Job Summary
As a Quant Analytics Senior Associate within the Product Strategy Team, you will help shape the future of Connected Commerce by developing data-driven solutions that optimize commercial transactions and support business growth. You will collaborate across the organization to advance product, design, enhancing customer experience.
In this role, you will apply your quantitative and problem-solving skills to deliver actionable insights and innovative solutions in a fast-paced environment. As part of the Connected Commerce Data & Analytics organization, you will contribute to advanced analytics projects across diverse operational functions, channels, and products.
**Job Responsibilities **
- Participate in data science projects: Leverage quantitative analytics on structured and unstructured data to generate actionable insights that influence business decision-making and strategic direction, address critical business problems, and identify growth opportunities.
- Drive analytics: Design, develop, and implement complex analytical solutions end-to-end with limited guidance, including formulating project proposals, performing hands-on data mining, cleaning, and exploratory analysis, defining key metrics, designing experiments and models, and translating abstract findings into actionable business solutions.
- Develop scalable solutions: Architect robust, efficient, and scalable data pipelines, modeling solutions, and analytics frameworks by leveraging cloud-based technologies (e.g., Snowflake, AWS, Tableau), programming languages (e.g., Python), and Gen AI skills (e.g., LLM calling, prompt engineering).
- Communicate insights optimally: Present findings, recommendations, and results effectively to both technical and non-technical audiences, including executive leadership, through clear reports, visualizations, and presentations to enable data-driven decision-making.
- Project management: Set and align expectations regarding timelines and scope. Manage priorities to meet commitments.
- Collaboration across teams: Establish and maintain close relationships with key cross-functional partners to understand business strategies, develop goals, identify impactful projects, address opportunities, influence key decisions with data, and ensure client satisfaction.
- Adaptation, compatibility, and culture fit: Contribute to a positive and inclusive culture and team environment.
Required Qualifications, Skills, and Capabilities
- BS/BA degree in a relevant quantitative field (e.g., Statistics, Economics, Finance, Business Analytics, Mathematics, Engineering, Computer Science, or a related field involving significant quantitative research and data analytics).
- 2+ years of financial services industry experience in business analytics roles (e.g., marketing/risk analytics, product analytics, business insights).
- 2+ years of work experience across a broad range of analytics technologies and tools (SQL, Spark, Python, Snowflake, AWS, Tableau, Unix, Excel Pivot, etc.) in a big data environment.
- Exceptional communicator capable of conveying complex information in an understandable, compelling, and persuasive manner to both technical and non-technical stakeholders.
- Adept critical thinker and problem solver with the ability to identify key drivers, prioritize tasks, be results-oriented, and demonstrate strong attention to detail.
- Ability to work independently as well as collaboratively in a dynamic, cross-functional environment, with a strong attention to detail and a passion for learning.
- Strong analytical and conceptual thinking skills, with a demonstrated ability to address complex, unstructured business problems through quantitative methods.
Preferred Qualifications, Skills, and Capabilities
- Master’s/PhD in a quantitative field (e.g., Statistics, Economics, Finance, Business Analytics, Mathematics, Engineering, Computer Science, or a related field involving significant quantitative research and data analytics) with hands-on experience leveraging sophisticated analytical, machine learning, natural language processing, and generative AI techniques.
- Experience prompt engineering.