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Cloud • Computer Vision • Information Technology • Sales • Security • Cybersecurity
Design and train LLMs and agentic systems for cybersecurity using RLHF/RLAIF and supervised fine-tuning. Build agent architectures, tooling, retrieval/memory, and evaluation pipelines with rigorous statistical benchmarking. Optimize prompts and inference, collaborate with engineers to productionize prototypes, and drive research on agent planning, safety, and reliability.
Top Skills:
DeepspeedDpoFsdpGpusGrpoHugging Face TransformersLlmsPeftPpoPythonPyTorchReward ModelingRlaifRlhfSglangTgiTrlVllm
Artificial Intelligence • Professional Services • Business Intelligence • Consulting • Cybersecurity • Generative AI
Lead design and delivery of AI/GenAI solutions: build and deploy scalable ML models, manage data pipelines and infrastructure, mentor teams, ensure data quality and compliance, and collaborate with stakeholders to drive AI-driven business outcomes.
Top Skills:
AWSDatabricksDeep LearningGCPJavaMachine Learning LibrariesAzureNatural Language ProcessingNeural NetworksPythonSnowflake
Healthtech • Payments • Software
The Data Scientist 1 role involves cleaning and analyzing complex datasets, developing statistical models, and communicating insights through data visualizations. Responsibilities include collaborating with teams, maintaining data quality, and keeping up with advancements in the field.
Top Skills:
AWSAzureGCPMatplotlibPower BIPythonRSeabornSparkSQLTableau
About the Role:
Health-E Commerce is seeking a Data Scientist to help shape the future of our modern data ecosystem. As a critical member of our centralized Data & Analytics team, you will be our primary expert in statistical modeling, machine learning, and AI applications built on top of our proprietary data platform leveraging unique first-party data.
Reporting directly to the SVP of Data Science & Analytics, you will play a critical role in building out our key Data Science assets that are direct contributors to revenue, ranging from marketing measurement and optimization, site optimization and personalization, and forecasting. As one of the founding members of the Data Science team, you will work cross-functionally across marketing, finance, merchandising, and product.
What You'll Do:
- Statistical Modeling: Design and implement advanced statistical models for applications such as demand forecasting, regression analysis, and probabilistic sampling to solve real-world business challenges.
- Machine Learning: Own the end-to-end ML lifecycle—feature engineering, model training, hyperparameter tuning, and deployment. Work with supervised, unsupervised, and ensemble methods to optimize performance across marketing, personalization, and operational use cases.
- AI Applications: Explore and implement cutting-edge AI techniques (e.g., NLP, recommendation systems, generative models) for exploratory work in GenAI.
- Data Modeling & Visualization: Collaborate with Data Engineering to ensure robust data pipelines for feature engineering and modeling. Partner with Analytics to deliver interactive dashboards and visualizations that integrate seamlessly with existing tools.
- Business Insights: Translate complex technical outputs into actionable insights for stakeholders. Frame ambiguous business problems into testable hypotheses and communicate findings in clear, non-technical language without losing nuance.
- Innovation & Thought Leadership: Stay ahead of industry trends in ML/AI and proactively identify opportunities to apply emerging technologies to Health-E Commerce’s ecosystem.
- Minimum of 4+ years of experience in data science, statistical modeling, machine learning, AI or related experience.
- Strong Python and SQL experience ; experience with ML frameworks (e.g., scikit-learn, TensorFlow, PyTorch).
- Hands-on experience with advanced methods such as boosted decision trees, neural networks, clustering, and stochastic simulation.
- Experience with various cloud data platforms working with data at scale and as part of end-to-end pipelines (e.g., Snowflake, Databricks, Azure Synapse, BigQuery, Microsoft Fabric).
- Experience deploying ML models into production, including MLOps and model maintenance.
- Proficiency in data visualization in at least one popular platform (Tableau, PowerBI, etc.)
- Experience working as part of an end-to-end data team, with proven ability to collaborate across technical teams in data engineering, product, analytics, and technology.
- Strong experience working in agile methodologies and using tools like Jira.
- Proven ability to translate business needs into technical requirements and to explain technical models into actionable insights. Exceptional communication and stakeholder management skills.
- Strong ability to translate ambiguous problems and translate into clear problem statements.
- Experience in e-commerce, marketing, or digital health is highly desirable.
- BA/BS in Computer Science, Data Science, Mathematics, Engineering, Economics or other technical function. Masters or PhD preferred.
Health-E Commerce's compensation philosophy is grounded in market data and internal equity to ensure fairness and consistency across the team. Individuals new to the company should generally expect offers to fall between the entry point and midpoint of the salary range. Our goal is to provide an offer that supports growth potential within the role and allows for future salary progression.
- Compensation: $130,000-200,000
- Discretionary Annual Bonus Eligibility: Up to 15%
- Medical, Dental, Vision, and 401K with a company match
- Dependent Care, FSA & HSA accounts
- Paid Parental & Bonding Leave
- Flexible PTO & office closure on all major holidays
- Monthly wellness & internet reimbursements
- Professional development including certification support & leadership coaching
- Mental Health resources
- 100% remote within the United States
- Must be able to work EST hours
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Austin has a diverse and thriving tech ecosystem thanks to home-grown companies like Dell and major campuses for IBM, AMD and Apple. The state’s flagship university, the University of Texas at Austin, is known for its engineering school, and the city is known for its annual South by Southwest tech and media conference. Austin’s tech scene spans many verticals, but it’s particularly known for hardware, including semiconductors, as well as AI, biotechnology and cloud computing. And its food and music scene, low taxes and favorable climate has made the city a destination for tech workers from across the country.
Key Facts About Austin Tech
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