AI-Driven Decision Scientist for Product Analytics

United States Digital Space LLC

United States

On-site

USD 110,000 - 160,000

Full time

9 days ago

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Benefits offered by this job

Ownership program

Flexible work culture

Remote/hybrid/in-office options

Generous time off

Wellness programs

Tuition reimbursement

Learning and development resources

Employee recognition program

Job summary

United States Digital Space LLC is seeking a Decision Scientist to drive data-informed decisions across our organization. You will deliver high-quality analyses and partner with cross-functional teams to translate business questions into actionable insights.

You will design experiments, perform causal analyses, and contribute to product and go-to-market strategies using SQL, Python or R, and BI tools. Experience in SaaS or EdTech is a plus; our team values clear storytelling and a collaborative,

Qualifications

Master's degree in Statistics, Computer Science, Economics, Applied Mathematics, Operations Research, or a related quantitative field (PhD is a plus).
2–4 years of experience in data science, analytics, or a related discipline with demonstrated ability to deliver actionable insights.
Strong understanding of statistical modeling, machine learning fundamentals, and experimental design (A/B testing).
Familiarity with AI tooling (Claude, ChatGPT, Glean) to improve productivity.
Strong proficiency in SQL for data extraction and manipulation.
Proficiency in Python or R for data analysis, modeling, and visualization.
Proficiency in a Business intelligence tool (Tableau, PowerBI... etc.).
Experience working with modern data platforms (e.g., Snowflake, Databricks, Fivetran).
Strong communication and storytelling skills with the ability to present complex analyses clearly.
Experience in SaaS, product analytics, or EdTech environments is a plus.
Ability to work effectively in a fast-paced, cross-functional environment.

Responsibilities

Support business impact through data-driven insights.
Conduct analyses that uncover opportunities to improve product adoption, customer engagement, and revenue growth using rigorous analytical methods.
Execute experimentation and causal analysis.
Support the design and execution of A/B tests and causal inference studies to evaluate the impact of new product features, pricing strategies, and go-to-market initiatives.
Contribute to product and business strategy.
Partner with product managers, engineers, and marketing teams to translate business questions into structured analytical frameworks and deliver clear, actionable findings.
Deliver analytical solutions end-to-end. Own the lifecycle of analytical projects — from scoping problems and building models to presenting insights and tracking outcomes.
Apply AI-first thinking.
Leverage AI tooling (e.g., Claude, ChatGPT, Glean) to accelerate analysis, improve throughput, and elevate the quality of deliverables.
Communicate insights clearly. Translate analytical findings into recommendations that both technical and non-technical stakeholders can understand and act on.