Manager, Advanced Analytics

About the Role

Key Responsibilities

• Analyze and mine both structured and unstructured data to drive product centric and user centric insights.
• Proactively identify opportunities to leverage insights and drive product improvements across multiple functions throughout the organization.
• Design, monitor, and analyze A/B testing with statistical calculations such as t-test and power analysis.
• Use SQL and Python to query, retrieve, process, and analyze large amounts of clickstream and transactions data from databases like Teradata, BigQuery, Google Cloud, and Hive.
• Provide data-driven insights and deliver recommendations with a deep understanding of business problems.
• Connect data, analytics, and people to develop and implement creative solutions to support eCommerce products.
• Provide analytics and technical expertise to management, product managers, and data engineering teams to identify business opportunities and optimize product performance and engagement.
• Use data engineering, R, Python, and SQL to manipulate structured and unstructured data sources for analysis.
• Create effective reporting and dashboards using data visualization tools such as Tableau, Splunk, and Looker to monitor product performance.

Requirements

• Master's degree or equivalent in Business, Finance, Accounting, Statistics, Analytics, or related field; OR Bachelor's degree or equivalent in the same fields with 2 years of experience in data analytics or related field.
• Experience identifying target and guardrail metrics for A/B testing and conducting statistical analysis for experimental design.
• Experience using Pandas, Numpy, and Regex Libraries in Python to analyze structured and unstructured data.
• Experience creating reports and dashboards with data visualization tools like Tableau, Looker, or PowerBI.
• Experience analyzing data with SQL, Python, or R to identify customer behavior patterns and site performance.
• Experience implementing rule-based, heuristic, or time series prescriptive analytics techniques using Python and R.
• Experience applying analytical modeling techniques such as Kmeans clustering, SVM, KNN classification, or decision trees.
• Experience developing hypotheses for drivers of change in domain metrics and conducting exploratory analysis using SQL and Python.
• Proactive problem solving and debugging skills to identify and fix issues in data pipelines, working with engineers.

Nice to Have

• Experience with statistical calculations such as t-test and power analysis.
• Experience with large-scale data processing and cloud-based data warehouses like BigQuery and Google Cloud.
• Knowledge of data engineering practices.

Qualifications

• Master's degree or equivalent in relevant fields, or Bachelor's degree with 2 years of experience.

Benefits & Perks

• Competitive pay with performance-based incentive awards.
• Health benefits including medical, vision, and dental coverage.
• Financial benefits such as 401(k), stock purchase, and company-paid life insurance.
• Paid time off including PTO, sick leave, parental leave, family care leave, bereavement, jury duty, and voting.
• Other benefits including short-term and long-term disability, education assistance, company discounts, military service pay, and adoption expense reimbursement.