Lead Decision Science Analyst
Location-Type: Remote (CST/EST Hours required)
Start Date: ASAP
Duration: 6-Month Contract-to-Hire
Compensation Range: $80-90/hr
Benefits: Eligible for Health, Dental, Vision, and 401K
Visa Sponsorship: Not eligible for visa sponsorship Job Description:
- This role translates complex data into strategic insights that directly influence product, marketing, and business decisions for the client through causal inference, experimentation, and deep exploratory analytics.
- Conduct deep exploratory, diagnostic, and causal analyses to identify growth levers and quantify the business impact of key initiatives.
- Design, analyze, and interpret A/B tests and other causal inference approaches, ensuring test validity and clear stakeholder readouts.
- Partner cross-functionally with Product, Engineering, Marketing, and Finance leaders to develop and monitor KPIs and evaluate initiative impact.
- Translate technical findings into clear, actionable recommendations for senior stakeholders through verbal, written, and visual communication.
- Utilize SQL and Python to extract, manipulate, integrate, and analyze large datasets across multiple data platforms.
- Identify leading indicators, behavioral trends, and segmentation opportunities to guide organizational strategy.
- Provide guidance to associate and senior analysts on analytics best practices, experimental design, and statistical rigor.
- Bachelor's degree in Business Analytics, Statistics, Mathematics, Econometrics, Engineering, or a related field with significant analytical coursework.
- 5 years of relevant experience in an analytics role, preferably in product, marketing, or growth analytics.
- 2 years of experience building dashboards and reports in Power BI, Tableau, or comparable visualization tools.
- 2 years applying experimentation and causal inference methods (A/B tests, quasi-experiments) in product or marketing contexts.
- Exceptional SQL skills with a strong track record of working with complex datasets, including data extraction and manipulation.
- Experience with Azure or other cloud environments
- Proficiency in Python and/or R for statistical analysis and data manipulation.
- Strong verbal and written communication skills, with the ability to translate complex concepts into actionable business insights for non-technical stakeholders.
- Experience with data warehouse and data modeling concepts and procedures.
- Background in SaaS/technology-focused organization
- MBA or Master's degree in a related analytical field.
- Experience with Databricks.
- Experience with IoT, SaaS, or intelligent consumer products and services.
- Familiarity with Salesforce, SAP, or CDP platforms such as Tealium.
- Experience with project management and tracking tools such as Jira.
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