Research Scientist

Essential functions

• Evaluation Analysis: Lead quantitative and qualitative analyses of safety evaluation data, including analyses of results patterns, distributional analyses, trend detection, and comparative assessments across languages, markets, and model versions. Apply state-of-the-art statistical methods to extract meaningful insights.

• Report Creation: Develop comprehensive, well-structured reports that synthesize evaluation results, highlight key findings, surface risks, and provide actionable recommendations for engineering, product, and policy teams. Ensure reports are accessible to both technical and non-technical audiences.

• Dashboard Development: Design and build interactive dashboards that provide real-time and historical visibility into safety evaluation metrics, trends, and cross-market comparisons. Ensure dashboards are clear, self-service, and tailored to diverse stakeholder needs.

• Cross-Functional Sharing: Present findings and recommendations to stakeholders across the organization, including engineering, product, legal, and executive teams. Translate complex analytical results into clear narratives that drive decision-making.

• Collaboration with Experts: Work closely with subject matter experts and other specialists to contextualize analytical findings, collaboratively validate interpretations across languages (working with language experts), and ensure that cross-market comparisons account for linguistic and cultural variation.

• Methodological Rigor: Establish and maintain analytical standards, reproducible workflows, and documentation practices that ensure consistency, transparency, and quality across all reporting deliverables.

Qualifications

• 3+ years of experience in an applied research or data science role with a focus on quantitative analysis, reporting, and insight generation.

• Advanced degree (MS/PhD) in Statistics, Data Science, Computational Social Science, Quantitative Psychology, or a related field.

• Strong proficiency in statistical analysis methods, including clustering, latent pattern analysis, regression, and hypothesis testing.

• Comfortable producing high-quality reports and data visualizations for diverse audiences, using tools such as Python (matplotlib, seaborn, plotly), R, Tableau, or similar.

• Experience building dashboards or automated reporting systems for ongoing monitoring and stakeholder communication.

• Able to produce meaningful visualizations and reports of complex data, and effectively present results to different audiences and across multiple media formats.

• Able to work independently to drive outcomes among cross-functional teams, with minimal direction.

• Organized, highly attentive to detail, and manages time well.

• Excellent written and oral communication skills.

Would be a plus

• Advanced degree (MS/PhD) in Statistics, Data Science, Computational Social Science, Quantitative Psychology, or a related field.

• Experience working in industry.

• Experience conducting analyses across multilingual or cross-cultural datasets.

• Experience with variable modeling, item response theory, or psychometric methods.

• Proficiency with dashboard and BI tools (e.g., Tableau, Looker, Superset, or custom-built solutions).

• Prior experience in AI safety, responsible AI, content moderation, or related domains.

• Experience with large-scale data infrastructure (e.g., Spark, Hadoop, or cloud-based analytics platforms).

We offer

• Opportunity to work on cutting-edge projects

• Work with a highly motivated and dedicated team

• Competitive salary

• Flexible schedule

• Benefits package - medical insurance, vision, dental, etc.

• Corporate social events

• Professional development opportunities

• Well-equipped office

About us

Grid Dynamics (NASDAQ: GDYN) is a leading provider of technology consulting, platform and product engineering, AI, and advanced analytics services. Fusing technical vision with business acumen, we solve the most pressing technical challenges and enable positive business outcomes for enterprise companies undergoing business transformation. A key differentiator for Grid Dynamics is our 8 years of experience and leadership in enterprise AI, supported by profound expertise and ongoing investment in data, analytics, cloud & DevOps, application modernization and customer experience. Founded in 2006, Grid Dynamics is headquartered in Silicon Valley with offices across the Americas, Europe, and India.