Top Software Data Science Jobs

Leads enterprise Data Science, Business Intelligence, and Data Engineering functions. Builds scalable data architecture, semantic layers, self-service analytics, AI and machine learning capabilities, predictive models, pipelines, governance standards, and customer-focused analytics. Manages multidisciplinary technical teams, partners with business leaders, drives data adoption, and translates analytics into revenue, engagement, retention, and operational outcomes.

Drive product-led growth through rigorous analysis of onboarding, activation, adoption, retention, expansion, and monetization. Partner with Product, Engineering, Design, Marketing, and Sales to design experiments, analyze funnels and cohorts, identify behavioral signals, build metrics and dashboards, improve instrumentation, and translate uncertain or incomplete data into actionable product recommendations.

Develop and deploy AI, machine learning, statistical, and adaptive process-control models for bioprocess optimization. Analyze sensor, batch, and experimental data; improve fermentation and downstream processing productivity, yield, cost, and scalability. Collaborate with engineers and scientists to integrate data science solutions into manufacturing and R&D operations, enhance data pipelines and modeling frameworks, and communicate findings to technical and non-technical stakeholders.

Develops and optimizes NLP and machine learning pipelines for medical and claims data supporting VA disability claims adjudication. Responsibilities include extracting and analyzing healthcare data, tuning transformer-based models, validating performance, documenting workflows, collaborating with VA stakeholders, and supporting model integration into government systems. The role requires Python, NLP, SQL, healthcare data knowledge, and experience delivering data science projects in regulated environments.

Develops scalable self-service analytics, data science frameworks, predictive and causal models, experimentation strategies, semantic layers, and AI-powered analytics tools. Partners with Product, Engineering, Design, and data engineering teams to improve product adoption, engagement, retention, and monetization insights. Leads complex analytics initiatives, ensures analytical rigor and governance, communicates findings to executives, and mentors analysts and data scientists.

Evaluates and improves statistical models, machine learning algorithms, and analytic workflows supporting classified Space and Counterspace intelligence missions. Analyzes complex datasets, validates model performance, assesses data quality, recommends enhancements, integrates new analytic approaches, and prepares technical assessments for government stakeholders. The role collaborates with engineers, developers, and data science teams in a classified environment while ensuring security and data governance compliance.

Lead end-to-end development and deployment of predictive models, conduct advanced data-driven research, and solve ambiguous business problems. Partner with senior stakeholders and engineering leaders to shape strategic planning, resource allocation, and product innovation. Communicate complex findings to technical and executive audiences, architect scalable analytical solutions, mentor data scientists, and establish high standards for data science practices.

Lead product-focused data science and machine learning initiatives, including exploratory analysis, production model development, evaluation frameworks, generative AI, graph-based machine learning, recommendation systems, and personalization. Collaborate with engineering, product, and business teams to deliver high-impact solutions, influence strategy, and communicate insights to technical and non-technical stakeholders. The hybrid role requires four days per week in the Greater Boston area.

Lead advanced data science for Unity’s advertising business, analyzing revenue, supply, demand, and customer behavior. Define metrics, evaluate ML and product initiatives, guide roadmaps, and turn large-scale data into executive-level recommendations. Partner with Product, Engineering, Sales, and Finance, while mentoring data scientists and providing technical leadership without formal management authority.

Lead the Data Science function for an AI video product, setting priorities, guiding data scientists, analysts, and engineers, and solving high-impact analytical problems. Drive product, growth, experimentation, retention, monetization, and data-quality initiatives. Build reusable metrics, datasets, self-service tools, AI evaluation systems, and agentic analytics capabilities while partnering with Product, Growth, Finance, Engineering, and AI teams.