Lead, Decision Science Analyst (Product)

Chamberlain Group•Oak Brook, IL

2d•$102,600 - $193,425•Hybrid

About The Position

The Lead Decision Science Analyst translates data into strategic insights that directly influence product, marketing, and business decisions. This role focuses on causal inference, experimentation, and deep exploratory analytics to answer complex business questions. The Lead Decision Science Analyst will partner closely with cross functional leaders from Product, Engineering, Marketing, and Finance to design experiments, evaluate impact, uncover growth opportunities, and provide recommendations that drive measurable business outcomes. Success requires strong business acumen, statistical rigor, and exceptional communication skills.

Requirements

Bachelor’s degree in Business Analytics, Statistics, Mathematics, Econometrics, Engineering, or another related field with significant analytical coursework
5+ years of relevant work 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 other 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.
Ability to deal with ambiguity and make quality decisions in a dynamic, fast-paced environment.
Ability to effectively lead projects from conception to conclusion, both independently and in a team environment (including working with both internal and external business partners)
Strong understanding of business processes and strategic planning
Strong verbal and written communication and presentation skills, with the ability to translate complex concepts into actionable business insights.
Proven track record of leading projects and cross-functional teams
Strong problem-solving skills and the ability to think analytically.
Ability to work independently and collaboratively in a fast-paced environment.

Nice To Haves

MBA or Master’s degree in a related field
Experience with Azure (or other cloud environments) and Databricks
Understanding of data warehouse/data modeling concepts and procedures
Experience creating calculated metrics, managing and blending data models within Power BI
Experience with IoT, SaaS, and/or intelligent consumer products & services
Experience working with customer-facing digital experiences, including end-to-end customer acquisition and engagement processes within mobile applications or parallel platforms.
Experience with Salesforce, SAP, and CDP platforms such as Tealium
Experience with Project Management/Tracking tools such as Jira
Experience building and creating web-based data visualizations.
Experience creating temporary semantic data layers that support organizational self-service analytics within Azure Cloud architecture.
Strong understanding of financial concepts and analytics
Working with a software/technology organization

Responsibilities

Build relationships with business leaders and truly understand their strategy, key initiatives, and KPIs for success such that you have shared ownership for reaching their goals.
Conduct deep exploratory, diagnostic, and causal analyses to understand drivers of behavior, identify levers for growth, and quantify the business impact of initiatives
Design, analyze, and interpret A/B tests and other causal inference approaches; ensure test validity and clear readouts.
Develop, measure, and monitor product or customer KPIs in collaboration with product managers and finance partners.
Identify leading indicators, behavioral trends, and segmentation opportunities to guide strategy.
Translate technical results into clear recommendations for senior stakeholders using verbal and written analytic insights, compelling visualizations, and data-driven recommendations.
Communicate uncertainty, assumptions, tradeoffs, and limitations to non‑technical stakeholders.
Utilize SQL and Python to extract, manipulate, integrate, and analyze large datasets.
Develop a deep understanding of relevant data from various data platforms.
Translate complex business requirements into analytical frameworks.
Ensure data accuracy and integrity in all analytics and reporting.
Provide guidance to associate and senior analysts with analytics best practices, experimental design, and statistical rigor.
Comply with health and safety guidelines and rules; managers should also ensure compliance across their teams.
Protect Chamberlain Group’s reputation by keeping information confidential.
Maintain professional and technical knowledge by attending educational workshops, reading professional publications, establishing personal networks, and participating in professional societies.
Contribute to the team effort by accomplishing related results and participating on projects as needed.