, lending, and saving solutions to millions of U.S consumers. Our payment solutions, including Bread Financial general purpose credit cards and savings products, empower our customers and their passions for a better life. Additionally, we deliver growth for some of the most recognized brands in travel & entertainment, health & beauty, jewelry and specialty apparel through our private label and co-brand credit cards and pay-over-time products providing choice and value to our shared customers.

To learn more about Bread Financial, our global associates and our sustainability commitments, visit or follow us on Instagram and LinkedIn.

  • All job offers are contingent upon successful completion of credit and background checks.
  • Bread Financial is an Equal Opportunity Employer.

Job Family
Information Technology

Job Type
Regular