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Business Banking Sales Quant Analytics Manager
manager · Data Science & Analytics
Bring your analytical and technical depth to a role where your work directly shapes sales strategy and portfolio performance. Job Template - shortened - 12-05-24 - PDF.pdf You will partner closely with business leaders to design, execute, and measure strategic initiatives—turning data into clear decisions and measurable outcomes. If you enjoy solving ambiguous problems, influencing stakeholders through insights, and delivering high-impact reporting and experimentation, this role offers the opportunity to grow your leadership while raising the bar on analytical excellence and control discipline.
Job summary
As a Quantitative Analytics Manager in the Business Banking Data and Analytics team, you will support the sales strategy organization through analytical exploration, reporting on outcomes, forecasting, and portfolio performance analysis, with an emphasis on control execution and monitoring. You will lead day-to-day partnerships with internal clients to design, develop, implement, and track stategic sales initiatives from a data and analytics perspective. You will translate complex analytical findings into clear, actionable recommendations for senior stakeholders. You will operate with strong ownership, resourcefulness, and a collaborative approach across partners.
In this role, you will blend deep quantitative methods with practical business judgment—balancing speed, rigor, and data quality to deliver insights leaders can trust. You will help shape how measurement is defined, how tests are designed and interpreted, and how performance is monitored over time. Your work will span diagnostic deep dives, tactical analyses, and longer-term strategic problem-solving, grounded in strong governance and controls.
Job responsibilities
- Develop insights, methods, and tools from large datasets using advanced analytics (predictive modeling, clustering, text mining, machine learning, statistical forecasting, simulation, and visualization).
- Integrate data from multiple sources and disparate databases to form conclusions and inform strategies.
- Analyze data to identify improvement opportunities, validate inputs, detect defects, and surface statistical anomalies tied to business processes.
- Strengthen and assess processes and controls that support consistent, measurable business results.
- Lead partnerships with stakeholders by building strong understanding of business drivers and underlying data.
- Translate complex analytical results into clear narratives and recommendations for business leaders.
- Partner with business owners to define quantifiable goals; advise on strategies and experimentation to achieve them.
- Lead execution of key performance indicators, trend analysis, dashboards, segmentations, and optimization to improve business performance.
- Collaborate across functions and lines of business to drive analytics, insights, and execution.
- Build and maintain strong internal client relationships through proactive communication and dependable delivery.
Required qualifications, capabilities, and skills
- Doctorate or Master’s degree in a related field with 5 years of experience, or Bachelor’s degree with 7 years of experience in a related discipline (for example: computer science, operations research, physics, mathematics, engineering, econometrics, statistics, or similar).
- Demonstrated ability to communicate analytical findings clearly and influence senior business leaders.
- Experience delivering analytics and insights to multiple levels of management.
- Proficiency in standard data mining and analytical methods (for example: modeling, segmentation, forecasting, and experimentation).
- Proficiency in data analysis languages such as Python, SAS, or R.
- Proficiency with relational databases and strong SQL skills.
- Strong analytical, interpretive, and problem-solving skills with attention to data quality and reliability.
- Technical understanding of data extraction, transformation, and load processing.
- Ability to manage multiple priorities, deliver in a fast-paced environment, and work effectively with cross-functional partners.
Preferred qualifications, capabilities, and skills
- Hands-on experience designing, building, and operating solutions on cloud data platforms (for example: Snowflake, Amazon Web Services, or Databricks) or equivalent.
- Experience with server-based dynamic and interactive reporting solutions.
- Experience with straight-through processing tools (for example: Alteryx) or equivalent.
- Experience with visualization tools (for example: Tableau) or equivalent.
- Exposure to query optimization and performance tuning in analytic workflows.