Data Scientist Lead, Sales Optimization

Key Skills

AWS, Data science techniques, Effective communication skills, KPIs, Leadership Skill, Machine learning techniques, Optimization, Python Programming, R Programming, Sales, SAS, Snowflake, Spark-SQL, SQL, Teradata

Job Description

Are you an expert in converting data into meaningful insights using the industry leading Machine Learning/Business intelligence tools and have interest working in Sales optimization? Then this is the right fit for you !The team provides expertise in data science & analytics to optimize sales performance for our bankers across the firm. Leverages industry-leading tools, Machine Learning / Business Intelligence to convert data into meaningful insights that enable sales leadership to drive value and an excellent customer experience for their business programs.

As a Data Scientist Lead in the Sales Optimization & Modeling function, you will partner with the various Lines of Business to analyze the performance of the bankers, financial and lending advisors in over 5,000 Chase branches. The role will develop key capabilities to analyze the sales interaction and identify opportunities to optimize how you engage customers with to improve customer acquisition and retention. You must be able to operate in a collaborative environment and will require you to engage with a wide variety of partners to socialize and move forward all Sales initiatives.

 Job responsibilities

• Develop the roadmap and execution of strategic initiatives to better manage Chase bankers with data and insights to help leadership identify strategic areas for improvement.
• Research, develop and implement new methods of measuring and analyzing data sets. Facilitate use case and requirements definition, design, testing, and implementation of new data delivery and analytic capabilities that address specific business needs.
• Understand the entirety of the sales funnel through incorporation of interaction data, quantification of opportunity and analysis of the pipeline data to identify opportunities.
• Collaborate across functions and Line of Business to drive Analytics and Insights, formulate quantifiable goals, advise on strategies and experimentation to achieve business goals.
• Support partnership with key Stakeholders with strong understanding of underlying data
• Develop advanced analytics using an assortment of modeling methods, algorithms and techniques, e.g., predictive modeling, text mining, statistical forecasting and analysis, optimization, and simulation modeling.
• Use data analysis techniques to develop insights that lead to new recommendations presented to management.
• Profile, wrangle, and prepare data from diverse sources to support analytical efforts. Write data transformation logic in languages such as Python, R, or Scala.

 Required qualifications, capabilities, and skills

• 6+ years of experience with analysis supporting an operating line of business
• Bachelors with 5+ years' experience in a quantitative or related discipline
• 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 and SAS)
• Comfortable communicating complex concepts into digestible information to be consumed by audiences of varying levels in the organization
• Experience working with various databases (Teradata, Oracle), Snowflake, AWS and advanced level database querying languages (SQL, HQL, Spark SQL) with modern cloud-based data architectures
• Problem-solving skills are essential. Must be able to think outside the box to implement creative solutions that solve business problems.
• Demonstrated ability to define business KPIs and establish measurement frameworks
• Proven ability to work in a fast paced environment, meet deadlines. Must be detail oriented, organized, and perform at high standards
• Excellent written and verbal communications skills with the ability to work and collaborate with internal and external partners.

Preferred qualifications, capabilities, and skills

• Masters or PhD in a quantitative field preferred: Statistics, Applied Mathematics, Computing and Information Theory, Econometrics, Biostatistics, Operations Research, or Industrial / Electrical Engineering
• Financial services experience preferred.