Top Software Data Science Jobs

Leads advanced data science, machine learning, AI, predictive analytics, anomaly detection, and NLP solutions for Internal Audit. Develops production-ready models and analytical frameworks, supports risk identification and continuous monitoring, and partners with audit, technology, and data teams. Communicates insights to technical and business stakeholders, ensures governance and validation standards, and mentors team members. The role requires strong Python and SQL skills, large-scale data experience, and expertise in deploying and monitoring analytics solutions.

Performs data gathering, mining, processing, modeling, and customer analytics on large datasets. Applies NLP, text analysis, machine learning, and statistical methods to identify customer needs and generate business insights. Develops and optimizes algorithms, presents findings to management through data visualization, and supports requirements analysis and data-driven decision-making. The role also involves AI agent development, cloud technologies, version control, and Agile collaboration.

Leads analytics and AI strategy, delivery, governance, and platform ownership for internal auditing. Manages data scientists, develops Power BI and Snowflake solutions, oversees reporting and control monitoring, and drives automation and AI adoption. Partners with audit and business leaders to translate requirements into scalable insights, improve decision-making, and establish secure, reliable analytics practices. The role also manages stakeholder relationships, vendor partnerships, team development, and analytics transformation initiatives.

Analyze clinician platform data to identify behavioral patterns, develop product and client-facing analytics, and communicate actionable insights. The role collaborates with product managers, analysts, engineers, and other data scientists on projects spanning data ingestion, analysis, and recommendations. Responsibilities also include contributing to data team strategy and applying statistical methods, SQL, Python data libraries, visualization, and distributed data processing techniques.

Supports ECS operations reporting and analytics through statistical analysis, hypothesis testing, dashboards, clinical reporting, and AI/ML solutions. Develops scalable reporting tools, identifies operational trends and root causes, resolves complex problems, and presents findings to leadership. Partners with clinical analysts and business stakeholders to modernize analytics, improve workflows, and support strategic decision-making.

Develop and refine credit risk, pricing, and predictive models for consumer lending. Design A/B testing frameworks, analyze model performance, collaborate with strategy and operations teams, and present data-driven recommendations to senior management. The role requires statistical analysis, machine learning, Python, SQL, independent problem-solving, and effective communication across teams.

Leads the full analytics lifecycle for advertising sales, including data preparation, exploratory analysis, predictive modeling, validation, productionalization, interpretation, and recommendations. Develops scalable data-driven solutions using statistical and machine learning methods, presents findings to varied audiences, mentors junior staff, contributes to strategic direction, and manages project execution. Requires advanced programming, SQL, cloud, big-data, forecasting, optimization, and AI/ML expertise.

Develop machine learning models and scalable data-processing systems using alternative datasets for credit decisioning. Evaluate vendors and data products, engineer features, validate and monitor models, build challenger models, and guide dataset applications. Collaborate with data scientists, software engineers, and product managers while translating complex statistical insights into business outcomes. The role uses Python, AWS, Spark, H2O, and other open-source technologies across large numeric and textual datasets.

Lead data science projects from discovery through delivery, applying statistical modeling, forecasting, experimentation, and AI to optimize pricing, resource allocation, operations, and customer experiences. Build analytical workflows and AI-enabled applications using Python and SQL, collaborate with Engineering on deployment and monitoring, and communicate data-driven recommendations and trade-offs to business and technical stakeholders.

Research and develop scalable machine learning and data science solutions for Vrbo pricing and monetization. The role applies causal inference, operations research, optimization, demand estimation, and experiment design to production systems. Responsibilities include defining performance metrics, analyzing complex datasets, collaborating with scientists, engineers, product managers, and analytics teams, communicating technical plans, and validating models through A/B testing.

Embedded Data Scientist for Superhuman Mail, partnering with product, growth, engineering, and design teams to guide roadmap decisions. Responsibilities include defining product metrics, designing experiments, applying causal inference and machine learning, measuring AI feature quality, analyzing activation and retention, identifying growth and conversion drivers, and communicating insights to stakeholders. The role requires strong Python, SQL, experimentation, statistics, and cross-functional influence skills.