As a Senior Data Scientist (AI Enablement & Solutions), you'll help accelerate our internal data organization by identifying high-value problems, evaluating rapidly evolving AI/ML tools, and delivering scalable solutions that improve the efficiency and quality of our analytics output. This role is intentionally problem-first: you'll start from the business outcome, define what "good" looks like, and then determine the most pragmatic technical path—often learning and adapting new data/AI capabilities along the way as tools evolve.

You’ll be expected to make strong judgment calls in ambiguous situations, run lightweight but rigorous evaluations, and ship maintainable internal data products and workflows that are trusted by stakeholders and sustainable for the team to operate long-term.

#LI-Remote

Problem-First Solution Assessment & Technical Direction

• Partner with stakeholders to translate our needs into clear problem statements, success metrics, and constraints (accuracy, latency, governance, cost, and usability).
• Assess solution paths (build vs. buy vs. hybrid), and recommend an approach that maximizes value while remaining scalable and maintainable.

AI Tooling Adoption & Enablement

• Stay current on emerging AI/LLM capabilities and identify where they can materially improve analyst productivity, data product usability, or decision-making quality.
• Define reference patterns for safe and reliable AI-enabled analytics (prompting patterns, retrieval strategies, evaluation approaches, monitoring/observability).
• Create lightweight enablement assets (playbooks, templates, example implementations) that help the broader data team adopt new tools.

Deliver AI-Enabled Data Products

• Design and implement internal data capabilities such as self-serve analytics experiences, semantic/metric layers, AI-assisted workflows, or decision-support tooling.
• Partner with data engineering to productionize solutions: APIs, pipelines, access controls, logging/telemetry, and CI/CD practices.
• Ensure solutions are operable and maintainable: documentation, runbooks, ownership clarity, and measurable service expectations.

Quality, Reliability, and Governance

• Build guardrails that increase trust: correctness checks, permission-aware outputs, auditability, regression testing, and monitoring.
• Establish evaluation frameworks appropriate for AI-enabled systems (golden datasets, offline metrics, human review loops, ongoing quality measurement).

Traditional Data Science & Analytics

Apply statistical and machine learning techniques to guide insights or enhance internal products (forecasting, segmentation, anomaly detection, experimentation support).

• 3+ years experience in data science, analytics engineering, data engineering, or applied ML roles with a track record of delivering productionized solutions.
• "problem-first" mindset: demonstrated ability to start from an ambiguous business need, define success criteria, and deliver an end-to-end solution that partners adopt.
• Experience learning new tools/frameworks/platforms to unlock the best path forward (rather than defaulting to familiar methods).
• Hands-on ability to build and ship: SQL and Python; experience developing production workflows/services (APIs a strong plus).
• Experience working with modern data warehouses and analytics stacks (Snowflake experience a plus).
• Excellent communication and influence skills; comfortable driving alignment across technical and non-technical stakeholders.

Preferred

• Experience evaluating and implementing AI/LLM-enabled solutions (e.g., tool/platform selection, POCs, rollout, monitoring).
• Familiarity with production best practices (testing, CI/CD, observability), and building maintainable systems.
• Experience with semantic modeling / metric layers and analytics governance.

AI is embedded in our workflows, decision-making, and products. Success here requires embracing AI as an essential capability.

• You’ll bring experience using AI and AI-related technologies, ready to thrive here.

• You’ll apply AI every day to business challenges - improving efficiency, contributing solutions, and driving results for your team, our company, and our customers.

• You’ll grow with AI by staying curious about new trends and best practices, and by sharing what you learn so others can benefit too.

Total Rewards

In addition to a great compensation package, paid time off, and paid parental leave, many Avalara employees are eligible for bonuses.

Health & Wellness
Benefits vary by location but generally include private medical, life, and disability insurance.

Inclusive culture and diversity
Avalara strongly supports diversity, equity, and inclusion, and is committed to integrating them into our business practices and our organizational culture. We also have a total of 8 employee-run resource groups, each with senior leadership and exec sponsorship.

We’re defining the relationship between tax and tech.

We’ve already built an industry-leading cloud compliance platform, processing over 54 billion customer API calls and over 6.6 million tax returns a year. Our growth is real - we're a billion dollar business - and we’re not slowing down until we’ve achieved our mission - to be part of every transaction in the world.

We’re bright, innovative, and disruptive, like the orange we love to wear. It captures our quirky spirit and optimistic mindset. It shows off the culture we’ve designed, that empowers our people to win. We’ve been different from day one. Join us, and your career will be too.

We’re An Equal Opportunity Employer

Supporting diversity and inclusion is a cornerstone of our company — we don’t want people to fit into our culture, but to enrich it. All qualified candidates will receive consideration for employment without regard to race, color, creed, religion, age, gender, national orientation, disability, sexual orientation, US Veteran status, or any other factor protected by law. If you require any reasonable adjustments during the recruitment process, please let us know.