AI Applied Data Scientist Jobs

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Take part in building a platform used by Data Scientists and Simulation Engineers to build, train and deploy Deep Physics Models. Work on a focused, stream-aligned and cross-functional team (back-end, front-end, design) that is empowered to make its implementation decisions towards meeting its objectives. Gather and leverage domain knowledge and experience from the Data Scientists and Simulation Engineers using your product.

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The role involves designing, sourcing, shaping, and evaluating input signal at scale to improve AI model learning speed, quality, and generalization across the entire training lifecycle. Responsibilities include working deeply with raw and synthetic data, designing new datasets and signal mixtures, iterating on input distributions and formats, understanding small changes in signal and their effects on training behavior, and considering the entire training stages as a dynamic and evolving system rather than as static assets. It also requires immersion, experimentation, and developing intuition through long feedback loops.

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The role involves designing, sourcing, shaping, and evaluating input signal at scale to improve the learning speed, quality, and generalization of AI models throughout the entire training lifecycle, including pre training, mid training, post training, supervised fine tuning, and reinforcement learning. Responsibilities include working deeply with raw and synthetic data, designing new datasets and signal mixtures, iterating on input distributions and formats, understanding how small changes in signal affect training behavior, thinking across all stages of training rather than in isolation, and treating data as a dynamic, evolving system rather than a static asset. The work requires immersion, experimentation, and developing intuition through long feedback loops.

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As a Senior Data Scientist at LMArena, you will explore and analyze large, complex datasets to uncover patterns, biases, and causal relationships in model behavior and system performance. You will formulate hypotheses about data quality, evaluation outcomes, and model performance, then design experiments to validate or refute them. You will build reproducible analysis pipelines using Python, Pandas, NumPy, and Spark to process and interrogate large-scale data. You will partner with ML researchers and engineers to design metrics and analyses that evaluate how models perform across domains, prompts, and tasks. Additionally, you will develop causal reasoning frameworks and statistical methods to explain model behavior beyond performance metrics. You will communicate insights clearly to both technical and non-technical partners, informing research direction and infrastructure improvements.

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The Senior Data Scientist will own Fyxer AI’s data science capabilities, setting the roadmap for key business areas like marketing and retention, implementing scalable solutions, and ensuring stakeholders use data to make confident commercial decisions. Responsibilities include building and refining predictive models on multi-channel customer and usage data to drive product and marketing decisions, collaborating with engineering, marketing, sales, and product teams to define KPIs, experiment with new algorithms, and surface actionable insights that drive impact. They will maintain data infrastructure including BigQuery, dbt, and Fivetran, ensure data quality for reporting and self-service analytics, and develop a culture of data-driven decision making by proactively suggesting improvements to tools, processes, and architecture.

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Design and implement customized AI solutions for manufacturing; analyze manufacturing data to uncover opportunities and develop AI models; collaborate with customers to understand their requirements and deliver clear, data-driven solutions; work closely with internal teams to ensure solutions are feasible, scalable, and aligned with product strategy; present findings to both technical and non-technical stakeholders.

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You will own Fyxer AI’s data science capabilities by setting the roadmap for business areas such as marketing and retention, implementing scalable solutions, and ensuring stakeholders use data for confident commercial decisions. Responsibilities include building and refining predictive models using multi-channel customer and usage data to inform product and marketing decisions; collaborating with engineering, marketing, sales, and product teams to define KPIs, experiment with new algorithms, and surface actionable insights; maintaining data infrastructure including BigQuery, dbt, and Fivetran, and ensuring data quality for reporting and analytics; and developing a culture of data-driven decision making while proactively suggesting improvements to tools, processes, and architecture.

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As a Senior Data Scientist, the role involves translating complex stakeholder queries and hypotheses into actionable analyses, experiments, and AI/ML model requirements, developing a comprehensive understanding of data lineage and sources while addressing sampling and analytical biases, overseeing the productionization of analyses and models to ensure seamless operation at scale adhering to software engineering best practices, driving targeted exploration of the data landscape to ideate and implement innovative uses of data for enhancing user engagement on products, building knowledge graph capability to support AI/ML models and agentic workflows, proactively monitoring and refining analyses and models to optimize effectiveness and efficiency while minimizing biases and operational challenges, evaluating and validating scalable methodologies for data collection and processing to ensure robustness, and communicating actionable insights to stakeholders at all Organizational levels by bridging technical concepts and business objectives.

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The Data Science Intern at Mercor will analyze data impacting ranking, hiring efficiency, candidate experience, and revenue. Responsibilities include working with real datasets, shipping insights used by product and engineering teams, and prototyping models to improve talent matching to AI companies. The intern will work closely with engineers, product managers, and leadership to design experiments, evaluate LLM-powered systems, and build data integrity and platform visibility foundations. Projects may involve defining north-star metrics and KPIs for ranking, interview analytics, and payout systems, designing and running A/B tests and quasi-experiments, building dashboards and lightweight data models for team insight self-service, instrumenting events and improving data quality and latency, prototyping models from baselines to gradient boosting, and evaluating LLM-powered agents through rubrics and human-in-the-loop experiments.

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Collaborate with Product teams to understand business objectives and challenges, translating them into data-driven insights and recommendations. Develop and implement predictive models, analytical tools, and methodologies to analyze product usage and customer behaviors. Analyze large datasets to generate actionable insights that guide the development and optimization of engagement and monetization strategies. Design and execute experiments to test hypotheses and measure the effectiveness of various features, product experiences, and strategies. Partner with cross-functional teams, including Product Management and Engineering, to integrate data-driven insights into products and services, driving continuous improvement and innovation. Present findings and recommendations to key stakeholders, including executives, to inform strategic decision-making and shape the company’s Product roadmaps. Collaborate with Data Engineers to ensure data quality, accessibility, and reliability for analysis purposes. Stay current with industry trends, emerging technologies, and best practices in data science, machine learning, and AI to drive innovation and competitiveness.