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The Data Science Growth Leader will drive business development and growth initiatives in AI and ML, develop enterprise-level data science solutions, mentor teams, and work closely with clients to translate their needs into actionable insights.
The Senior Manager, Fraud Risk Data Science will lead the Fraud Risk Data Innovation team, managing data scientists and collaborating on data science projects related to fraud detection and transaction risk. Responsibilities include ownership of predictive modeling projects, designing experiments, and communicating results across teams.
The Senior Data Science Consultant at DesignMind will lead client engagements, build machine learning systems, and mentor teams while communicating with stakeholders. Responsibilities include data modeling, statistical analysis, and delivering insights through documentation and presentations.
Faculty positions at Assistant and Associate Professor levels in computational neuroscience and neural data science at FAU's College of Engineering and Computer Science. Candidates will engage with data from brain circuits and collaborate with research communities at FAU campuses. Join a dynamic team integrating engineering and computational sciences with neuroscience research.
The Data Science Consultant will work with stakeholders to translate business challenges into technical solutions using applied mathematics and statistics. Responsibilities include developing production-ready solutions, assessing and cleaning data, selecting appropriate algorithms, training models, and creating data visualizations to support decision-making.
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Engage with senior leadership to provide analytics and insights on business performance, competitive analysis, and metric trends. Conduct exploratory data analysis to uncover insights that drive strategic decisions. Prepare and present reports and dashboards for senior-level audience. Develop and maintain operational models and data pipelines. Implement automated reporting solutions to streamline data analysis and presentation. Manage data and analysis requests from Investor Relations, Finance leadership, and executives.
As a Data Scientist at Vianai, you will develop and train machine learning applications, collaborate with diverse teams, and communicate insights effectively, requiring strong analytical and problem-solving skills backed by experience in statistical modeling and data mining.
The Senior Manager for Data Science will lead and develop machine learning capabilities within the Platform Security team at Blizzard Entertainment. Responsibilities include managing a team of data scientists, developing AI products, collaborating with engineers, and communicating complex models to both technical and non-technical stakeholders. A focus on player interactions and safety within the gaming community is crucial.
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Responsible for leading and participating in the design, development, and maintenance of software applications, focusing on cloud native solutions. Collaborate with cross-functional teams to enhance data-driven features, improve user engagement, and mentor junior engineers while maintaining high coding standards.
The Senior Software Engineer will work on developing and maintaining shared services for PlayOn's Data Science team, focusing on cloud-native software solutions and collaborating with multifunctional teams to enhance consumer engagement through data-driven features.
The Manager, Data Science will lead technology and modeling developments for marketing analytics, manage large datasets, automate processes, create data visuals, and contribute to the team's AI infrastructure while collaborating cross-functionally to optimize marketing performance.
The Data Science Senior Manager will lead the Lingo Data Science team, focusing on building next-generation Biowearables. Responsibilities include developing machine learning models, analyzing biological data, discovering trends in large data sets, conducting advanced statistical analyses, and designing signal processing algorithms.
The Senior Manager of Data Science will lead the data-science team to develop a strategic roadmap, implement advanced analytics, and oversee MLOps. Responsibilities include managing team priorities and resources, collaborating with cross-functional teams, and providing insights based on data analyses. A strong background in consumer marketing analytics, leadership experience, and technical skills in SQL, Python, or R are required.
The Data Science Senior Analyst is responsible for partnering with various teams to design, execute, and measure compliance in a financial institution. They conduct quantitative analysis, develop data displays, and drive optimization through data analysis. They also consult with business clients to determine system functional specifications and lead system change processes. Strong analytical and communication skills are required for this role.
As a Sr. Data Scientist at EverBright, you will develop machine learning and optimization solutions, evaluate solar production, ensure data quality, and work with large datasets. Strong leadership and communication skills are essential for collaborating with diverse teams and contributing effectively in an agile environment.
The Data Science Lead Analyst will evaluate generative AI applications for compliance with fair lending regulations. Responsibilities include designing and maintaining compliance programs, developing methodologies for evaluating AI applications, and collaborating across departments to address compliance issues. The role also involves statistical analysis and assisting with regulatory inquiries.
The Head of Emerging Technology & Data Science is responsible for driving advanced technology and analytics integration within Hartford Funds. This role involves leading innovation in AI and machine learning, collaborating with stakeholders to identify solutions, and maintaining a catalog of AI solution patterns. The individual will report on progress, serve as a thought leader, and represent the company in the investment community.
As a Senior NLP Data Science Researcher, you will leverage advanced Generative AI and NLP methods for healthcare projects. Your responsibilities include optimizing NLP/LLM models, developing Python-based inference pipelines, and performing data analysis. Strong technical and communication skills are essential as you interact with clients and lead scientific publications.
The Staff Data Scientist will develop and implement machine learning models to optimize Aarki's programmatic demand-side platform, collaborating with technical teams and contributing innovative solutions to enhance performance and address business challenges.
As a Staff Data Scientist, you will lead projects in lead generation models, credit risk analytics, and fraud detection. This involves applying machine learning and statistical modeling, overseeing the model lifecycle, analyzing data to drive strategic decisions, and mentoring junior data scientists while collaborating with business stakeholders.
The Integrative Data Scientist will analyze diverse chemical and biological datasets, propose hypotheses, and collaborate with various teams to inform drug discovery. The role involves utilizing integrative approaches to enhance experimentation and data-driven decision-making within Vertex Pharmaceuticals.
As a Senior Analyst in Credit Risk Management, you will analyze data to improve credit strategies and policies, develop predictive models, and present actionable insights. You'll work collaboratively with other analysts and stakeholders to enhance risk management and decision-making processes.
As a Data & Analytics Manager, you will work with post sales teams to translate business problems into analytics solutions, build dashboards and visualizations for customer success, apply data science techniques, and communicate insights non-technically. You'll also create prototype data applications to support customer engagement.
As a Data Science Consultant, you will analyze business problems, create actionable data science roadmaps, communicate methodologies to non-technical audiences, and identify appropriate data science solutions while collaborating on end-to-end solutions with digital design and engineering practices.
Manage a team of data scientists and machine learning engineers to develop AI products aimed at enhancing business performance. Translate data science outputs for wider business applications and establish data science capabilities across the organization.
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