Top Data Science Jobs in Austin, TX

Partner with Marketing to own attribution, ROI, conversion, and funnel analysis. Design experiments, surface proactive insights, optimize marketing spend, and collaborate with Data/Analytics Engineers to build data models and pipelines. Communicate findings and recommendations to non-technical stakeholders.

Embedded senior data scientist partnering with product, design, and engineering to run high-throughput experiments, define KPIs and dashboards, apply causal and behavioral analytics, surface funnel opportunities, build self-service analytics, mentor peers, and shape the analytics roadmap for discovery and conversion.

The Data Scientist will analyze user behavior, create segmentation strategies, design experiments, and track business metrics to drive growth in a SaaS company.

As a Data Scientist, you'll develop and validate machine learning models, implement AI solutions, and conduct fieldwork in support of customers.

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

Lead product analytics to inform strategy and optimize user experience: translate business questions into analysis, build reliable analytics infrastructure, run A/B tests and ML/statistical analyses, track funnels and cohorts, support 0-to-1 product launches, and communicate actionable insights to cross-functional teams.

Work with clients and engineers to audit marketing datasets, build analytics pipelines, and apply predictive models (segmentation, attribution, propensity) using SQL, Python, cloud big-data tools, and ML frameworks. Support implementations, develop analytic applications, and communicate findings to drive marketing outcomes.

As a Data Scientist at SentiLink, you'll develop fraud detection models using machine learning, engage in product development, and support analysis across teams. This role emphasizes hands-on technical work and end-to-end project ownership in a fast-paced environment.

As a Staff Data Scientist, you will develop AI conversational agents and predictive models for Finance, collaborating with cross-functional teams to drive analytics adoption and solutions in finance operations.

As a Data Scientist, you will develop algorithms, collaborate on product requirements, and communicate data-driven insights, while enhancing product offerings and delivering actionable insights.

The Sr. Data Scientist leads data-driven decision-making to enhance product development, collaborates with cross-functional teams, and champions AI-enabled reporting and data quality improvements.

Perform quantitative real estate and urban economic analysis, applying econometric and spatial methods to synthesize property, macroeconomic, and geospatial data. Build and maintain automated data pipelines, ensure data integrity, document dataflows, and prototype ML/AI methods. Collaborate with research, GIS, and engineering teams to produce reproducible insights and analytical products for stakeholders.

As a Senior Data Scientist, you will develop machine learning models, automate data pipelines, and implement AI solutions while collaborating with engineers and stakeholders to meet customer needs.

As a Senior Data Scientist, you will lead high-complexity projects, develop ML and NLP solutions, and collaborate across teams to drive business impact through statistical modeling and data analysis.

Lead and deliver end-to-end data science projects: design, build, deploy, and monitor ML/statistical models for credit risk, pricing, collections, and fraud. Partner with cross-functional teams to integrate models into production, set model development standards, mentor engineers, and maintain reliable ML pipelines and monitoring systems.

The Data Scientist will analyze complex datasets, develop predictive models, and collaborate with stakeholders to drive data-driven decisions.

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.

The Risk Data Scientist will develop adaptive decisioning models for risk assessment in financial transactions, focusing on fraud detection and compliance, while managing model governance and deployment in a regulated environment.

Senior individual contributor who drives product analytics, experimentation, and applied modeling. Owns growth and performance analyses, designs experiments with robust statistical evaluation, builds repeatable reporting, and partners with Product, Engineering, Operations, Clinical, and Finance to translate data into actionable product and operational decisions.

Assist senior data scientists with data collection, preprocessing, cleaning, and basic statistical analysis. Support model development, perform basic visualizations, and document processes and findings while learning and applying data science techniques.

Lead Oracle-focused healthcare data quality and analytics: validate transactional data, build standardized KPIs and dashboards, develop predictive inventory and revenue cycle models, and collaborate with clinical and finance teams to ensure compliance and optimize operations.

Build and deploy predictive and time-series models using HR and clinical data (Oracle HCM, GCP) to forecast staffing, identify flight-risk employees, analyze pay/burnout relationships, and create interactive dashboards and analyses to inform HR strategy and operational workforce decisions.

Turn multi-model signals into measurement, forecasts, and optimizations. Clean and label large datasets, extract structure with LLMs/NLP, define product-grade metrics, run experiments, build predictive models, create evals and monitors, and translate insights into product and business decisions.

Perform data cleansing, ETL, and preprocessing; analyze Retail CPG sales, inventory, and customer data; build predictive models for forecasting and segmentation; research and deploy Agentic frameworks and intelligent agents; produce visualizations and communicate insights to cross-functional stakeholders to optimize supply chain, marketing, and customer experience.

The Senior Data Scientist will build models and analyses, design experiments, integrate datasets, and leverage AI for improved workflows and insights in data science.