Research Scientist

Grid Dynamics; United States; On-site; USD 120,000 - 190,000; Full time

Benefits offered by this job

Cutting-edge projects

Motivated team

Corporate events

Well-equipped office

Job summary

Grid Dynamics is seeking a Research Scientist to lead the analysis, reporting, and cross-functional dissemination of safety evaluation results across languages and markets. You will supervise and collaborate with managed services partners on latent pattern analyses, building reports and dashboards to share insights with stakeholders.

An ideal candidate has strong quantitative research skills, experience delivering high-impact analytical deliverables, and the ability to work with cross-functional

Qualifications

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

Responsibilities

• 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.

Skills

Statistical analysis

Clustering

Latent pattern analysis

Regression

Hypothesis testing

Python (matplotlib,seaborn,plotly)

R

Tableau

Dashboard development

Data visualization

Independent work

Strong communication

Cross-functional collaboration

Tools

Spark

Hadoop

Job description

This role is for a Research Scientist to lead the analysis, reporting, and cross-functional dissemination of safety evaluation results across languages and markets. You will play a crucial role in supervising and collaborating with managed services partners on latent pattern analyses, creating comprehensive reports and dashboards, and sharing insights with cross-functional stakeholders.

An ideal candidate possesses strong quantitative research skills, experience producing high-impact analytical deliverables, and the ability to work closely with cross-functional partners and subject matter experts. In this role, your collaborative work will enable the team to derive insights from evaluations conducted with language experts and multi-lingual annotators, contextualizing findings across diverse linguistic and cultural settings.

Responsibilities

• 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.

Min requirements

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

• Experience with designing and conducting experiments to evaluate AI system behavior under various conditions, including adversarial attacks and edge cases.
• Experience with AI safety tools and frameworks.
• Data science experience, especially with large, distributed data frameworks (e.g., Spark or Hadoop).
• Prior experience on AI safety, responsible AI, or related topics.
• General familiarity with relevant regulations and ethical guidelines related to AI (e.g., EU AI Act).
• General familiarity with red teaming and adversarial testing of AI systems.
• Experience with technical AI safety mitigations.

We offer

• Opportunity to work on cutting-edge projects
• Work with a highly motivated and dedicated team
• Corporate social events
• 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.