Data Science Manager Jobs in Austin, TX
Data Science Manager jobs in Austin are concentrated in the Domain, Downtown, and the East Austin tech corridor, with strong demand from Apple, Amazon, and DoorDash across enterprise tech, fintech, and healthcare analytics. Demand is active year-round, driven by Austin's dense cluster of scaled tech companies and fast-growing data teams. See the openings below and apply to the ones that match your experience.
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The position of Senior Consultant - Data Science & AI is within the TTEC Digital Analytics team. The Analytics group is responsible for Data Science, Advanced Analytics, Generative AI, and Engineering projects that include the design and validation of predictive models, building scalable machine learning pipelines, engineering autonomous agentic workflows, and leveraging enterprise Gen AI (LLMs, RAG architectures) to convert raw, unstructured client data into actionable insights that drive strategic business decision-making.
Key responsibilities
- Develop Machine Learning Models: End-to-end development, training, and deployment of production-grade predictive and prescriptive models (e.g., propensity modeling, customer segmentation, demand forecasting).
- Design & Deploy Generative AI Solutions: Architect, fine-tune, and evaluate enterprise Gen AI systems—including Retrieval-Augmented Generation (RAG) pipelines, custom LLM applications, and prompt engineering frameworks—to extract insights from unstructured data.
- Architect Agentic AI Systems: Design and deploy autonomous AI agents and multi-agent workflows capable of multi-step reasoning, tool utilization, and task automation to solve complex client business challenges.
- Deliver Advanced Analytics: Help clients maximize the efficiency of their strategic initiatives by building advanced analytics models that measure campaign performance, predict customer behavior, and maximize long-term ROI.
- Data Storytelling & Visualization: Synthesize complex algorithmic outcomes and machine learning metrics into compelling, executive-ready presentations and dashboards that clearly articulate business value and ROI.
- Develop and Maintain Analytics Workflows: Analyze raw client data and build optimized analytics datasets within cloud environments to support modeling and reporting.
- Lead workshops with external clients to uncover business objectives, map out data landscapes, and translate vague business problems into structured data science methodologies.
- Create solutions and design documentation for client data science architectures and ML pipelines.
- Work on projects independently as well as being part of a large team across multiple client engagements.
- Crosstrain Junior Data Scientists/Analysts or other team members with your area of expertise, providing technical leadership and code reviews.
- Further develop skills both on the job and through formal learning channels to stay ahead of AI/ML trends.
- Assist in pre-sales activities by scoping new client opportunities and providing accurate work/effort estimates.
Skills and Experience Requirements
- Post-Secondary Degree (or Diploma) related to Data Science, Statistics, Computer Science, Economics, Business Analytics, or an IT-related field.
- 5–8 years of total experience in Data Science, Advanced Analytics, or Management Consulting.
- 3+ years of experience in an external client-facing consulting or professional services capacity.
- 3+ years of application, model design, and deployment experience natively within a cloud environment (GCP preferred).
- 1–2+ years of hands-on experience architecting and deploying Generative AI systems (e.g., RAG pipelines, fine-tuned LLMs) and Agentic AI workflows (e.g., autonomous agents, tool-use integration).
- Demonstrated experience delivering both traditional predictive models and modern AI solutions to enterprise stakeholders.
- Google Cloud Certified Professional Data Engineer, Professional Machine Learning Engineer, or equivalent Generative AI/Cloud Certifications (Highly Preferred).
- Python Stack: pandas, numpy, scikit-learn, XGBoost, PyTorch/TensorFlow, Transformers
- Generative & Agentic AI Frameworks: LangChain, LlamaIndex, AutoGen/CrewAI, Prompt Engineering, RAG architectures, Multi-Agent Orchestration, Function Calling & Tool Integration
- Vector Databases & Search: BigQuery Vector Search, Google Cloud Vector Search, Pinecone, Chroma, or FAISS
- SQL: Advanced query optimization for large-scale data warehouses
- Google Cloud Platform (Core focus): Gemini Enterprise, Vertex AI Agent Builder, BigQuery ML, Model Garden (Model development, fine-tuning, and deployment)
- Data Engineering & Orchestration: BigQuery, Dataflow, and Cloud Storage for data extraction, pipeline management, and indexing
- BI & Data Visualization Tools: Looker / Looker Studio, Tableau, or Power BI
- MarTech/AdTech Ecosystems
- Agile/Scrum Methodologies
- CI/CD & MLOps/LLMOps: Version control, automated deployment pipelines, LLM evaluation, and model monitoring tools
- Personal: Strong interpersonal skills, high energy and enthusiasm, integrity, and honesty; flexible, results-oriented, resourceful, structured problem-solving ability, deal effectively with difficult client situations, ability to prioritize.
- Leadership: Ability to gain credibility, motivate, and provide leadership; work with a diverse external customer base; maintain a positive attitude. Provide technical support and guidance to more junior team members, particularly for challenging modeling or analytical assignments.
- Operations: Commercial acumen and ability to manage multiple projects simultaneously. Perform tasks in a client-friendly manner while utilizing time and resources efficiently, proactively managing project scope.
- Technical: Ability to understand, translate, and communicate highly complex technical and mathematical concepts to non-technical business stakeholders.
This position is eligible to participate in an annual incentive program. Actual compensation offered to a candidate may vary based upon geographic location, work experience, education and/or skill levels.
- Medical, dental, vision
- tax-advantaged health care accounts
- financial and income protection benefits
- paid time off (PTO) and wellness time off.
We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.
See All 46 Data Science Manager Jobs in Austin
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Find Data Science Manager JobsData Science Manager Job Market in Austin
Who's Hiring
- Apple11

- Amazon8

- DoorDash3

- Meridial3

- SentiLink3

Top Industries Hiring
- Technology & Software
- Retail
- Education
- Electronics & Hardware
- Banking & Financial Services
Data Science Manager Jobs in Austin: Frequently Asked Questions
How do I get a data science manager job in Austin?
Focus your search on Austin's enterprise tech corridor in the Domain, the fintech and payments companies downtown, and the health tech employers anchored near the medical district. Candidates with experience managing cross-functional data teams and translating model outputs into business decisions stand out locally. Attending Austin Data Science meetups and engaging with the city's active AI and analytics community also puts you in front of hiring teams before roles are posted.
Which companies hire data science managers in Austin?
Companies currently hiring data science managers in Austin include Apple, Amazon, and DoorDash, per current listings on Migrate Mate as of September 2026. Austin's market skews toward scaled tech companies, high-growth fintechs, and enterprise SaaS firms that run large internal data organizations.
Are there remote data science manager jobs in Austin?
Yes, though remote availability varies: data science manager roles are desk and analytical by nature, making them more remote-compatible than hands-on or lab-based positions. About 62% of data science manager openings tied to Austin are remote or hybrid as of September 2026, reflecting how Austin employers have adopted flexible work policies post-pandemic. Strategy, reporting, and team leadership responsibilities tend to travel well remotely, while stakeholder-facing or embedded product work more often requires in-office presence.
How can I get a data science manager job in Austin with little or no experience?
The most realistic path is moving into a lead or senior individual-contributor role at one of Austin's mid-stage tech or fintech companies, then stepping into management as the team scales. Austin employers frequently promote from within, especially at Series B and C startups in the Domain and East Austin. Building a portfolio that shows cross-functional collaboration, mentorship, and translating data work into product or revenue impact will open more doors than credentials alone.
Which industries hire the most data science managers in Austin?
The sectors hiring the most data science managers in Austin are Technology & Software, Retail, and Education, based on current listings on Migrate Mate as of September 2026. Austin's position as a hub for enterprise software, payments infrastructure, and health tech creates sustained demand for data science leaders who can operate across product, engineering, and business functions.
See All 46 Data Science Manager Jobs in Austin
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