Top Remote Data Science Jobs in Minneapolis, MN

Develop and deploy machine learning models for fraud detection and prevention, collaborating with teams and ensuring model performance over time.

As a Data Scientist/Machine Learning Engineer, you'll finetune models, improve data quality, add new signals, and push solutions to production.

The Data Scientist will analyze complex datasets, ensuring data correctness while developing insights and automation for investment management.

The Data Scientist will develop and optimize machine learning models, perform data analysis, and collaborate with teams in a FinTech environment.

The Staff Data Scientist will lead studies using real-world healthcare data to drive drug discovery, collaborating with cross-functional teams and generating patient-centered insights.

Seeking a Data Scientist II to develop AI systems for biomedical applications. Responsibilities include building data pipelines, optimizing AI algorithms, and collaborating with researchers to enhance biomedical research efforts.

As a Lead Data Scientist, you'll extract insights from large datasets, develop predictive models, and optimize processes while collaborating with teams.

The role involves managing data to uncover insights, developing predictive models, and bridging clients with data intelligence within the context of evolving market research methodologies.

The role involves designing and analyzing experiments for Open Connect, building experimental tooling, delivering insights, and collaborating with cross-functional teams.

As a Data Scientist at Sardine, you'll design and deploy data-driven solutions to prevent fraud, collaborating with clients and engineering teams to build and optimize machine learning models.

As a Staff Data Scientist, you will lead quantitative measurement efforts, develop causal inference methods, build ML models, and drive payment strategies via data insights.

As a Data Scientist, you'll develop predictive models and analytics tools to enhance athlete evaluation and team performance, collaborating closely with sports organizations on data-driven insights.

The Data Scientist II will enhance marketing strategies through advanced measurement frameworks, statistical models, and cross-functional collaborations to drive revenue growth for Pinterest.

As a Data Scientist, you will analyze blockchain data to derive insights, develop and deploy predictive models, and improve product offerings.

Lead the technical vision for pricing guidance algorithms at Airbnb, develop pricing strategies, and provide technical leadership to cross-functional teams.

The Staff Data Scientist will drive strategic initiatives in Reddit's ad ecosystem, develop advanced models, and collaborate across teams to optimize advertising efforts.

The Sr. Data Scientist I designs, develops, and improves data science solutions, builds machine learning models, and mentors junior team members.

The Data Scientist will develop machine learning models to optimize software build processes, analyzing large datasets and collaborating with teams for improvements.

Lead Data Scientist responsible for enhancing user experience and product efficiency through data analysis, ML modeling, and collaboration across teams. Mentors others and drives innovation in real-world applications.

Lead the sales analytics function, transforming raw data into actionable insights, mentoring analysts, and developing dashboards in Tableau.

The Sr. Data Scientist analyzes complex datasets, builds predictive models, creates data pipelines, and collaborates across teams to support strategic decision-making.

The Senior Data Scientist will develop machine learning models, collaborate with cross-functional teams, and help improve credit risk assessments to drive business growth.

The Senior Data Scientist will lead data science projects, mentor junior staff, and translate business challenges into machine learning solutions, influencing business strategy through data insights.

The Senior Data Scientist will enhance the Marketing Mix Modeling platform, develop AI tools, automate modeling processes, and provide actionable insights from complex data.

Develop and implement fraud detection models using machine learning techniques, analyze data for patterns, and optimize existing models for risk management.