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# Data Scientist (Technical Leadership)

- **Company:** The Meta Game, Inc.
- **Location:** Albany, NY, United States
- **Experience:** Expert
- **Salary:** $210,000.0 - $281,000.0
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Data Analysis, Computer Engineering, Data Mining, Machine Learning, Information Technology
- **Published:** August 6, 2026
- **Apply:** https://www.techcareers.com/job.asp?id=3342457082&tx=JT9486TYT&pt=1&aff=0B19D771-A501-4A5E-8338-2A822B784D54&utm_source=Job%20Feed&utm_medium=textkernel&utm_campaign=DE&utm_term=0B19D771-A501-4A5E-8338-2A822B784D54

## About the Role

1. Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience
 2. 8+ years of experience in data science or analytics, leading analytics work in an IC capacity, working collaboratively with Engineering and cross-functional partners, and guiding data-influenced product planning, prioritization and strategy development
 3. Experience working effectively with multiple stakeholders and cross-functional teams, including Engineering, PM/TPM, Analytics and Finance
 4. Experience framing and communication skills, 1. Demonstrated ability to integrate AI tools to optimize/redesign workflows and drive measurable impact (e.g., efficiency gains, quality improvements)
 2. Masters or Ph.D. Degree in a quantitative field
 3. Demonstrated ongoing AI skill development (e.g., prompt/context engineering, agent orchestration) and staying current with emerging AI technologies
 4. Experience with predictive modeling, machine learning, and experimentation/causal inference methods
 5. Experience adhering to and implementing responsible, ethical AI practices (e.g., risk assessment, bias mitigation, quality and accuracy reviews)

## Description

1. Work with large and complex data sets to solve a wide array of challenging problems using different analytical and statistical approaches
 2. Apply technical expertise with quantitative analysis, experimentation, data mining, and the presentation of data to develop strategies for our products that serve billions of people and hundreds of millions of businesses
 3. Identify and measure success of product efforts through goal setting, forecasting, and monitoring of key product metrics to understand trends
 4. Understand and identify opportunities to more responsibly leverage cutting edge technology
 5. Define, understand, and test opportunities and levers to improve the product, and drive roadmaps through your insights and recommendations
 6. Partner with Product, Engineering, and cross-functional teams to inform, influence, support, and execute product strategy and investment decisions
 7. Navigate ambiguity and complexity by forming clear hypotheses, making data-driven decisions, and proactively identifying areas for deeper investigation


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