Senior Manager, Data Services Operations

Jeenie · Remote · Full-time · Reports to VP of Operations

About Jeenie

Jeenie is an AI + human interpreting platform built for the fast-paced needs of modern healthcare and trusted across industries. We connect clinicians and patients to medically-qualified interpreters in hundreds of languages, by video or audio, on any device.

About the Role 

Jeenie connects people with live human interpreters. Our Data Services team puts that same global linguist network to work for AI companies, producing high-quality speech and language data across transcription, annotation, tagging, and evaluation.

We're looking for the person who will run that operation.

You'll lead a distributed, on-demand workforce of transcribers, annotators, and reviewers, while managing a small team of project coordinators who keep the work moving every day. You'll own the full operational picture: on-time delivery, cost, capacity, and quality.

This is a hands-on leadership role in a marketplace model. Most of the people doing the work are independent contributors who choose when and how much they work. You know how to build and manage that kind of workforce — how to qualify and tier people, keep great contributors engaged, coach performance, and make tough calls when quality isn't there.

You'll also become our in-house expert on data quality. We expect you to know your way around metrics like WER, DER, and agreement rates — and to speak up when a spec, sample, or deadline doesn't make sense.

The Role

You’ll own the product strategy for Data Services: the datasets, the quality and privacy frameworks, the tooling, and the workflows required to produce and deliver them responsibly at scale. You set direction across engineering, research, and data operations, and work hand-in-hand with the partnerships team to ensure that what we build maps directly to what buyers need.

What You’ll Do

Build and lead the workforce

• Partner with Recruiting to grow our network of qualified transcribers and annotators across languages and dialects, often on short timelines.

• Support the co-design qualification tests, contributor tiers, feedback loops, and performance standards.

• Manage and develop a distributed team of project coordinators and senior reviewers across countries and time zones.

• Make sure contributors have what they need to succeed — clear guidelines, timely pay, useful feedback, and a reason to come back for the next project.

• Work with external vendor partners when we need additional language or volume capacity, and hold them to our quality standards.

Own project delivery

• Take client projects from spec to delivery: understand the requirements, estimate effort and cost, staff the work, and scale as needed.

• Monitor throughput, capacity, productivity, cost, and turnaround — and spot risks before they become missed deadlines.

• Be the operational voice in client conversations around timelines, edge cases, quality, and guideline changes.

• Re-forecast and adjust quickly when project requirements change.

Own quality

• Design and run project-level QA, including gold sets, sampling plans, reviewer calibration, and acceptance thresholds.

• Track and explain the metrics clients care about.

• Diagnose the real source of quality issues: contributor performance, unclear guidelines, poor source data, or flawed ground truth.

• Ensure annotation and transcription guidelines are clear, practical, and consistently maintained.

• Help the team continuously raise the quality bar.

Use data to make the operation better

• Build reporting that gives you a clear view of every project's throughput, cost, capacity, and contributor productivity.

• Pull and analyze your own data rather than waiting for someone else to build the report.

• Spot recurring manual work and turn it into tooling or automation opportunities for Product and Engineering.

• Bring operational insights to leadership and help shape how the business scales.

A typical week might include

• Launching a pilot in two new languages and reviewing the first scored batch.

• Digging into a sudden WER increase and discovering the real issue is audio quality, not transcription performance.

• Coaching a project coordinator through a reviewer performance issue.

• Re-forecasting a delivery after a client changes the tagging spec mid-project.

• Working with Recruiting to quickly add capacity for an unexpected project.

What we're looking for

You know this industry, and you can show us. We're much more interested in specific examples than buzzwords.

• 3+ years in AI training data operations — transcription, speech data, annotation, labeling, or data evaluation — at a data vendor, crowd platform, or AI company's in-house data team.

• 4+ years of people management, including coordinators, project managers, team leads, or similar roles. You've hired, coached, developed, and — when necessary — managed people out.

• Experience running a large marketplace or crowd workforce, ideally hundreds of contributors or more, using qualification, testing, tiers, pay, and communication rather than fixed schedules.

• Multilingual delivery experience. You've run projects across multiple languages, including languages you don't personally speak, and know how to build systems that maintain quality anyway.

• Strong command of data-quality metrics. You can explain WER and DER, understand why two vendors might report different results on the same audio, and know how to establish fair acceptance thresholds.

• A track record of shipping at scale — for example, thousands of audio hours or labeled items delivered against client specifications and deadlines.

• Strong analytical skills. You're comfortable building your own reports and analysis in advanced spreadsheets; SQL or Python is a plus.

• Clear, direct communication. You can work effectively with contributors, clients, and executives — and when you escalate something, you bring the facts, the impact, and the decision needed.

Bonus points

• Background in linguistics, translation, or localization.

• Experience with commercial or in-house annotation/transcription platforms.

• Experience with pre-annotation using ASR or LLMs.

• Experience with newer data types such as LLM evaluation, conversational data, or multimodal data.

• Automation skills with Apps Script, Python, APIs, Zapier, or similar tools.

• Experience managing international contractors.

• Fluency in a language besides English.

What to include when you apply

Your resume is great. A short note is even better. One page is plenty.

Tell us:

1. Your biggest data project: What was the data type, languages, volume, timeline, and how did you measure quality?

2. Your team: How many direct reports and contributors did you manage at peak? Across how many countries or time zones?

3. A quality problem you solved: What did the metric show, what was actually causing the problem, and what did you change?

Applications that answer these questions get read first.

The details

• Location: Remote, US-based (preferred). Eastern Time overlap preferred, with flexibility to work across US time zones based on business needs.

• Type: Full-time