JP Morgan Private Client

3 days ago

Columbus, Ohio, United States Chase Full time
Description

Join the team that provides expertise in data science and analytics for JP Morgan Private Client

As a Data Scientist Lead, within the JPM Private Client Data and Analytics team, you will be responsible for supporting partner relationships within the Private Client Sales Strategy team through analytical data exploration and reporting on outcomes, ad-hoc deep dives, test design building and reading, and overall portfolio 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, statistical forecasting, optimization, and simulations.
  • Lead the analytical optimization of the sales funnel and act as a subject matter expert to identify opportunities that impact sales.
  • Work with business partners and Technology to set quantifiable goals, advise on strategies, and experiment to achieve business objectives.
  • Deliver marketing, sales, finance, and business insights through analytics, reporting, and advanced visualization techniques.
  • 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, SAS, or Scala.
  • Stay updated on industry trends and test new tools and techniques to address business challenges.

 Required qualifications, capabilities, and skills:

  • Masters or PhD in a related field, or bachelor's with 5+ years' experience in a related discipline; 6+ years of related Marketing Analytics experience
  • Hands-on experience in delivering analytics and insights to multiple levels of management (Including Test Design, Financials, 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, Oracle), Snowflake, AWS and advanced level database querying languages (SQL, HQL, SparkSQL) with modern cloud-based data architectures. 
  • Technical understanding of data extraction, transformation, and load processing and proficiency in web analytics (Adobe Insight/Adobe Site Catalyst) 
  • 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

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