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The Staff Data Scientist will lead advanced analytics and data science initiatives for media measurement, develop and deploy statistical models and machine learning algorithms, and collaborate with cross-functional teams to refine measurement methodologies. Responsibilities include managing projects, mentoring other data scientists and communicating results to stakeholders.
The IT Data Scientist II will design and develop scalable AI and machine learning solutions, conduct research to build predictive models, and analyze data to derive insights for business decisions. The role includes coding in SQL and Python/R, exploring data quality, building models, and integrating solutions while engaging with internal customers to fulfill AI/ML requests.
The Data Scientist will develop and implement data analytics models, engage stakeholders, and provide data-driven insights to address agency challenges related to OJP grant oversight and compliance. Responsibilities include analyzing complex data, creating data visualizations, and communicating findings effectively.
As Lead Data Scientist at CropX, you will oversee and drive the success of the data science team, develop predictive models, and collaborate with cross-functional teams on innovative data projects. You will also work with senior leadership on AI strategies and research advancements to enhance the company's agronomic platform.
The NFL Data Scientist will develop and improve machine learning and statistical models for Swish's sports betting products, analyze model performance, and collaborate with data engineering and product teams. Responsibilities include rigorous experimentation and documenting model development.
As a Senior Data Scientist on the Search Ranking Team, you will develop, validate, and deploy machine learning models that enhance product search relevance. Your work on machine learning and data analysis will influence customer interactions and purchasing decisions across various platforms. You'll collaborate with team members to optimize search results based on a multitude of factors, directly impacting millions of users' experiences.
As a Graduate Data Scientist I, you will work in teams focusing on forecasting or inventory to develop machine learning models, analyze data, and deliver data-driven solutions for clients. You'll engage in coding, model implementation, and collaborate across teams throughout the product lifecycle.
The Senior Manager, Data Science will lead the personalization analytics initiatives at Walmart, focusing on improving ecommerce personalization strategies. This involves collaborating with various teams, managing data scientists, and running A/B tests to enhance product recommendations and customer experience.
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As a Staff Data Analyst, you will lead data initiatives to maximize marketing impact, mentor team members, and provide strategic insights and recommendations. Responsibilities include overseeing the integration of data sources, analyzing marketing campaign performance, and generating reports for various stakeholders.
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As a Data Scientist II at Coinbase, you will analyze products, guide experiments, and maintain metrics to influence product development and company performance through data insights. You'll partner with various teams to ensure data-driven decision-making in a fast-paced environment.
The Sr Principal Data Scientist will leverage expertise in AI/ML and advanced analytics to create analytics products and services in digital health. Responsibilities include architecting data products, collaborating cross-functionally, defining business problems, and mentoring junior team members while promoting a culture of innovation.
The Lead Data Scientist will analyze data using advanced mathematical and statistical techniques, design experiments, construct predictive models, and extract actionable insights. Responsibilities include leading analytics projects, mentoring junior staff, and communicating findings to stakeholders.
The Senior Director of Engineering and Data Science at Fluence leads software engineering and data ops teams, focusing on developing AI-based solutions and aligning initiatives with business goals. The role involves shaping architectural decisions, optimizing performance, and fostering a culture of innovation. Collaboration with executives and mentoring team members are also key responsibilities.
The Senior Data Scientist will model complex enterprise problems using machine learning and statistical techniques to discover insights, focused on inventory and assortment optimization. Responsibilities include developing predictive models, mentoring team members, and collaborating with cross-functional teams to implement data-driven solutions.
The Graduate Data Scientist I role involves designing, researching, building, and delivering data-focused products. Responsibilities include developing ML and deep learning forecasting models, analyzing data signals, collaborating with engineers and product managers, and conducting experiments for optimizing advertising spend.
As a Data Scientist, you will develop decision systems and predictive models to drive business improvements at Progressive Leasing. Your role includes data exploration, machine learning, and optimization of business processes based on analytics. You will work with a team to innovate and enhance analytical tools, ensuring continued success in the FinTech industry.
The Data Scientist role involves collaborating with founders and executives to create custom software and machine learning solutions. Responsibilities include applying data science methods, statistics, NLP, calling machine learning APIs, and engaging in research into AI alignment. Candidates should demonstrate problem-solving and self-management skills.
As a Senior Data Engineer for the Collision Avoidance System, you will design data pipelines, develop ETL processes, maintain data quality, implement data models, and build dashboards, collaborating with various teams to enhance data availability for machine learning and ensure compliance with privacy policies.
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As a Senior Data Scientist on the Pricing team at Lyft, you'll create mathematical frameworks that influence pricing strategies, collaborate with cross-functional teams, implement algorithms in production, and drive data-driven decisions to optimize user experience and profitability.
The Principal Data Scientist will develop and operationalize AI/ML products, define requirements for analytics use cases, and collaborate with teams to drive business insights. The role involves mentoring junior data scientists and promoting data-driven decision-making while staying updated on AI/ML innovations.
The facilitator will guide small classes in Data Science courses, providing discussions, feedback, and fostering a collaborative learning environment. Responsibilities include assessment grading and connecting theoretical concepts with practical applications to empower learners.
The Performance Science Data Engineer role involves utilizing data science techniques to enhance live entertainment experiences, focusing on analyzing performance metrics and improving overall event execution. The position may collaborate cross-functionally to drive data-driven decisions and optimize audience engagement.
The Senior Data Scientist will manage and lead data science projects to improve healthcare outcomes, utilizing machine learning techniques to develop sophisticated predictive models. Responsibilities include collaborating with teams, ensuring project alignment with organizational goals, translating complex data into actionable insights, and mentoring junior data scientists.
As a Data Scientist III, you will work on Socure's Consortium Intelligence products by applying AI and machine learning to tackle fraud prevention and identity verification. Responsibilities include managing data pipelines, developing algorithms, and analyzing large datasets to uncover fraud patterns, while collaborating with engineering and product teams.
The Tennis Data Scientist will develop and enhance machine learning and statistical models for sports betting products. They will work through all model development phases, improve model performance, analyze results, and document their work for stakeholders. The role emphasizes collaboration with engineering and product teams to deploy new models effectively.
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