Data Analyst

Engage stakeholders to understand business problems and customize analytic and predictive model solutions to business needs.

Solve problems using advanced statistical techniques including, but not limited to regression/logic regression, bootstrap, factor analysis, decision tree, clustering & binning, and basket analysis.

Conduct exploratory data profiling techniques, common summary descriptive statistics, etc.

Develop and maintain expertise in a wide range of new technologies, methodologies, and techniques facilitating advanced research, decision sciences, and systems engineering.

Support the design and management of market and product experiments and pilots to test hypotheses or generate test and control observation data.

Partner with Technology, Product Management, Engineering, Marketing, Sales, and Finance teams to deliver solutions for clients and into the operation.

Build and lead a team of analysts, while initially serving as an individual contributor.

Lead projects with moderate complexity.

Engage internal customers to understand problems and customize analytic and predictive model solutions to business needs.

Bachelor's or Master's in Mathematics, Science, Statistics or related Technical field; or Equivalent related professional experience (e.g. driving significant and sustained change and performance improvement from data-driven insights)

Demonstrates statistical competency and requires limited supervision

Familiar with SQL, Python, or R, or any other major data analysis programming language

Having a work experience in the fundamentals of big data architecture (streaming events, data lakes, analytics engines) and relational database models

Display strong domain knowledge, business acumen, and critical reasoning skills

Strong proficiency in Excel, PowerPoint, and statistical/data processing software and programming languages (e.g., SAS, R, SQL, SPSS, etc.).

Mines data sets using sophisticated analytical techniques to generate insights and inform business decisions

Identifies and tests hypotheses, ensuring statistical significance through experimental design and builds predictive models for business application, product development, etc.

Translates quantitative analyses and findings into accessible visuals for all stakeholders and multiple audiences, and provide clear view into interpreting data

Ability to work in cross-functional teams