Location: Palo Alto, CA, United States

DESCRIPTION:

Duties: Build data solutions and extract insights from big data environments to design metrics and conduct in-depth analyses that drive business decisions. Partner with leaders across the business of Sales, Marketing, Finance and Account Management to deliver high-impact analytics. Establish strong partnerships with our stakeholders across Chase Payment Solutions. Collaborate with analytics and non-analytics groups to design solutions and provide actionable insights. Drive the execution of analytics and data science initiatives. Analyze data from a variety of data sources and identify key insights. Demonstrate strong analytical ability through understanding and implementation of various analytical and statistical techniques to answer high-priority business questions. Interpret analytical results and present findings to stakeholders. Build data visualization and provide ongoing enhancements to business dashboards. Experiment, develop, and produce high-quality machine learning models that drive business growth.

QUALIFICATIONS:

Minimum education and experience required: Bachelor's degree in Data Science, Business Analytics, or related field of study plus 1 year of experience in the job offered or as Data Scientist, Business Analyst, or related occupation.

Skills Required: This position requires any amount of experience with the following: Creating and maintaining dynamic and interactive dashboards using Tableau and Looker leveraging ETL automation, ODBC connector; creating advanced visualizations including heat maps, drill-down charts and tools including parameters, and LOD (Level of Detail) expressions; Conducting in-depth exploratory data analysis within large enterprise databases (Terabytes- scale) using SQL via CTE and window functions; transforming raw data into actionable insights using Python libraries including Pandas and NumPy for data manipulation, scikit-learn for machine learning, matplotlib, and seaborn for data visualization; Presenting data findings, model results, and performance metrics to cross- functional teams and translating complex analyses into strategic recommendations for business growth; Designing and building robust, scalable data processing and model training pipelines by leveraging Random Forest and K-Nearest Neighbors (KNN) machine learning algorithms; Developing, optimizing, and producing predictive modeling pipelines by Tree-based Pipeline Optimization Tool (TPOT) python libraries that automate hyperparameter tuning and model selection to enhance prediction performance and model efficiency; Automating and streamlining ETL workflows in order to produce recurring reports and data updates leveraging Excel and Alteryx workflows; Leverage advanced Excel functionalities including vlookup, index match, and pivot tables; PySpark and Snowpark data science libraries in Python; and data engineering pipelines for big data.

Job Location: 3223 Hanover St, Palo Alto, CA 94304.

Full-Time. Salary:  $148,699 - $170,000 per year.
 

Build data solutions and extract insights from big data environments to design metrics and conduct in-depth analyses that drive...