Lead Advanced Analyst, Product Analytics

Maleda Tech

6d•$115 - $128•Remote

About The Position

We're looking for a Lead Advanced Analyst to support a fast-moving consumer product team. This role sits at the intersection of data, product, and strategy - using rigorous analysis, experimentation, and statistical modeling to shape decisions that directly impact the product experience. You'll work closely with Product, Engineering, Finance, Marketing, Operations, and Data Science teams to turn complex data into clear, actionable direction, and you'll have real influence over how the product evolves.

Requirements

6+ years of industry experience in a quantitative field (Statistics, Econometrics, Computer Science, Engineering, Mathematics, Data Science, Operations Research, or similar); Master's or PhD a plus
Prior experience in an advanced analytics or product data science role
Strong business acumen and strategic thinking, with the ability to conduct rigorous analysis and make sound judgment calls
Excellent communication skills, able to explain complex concepts clearly to a range of audiences
Proven stakeholder management skills, with the ability to collaborate and influence across functions
Experience partnering directly with product teams on analytics strategy, experimental design, and measurement
Experience analyzing A/B experiments and statistical data
Experience designing and building metrics, from concept through data pipeline implementation
Strong proficiency in Python or R, plus SQL
Experience with AI-assisted analytics tools (e.g., Claude, ChatGPT)
A growth-minded, agile approach with a track record of driving projects from idea to impact

Nice To Haves

Master's or PhD a plus

Responsibilities

Work with large, complex data sets to solve challenging analytical problems using a range of statistical and quantitative methods
Apply quantitative analysis, experimentation, data mining, and forecasting to identify trends that inform product and business decisions
Collaborate cross-functionally with Product, Engineering, Finance, Marketing, Operations, Data Science, and Analytics Engineering teams to deliver actionable insights
Design, execute, and analyze experiments to measure feature impact, using causal inference methods when randomized trials aren't feasible
Design and build metrics and dimensions to monitor product and business performance
Build reporting and analytical tools that enable stakeholders to make data-driven decisions
Present findings and recommendations clearly to stakeholders, including senior leadership
Stay current on industry trends and advancements in quantitative and qualitative analysis techniques
Use AI tools to automate repetitive analytical work and support stakeholder self-service