Data Scientist Lead, Sales Science

Deliver data-driven insights and strategies to enhance field client engagement and drive business outcomes within our Consumer & Community Banking division. Join our dynamic analytics team to leverage advanced data and analytics techniques and experimentation frameworks in delivering innovative insights and solutions across LOBs to enable our field teams to drive measurable business impact and customer outcomes.

Job Description:
As a Data Scientist Lead, within the Sales Science team, you will be responsible for supporting partner relationships within the Sales teams through analytical data exploration and reporting on outcomes, ad-hoc deep dives, test design building and reading, and sales strategy performance analysis.

Job Responsibilities:

• Collaborate with stakeholders to solve quantitative problems and optimize business processes using analytic methods such as predictive modeling, clustering, text mining, machine learning, optimization, and simulations.
• Lead the analytical optimization of xLOB sales funnels and act as a subject matter expert to identify opportunities
• Work with business partners and Technology to set quantifiable goals, advise on strategies, and experiment to achieve business objectives.
• Design, support, and share learnings from a multi-layer experiment framework allowing for optimization inside LOBs and across various field roles
• Communicate complex analytical results effectively and develop insights from data analysis to make recommendations to management.
• Prepare, write, and transform data from diverse sources to support analytical efforts using languages such as Python and SQL
• Stay updated on industry trends and test new advanced analytics techniques to address business challenges.

Required qualifications, capabilities, and skills:

• Masters in a related field, or bachelor’s with 5+ years' experience in a related discipline; 6+ years of related Analytics experience
• Hands-on experience in delivering analytics and insights to multiple levels of management (Including Test Design, Conversion/Response Reporting, Response Analysis, Incremental Analysis, Response Profiling and Target/Segmentation Analysis)
• Advanced knowledge of complex statistical and data science techniques, ML algorithms: linear/logistic regression, Clustering, Decision Trees, Random Forest, Neural Networks, Gradient Boosting, text mining using Machine learning toolkits (Python, R)
• Experience working with various databases (Teradata), Snowflake, AWS and advanced level database querying languages (SQL, HQL, SparkSQL) with modern cloud-based data architectures.
• Proven track record developing and launching GenAI solutions in Financial Services or a related industry
• Tangible experience with business strategy and tactical implementation, with the ability to define business KPIs and establish measurement frameworks
• Strong written and oral presentation / communication skills – the ability to convey complex information simply and clearly to senior business leaders and business partners and influence internal and external partners