Competitive Intelligence Lead
The Meta Game, Inc.
Burlingame, CA, United States
7 days ago
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Role details
Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Experience level
Expert
Working hours
Regular working hours
Job source
Tech stack
Artificial Intelligence
Data Analysis
Data Governance
Data Transformation
Query Languages
Python (Programming Language)
Mathematical Software
SQL Databases
Scripting
Application Enhancement Tool
Data Ingestion
Generative AI
+1 more
Information Technology
Job description
- Market Strategy: Influence organization-level product direction through data-driven narratives and an in-depth understanding of the market landscape. Demonstrated experience operating at scale, across ambiguous environments with working knowledge of econometrics. As a quantitative market-strategist, blend practical and applied understanding with technical expertise, including pressure-testing data for quality, reliability, understanding data biases, and being solution-driven.
- Analytics Leadership: Conduct advanced analyses with 3P datasets, develop statistical models and forecasts, and deliver actionable insights that inform market and business strategy. Specific activities include:
- Data onboarding: Identify, onboard, and rigorously evaluate 3P datasets to determine their signal-to-noise ratio and predictive power.
- Data triangulation: Triangulate data from many sources of imperfect information. Synthesize multiple, low-fidelity 3rd-party signals into a single high-fidelity trend report using Bayesian aggregation or other methods.
- Data transformation: Apply quasi-experimental designs (e.g., synthetic control, diff-in-diff) to isolate the impact of exogenous market shocks and competitor actions on internal performance metrics.
- Insight and implications: Apply guidance from such analyses to increase the accuracy of forecasts and better understand market trends.
- Technical & Methodological Expertise: Act as a recognized professional in a technical or methodological area (e.g., causal inference, Bayesian aggregation), driving the adoption of advanced methods and organization-wide best practices.
- Data Governance & Quality: Ensure data privacy, security and compliance with organizational standards. Champion data quality frameworks and documentation practices that enable credible reproducible analyses.
- Resourceful and adaptable professional with a bias for action.
Requirements
- Bachelor’s degree and a minimum of 6 years of work experience (minimum 4 years with a Ph.D.) in business intelligence, product analytics or economic or strategy consulting in a technology environment.
- Demonstrated skill to ethically source, validate and synthesize high-signal insights from stakeholder interviews, skilled conversations, field research and relationship-based information gathering while maintaining high standards for privacy, consent and integrity.
- Proficiency in AI-powered tools: Demonstrate working knowledge of Generative AI technologies and experience designing, prompting and orchestrating AI systems to automate data analyses, synthesize insights and execute multi-step analytical tasks.
- Practical working understanding of data-analytics tools and direct experience managing, analyzing, manipulating and interpreting 1P and external 3P datasets.
- Experience with data querying languages (SQL), scripting languages (Python) and/or statistical/mathematical software (R).
- Proven experience with statistical analysis including causal inference, quasi-experiment or Bayesian aggregation.
- Demonstrated communication skills and experience presenting complex findings to both technical and non-technical stakeholders.
- Demonstrated experience thriving in ambiguous environments and shaping new analytics organizations or products., * Master’s or Ph.D. in a quantitative field such as Quantitative Economics, Political Science, Operations Research, Data Science, Computer Science, Physics, Business or Mathematics.
- Demonstrated ability to integrate AI tools to optimize/redesign workflows and drive measurable impact.
- Experience adhering to and implementing responsible, ethical AI practices.
- Demonstrated ongoing AI skill development and staying current with emerging AI technologies.
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