Senior Data Scientist: AI-Driven Data Strategy

Precision Labs; United States; Hybrid; USD 120,000 - 180,000; Full time

Job summary

Deepgram is seeking a Data Scientist to work at the intersection of research and data, focusing on conversational data and model improvement. You will collaborate with research, engineering, and data teams to build systems that scale data experimentation and benchmarking.

The role emphasizes hands-on data work, active learning loops, and human-in-the-loop workflows, with a strong focus on real-world speech data and model quality.

Qualifications

• Hands-on work on real data pipelines and model-facing problems in data science, ML, or applied research.
• Strong Python and data tooling; comfort building analysis, scoring, and automation yourself.
• Experience with data characterization, data selection, active learning, or similar "what should we work on next" problems.
• Working familiarity with speech/audio or NLP models — you can reason about model output quality, confidence, and error modes.
• A track record of turning ambiguous, messy data situations into measurable model or product improvements.
• You build systems others run without you in the room — a reusable harness, not a one-off notebook.
• Strong communication skills, especially translating complex findings for audiences who don't share your background.
• An active AI-tool user. Not aspirational — tell us what you use and what you've built with it.

Responsibilities

• Understand and characterize our data.
• Design and build active-learning loops.
• Think deeply about how to best leverage humans in the loop.
• Make representative benchmarking possible.
• Change our minds about what data strategies actually work.
• Care about data consistency, cleanliness, and organization — and about making data legible and accessible to non-technical teams.

Skills

Python

Data tooling

Active learning

Model evaluation

NLP/ASR

Communication

Automation

Job description

Deepgram is seeking a Data Scientist to work at the intersection of research and data, focusing on conversational data and model improvement. You will collaborate with research, engineering, and data teams to build systems that scale data experimentation and benchmarking.

The role emphasizes hands-on data work, active learning loops, and human-in-the-loop workflows, with a strong focus on real-world speech data and model quality.