Top Software Data Science Jobs

As a Staff Data Scientist, you will analyze large-scale broadband data, develop and validate ML models, and integrate solutions into Calix Cloud, collaborating with teams for enhanced network intelligence and subscriber experience.

Lead end-to-end data science for aviation supply chain and operational data: integrate disparate sources, perform quality assessments, build predictive and statistical models (classification, regression, time series), document algorithms, and communicate results to stakeholders.

The Director of Data Science will lead data-driven initiatives for autonomous vehicle services, overseeing ML evaluations, analytics, and strategic data science objectives. They will manage a team, collaborate with engineering and operations, and ensure high standards in data measurement and experimentation.

The Data Platform Architect will lead technical efforts in designing Snowflake's data solutions for enterprise clients, collaborating with sales, presenting to executives, and integrating complex data technologies.

Lead HR-focused predictive analytics by designing and deploying ML and statistical models for attrition, workforce forecasting, and talent outcomes. Translate insights into dashboards and recommendations, advise HR on AI strategy and compliance, and deliver high-impact workforce planning projects across regulated environments.

As a Senior Data Scientist at Omnissa, you will lead the data science team to innovate AI/ML solutions, develop advanced analytics models, and collaborate on integrating machine learning into core platform features.

Lead Data Scientist responsible for creating ML-driven risk assessments and AI workflows within a SaaS security platform, ensuring effective decision-making and system reliability.

The Data Scientist will analyze claims data, develop predictive models, and work with unstructured data using R and Python in a financial services context.

As a Lead Data Scientist, you'll develop ML models, mentor junior scientists, and provide insights from telemetry data to support strategic decisions.

Design and implement quantitative behavior metrics for autonomous vehicles, build and maintain data pipelines and dashboards, analyze large-scale vehicle logs and simulation data to identify regressions, set metric thresholds to support geofence expansion, and communicate findings to technical and non-technical stakeholders.