Top Software Data Science Jobs

Lead end-to-end data science projects, develop machine learning models, collaborate with stakeholders, mentor team members, and communicate insights effectively.

Perform data cleaning, preprocessing, integration, and quality assurance; create complex visualizations and dashboards (Tableau/Power BI); run routine data quality checks; and apply AI/ML models to analyze unstructured data to support mission-critical decision making.

As a Data Scientist, you will validate credit risk models, prepare reports, assist analysts, monitor performance, and support automated model training processes. Strong programming and statistical analysis skills are essential.

Lead Data Scientist responsible for analyzing large datasets, building data models, creating analytics features, and improving data quality for audit insights.

The Applied Scientist role involves developing quantitative models for decision-making under uncertainty, focusing on pricing, demand modeling, and risk management. Responsibilities include building and optimizing models, collaborating with engineering and product teams, and translating complex problems into actionable solutions.

As a Senior Data Scientist, you will develop predictive models, conduct EDA, collaborate cross-functionally, and drive data-driven decisions.

This role entails using statistics and machine learning to analyze complex datasets, implementing algorithms, and back-testing models. A PhD is required for this position.

Lead data science initiatives to develop and deploy AI solutions that improve business outcomes. Collaborate with cross-functional teams to analyze data, create models, and evaluate performance.

Lead a multi-skilled finance analytics team delivering data science, data engineering, BI, reporting and automation. Set technical vision, drive analytics roadmap, ensure governance, security, and operational maturity while mentoring staff and partnering with stakeholders to deliver AI-enabled finance solutions.

As a Data Science Manager, you will lead a team in developing personalized experiences through machine learning, aligning efforts with product and engineering to drive impact and innovation.