Top Hybrid Data Science Jobs

Build and deploy predictive, forecasting, pricing, promotion, and machine learning models using large-scale retail data. Apply statistical modeling, causal inference, and experimentation to support demand forecasting, inventory planning, merchandising, and supply chain decisions. Partner with Product, Engineering, Analytics, and Business teams to define requirements, evaluate model performance, and translate complex findings into actionable recommendations and production-ready solutions.

Lead and establish bet365’s US data science capability while remaining hands-on with coding, machine learning model development, deployment, and MLOps. Mentor data scientists and machine learning engineers, build production-grade AI solutions, define workflows and standards, collaborate with product and data leaders, and align with the UK data science team. Translate business problems into actionable initiatives and deliver scalable, monitored models on Google Cloud Platform.

Lead product-focused quantitative analyses and machine learning efforts to generate actionable insights, drive product decisions, and optimize features. Collaborate with cross-functional teams to design metrics, build scalable statistical solutions, create dashboards, and communicate findings while using AI tools responsibly.

Develop advanced algorithms and apply statistical, data mining, machine learning, and AI techniques to large structured and unstructured datasets. Identify trends, evaluate emerging data technologies, and communicate analytical findings to clients and ZS stakeholders. The role requires collaboration across multiple projects, strong quantitative and research skills, and proficiency with Python, SQL, Pandas, and PySpark. Client-facing work may require travel.

Support model risk governance by maintaining policies, documentation, inventories, validation plans, training, and stakeholder communications. Develop statistical programs and analytical solutions using R, Python, SQL, Hive, Spark, and cloud platforms to analyze large datasets and support credit risk and business intelligence consulting engagements.

Summer intern assisting with IT solution design and implementation, supporting cybersecurity initiatives through security protocol analysis, and collaborating with data science teams to analyze data and generate actionable insights. The role offers hands-on experience, mentorship, and professional development within Honeywell Aerospace. Candidates must remain enrolled in a relevant degree program, maintain at least a 3.0 GPA, and meet U.S. person requirements.

As a Senior Data Scientist, the role involves leveraging data analysis, experimentation, and statistical methods to influence business decisions and enhance Gusto's product performance, while mentoring team members.

The Data Scientist will analyze complex datasets, build predictive models, collaborate with stakeholders, and present insights for business decisions.

Develops and validates machine learning and statistical models for anti-money laundering, transaction monitoring, customer screening, and risk rating. The role evaluates AML data quality, integrates vendor solutions, maintains governance and regulatory documentation, leads model lifecycle quality control, and reports performance through management dashboards. It also supports AML risk assessments, audits, regulatory examinations, and cross-functional stakeholder coordination.

Apply statistical inference and experimentation to evaluate product changes, identify Growth opportunities, and guide strategy. Partner with product, engineering, and marketing leaders to define metrics, build datasets and dashboards, and communicate insights that drive business and product decisions. The role requires SQL, scripting, data transformation, and practical tradeoffs between speed and accuracy. Predictive modeling experience is preferred, as are startup and B2B SaaS backgrounds.