Syllo
via Greenhouse
Senior Data Scientist, AI Evaluation
This is the employer's own posting, not a copy on a job board.
What we know
Is it still open?
Confirmed still open
Last checked 2h ago — checked against the employer's own applicant tracking system, which is the company answering directly.
We re-read the employer's own applicant tracking system and the posting was still there. That is the company answering directly.
How old is it?
Posted 4h ago
The date the source published, not the day we noticed it (2026-09-15). Last seen at its source just now.
Is it remote?
Remote
That is the location the employer filed this posting under. Quoted as written — we do not re-word the source's own location.
Who may apply?
Not stated
The description states no restriction of its own. This is the source's own tag.
Pay
$160k–200k/yr
Read out of the job description by us, not from a structured field. Shown in the posting's own currency and period; we never convert.
Skills named in the ad
Recognised terms only, from a fixed vocabulary — this is what CV matching compares against.
Carried by 1 source
-
greenhouse employer's own board first seen 2h ago · last seen just now
The listing
About Syllo
Syllo is on a mission to transform litigation. Our product is a unified litigation platform that enables lawyers and paralegals to safely harness the power of language models and agentic AI throughout the litigation life cycle. Since going to market, we have gained a diverse group of enterprise customers, including some of the biggest law firms and corporations in the country, and we are quickly expanding. By reducing the expense of litigation industry-wide, we aim to improve access to high-quality representation and promote the alignment of legal outcomes with merit.
About the Role
We’re seeking a Senior Data Scientist to help us evaluate and improve the quality and performance of our AI systems. You’ll develop rigorous approaches to measuring system behavior, run experiments, investigate issues, and turn complex data into actionable decisions.
This is a hands-on role at the intersection of data science, engineering, and applied AI. You’ll work directly with production data and systems and partner closely with Engineering, Product, and Analytics.
Responsibilites
- AI Evaluation: Develop quantitative methods and tooling to evaluate AI system quality and performance.
- Experimentation: Design and run experiments to compare approaches, understand tradeoffs, and measure the impact of changes.
- Quality Monitoring: Build repeatable processes to identify regressions, anomalies, and changes in system performance.
- Data Analysis: Extract, transform, and analyze production data to support technical and product investigations.
- Technical Investigation: Diagnose complex issues involving data, models, and production systems, identifying root causes and potential solutions.
- Measurement & Instrumentation: Partner with Engineering to improve how system quality, reliability, and performance are measured.
- Internal Tooling: Build tools and dashboards that make system performance easier to understand and monitor.
- Communication: Clearly communicate findings, tradeoffs, and recommendations to technical and non-technical stakeholders.
Qualifications
- Master's degree in computer science, data science, machine learning, or a related field with substantial hands-on experience; or 2–4 years of relevant professional experience.
- Strong Python and SQL skills and experience working directly with production data.
- Comfortable navigating production code and data systems you did not build.
- Strong foundation in applied statistics, experimentation, and quantitative analysis.
- Practical experience working with and evaluating modern AI/ML systems.
- Experience diagnosing complex issues involving data, models, or production systems.
- Ability to turn ambiguous questions into structured investigations and clearly communicate the results.
Bonus Qualifications
- Experience building AI/ML evaluation frameworks, benchmarks, or monitoring systems.
- Experience with information retrieval, search, or large-scale information systems.
- Familiarity with modern cloud data platforms and production data infrastructure.
- Experience building internal analytics or observability tooling.
Salary Range ($160K- $200K) plus health insurance and equity.