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Data Annotation Finance Jobs in Princeton, NJ (NOW HIRING)

Teleskope

Jr. AI Engineer - Data Annotation

New York, NY · On-site

$75K - $90K/yr

What You'll Do * Do hands-on data annotation and quality control (labeling, reviewing, and ... A beautiful, well-stocked office in NYC's Financial District. * Flexible vacation and work-from ...

YO AI Labs

AI Finance Expert - Remote

New York, NY · Remote

$93K - $116K/yr

AI Finance Domain Expert Job Type: Contractor (Part-Time) Location: Remote Job Overview We are ... Data Annotation * Problem-Solving * Independent Research * Attention to Detail Preferred ...

Meta

Sourcing Manager, Data Operations

New York, NY · Remote

$139K/yr

Within Meta's Finance organization, Strategic Sourcing owns end-to-end indirect sourcing, market ... Experience in managing high-volume data annotation sourcing programs * Demonstrated ability to ...

Meta

Sourcing Manager, Data Operations

New York, NY · On-site

$139K - $196K/yr

Within Meta's Finance organization, Strategic Sourcing owns end-to-end indirect sourcing, market ... AI data annotation and collection vendors • Proactively identify, track, and manage risks and ...

Smarsh

Lead Data Scientist

New York, NY · On-site +1

Summary As a Lead Data Scientist (NLP & Financial Compliance) at Smarsh , you will spearhead the ... Data annotation and quality review * Exploratory data analysis and model fail state analysis

Smarsh

Lead Data Scientist

New York, NY

Summary As a Lead Data Scientist (NLP & Financial Compliance) at Smarsh , you will spearhead the ... Data annotation and quality review * Exploratory data analysis and model fail state analysis

Snorkel AI

Head of Forward Deployed Engineering

New York, NY · On-site +1

$268K - $403K/yr

We work with some of the world's largest organizations to empower scientists, engineers, financial ... Bonus: experience working with data annotation workflows or internal tooling for data delivery orgs ...

Zenlaw

Data Scientist (Remote)

New York, NY · On-site +1

... Finance, Insurance, and other industries. Today, we're growing fast and excited for new teammates ... Run data analysis on our dataset to design potential rules for annotation. * Improve the ...

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All JobsData Annotation Finance JobsData Annotation Finance Jobs in Princeton, NJ

Data Annotation Finance information

See Princeton, NJ salary details

$36.7K

$89.6K

$148.9K

How much do data annotation finance jobs pay per year?

As of Aug 19, 2026, the average yearly pay for data annotation finance in Princeton, NJ is $89,584.00, according to ZipRecruiter salary data. Most workers in this role earn between $66,600.00 and $105,400.00 per year, depending on experience, location, and employer.

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Data Annotation Finance jobs near you
Infographic showing various Data Annotation Finance job openings in Princeton, NJ as of June 2026, with employment types broken down into 54% Full Time, 38% Part Time, and 8% Contract. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution, with an average salary of $89,584 per year, or $43.1 per hour.

Jr. AI Engineer - Data Annotation

Teleskope

New York, NY • On-site

$75K - $90K/yr

Full-time

Medical, Dental, Vision, Retirement, PTO

Posted 29 days ago

Job description

About Teleskope
Teleskope is redefining data security for the AI era with the only dedicated platform that combines precise visibility with automated remediation. Teleskope continuously scans, catalogs, and classifies data in-motion and at-rest while automating policy-based actions, helping organizations proactively manage data sprawl while securely enabling AI adoption.
Fresh off our $25 million Series A round, Teleskope is entering a high-growth phase backed by top-tier investors and exceptional product-market fit.
About the Role
We're looking for a hungry, hands-on AI Engineer to join our data science team. You'll do the work directly, labeling and reviewing classification data and running QC, but you won't just execute. You'll bring an engineer's mindset to it: when a task is repetitive, you script it; when quality is hard to measure, you build a way to measure it. You'll use Python, SQL, and agentic development tools to make annotation and QC faster, more consistent, and more scalable.
This is a rapidly evolving role, and we expect you to context switch comfortably as priorities shift. You'll work shoulder-to-shoulder with data scientists and ML engineers, people who think about data the way you do, and the labels and quality signals you produce feed directly into the models that protect real customers' most sensitive data. The work is high-impact and the data is messy; a big part of the job is learning, through the work itself, what it takes to make it usable.
This is a hybrid role requiring 3+ days in-office in New York City.
Who Should Apply
We're looking for someone with programming ability, dependability, and the drive to learn on the job. Recent grads are welcome, and CS and STEM backgrounds are a great fit. What matters most is that you can think critically, you're excited to work through messy data, you can context switch as priorities change, and you want to grow fast in a fast-moving environment.
What You'll Do
  • Do hands-on data annotation and quality control (labeling, reviewing, and correcting classification outputs) as a core member of the data science pipeline.
  • Take ownership of improving and scaling the process: find the bottlenecks, repetitive steps, and sources of error, and fix them with Python, SQL, and agentic workflows.
  • Build and run quality control checks that catch labeling errors, measure inter-annotator agreement, and surface systematic issues before they reach production.
  • Work closely with data scientists and ML engineers to close the loop between real-world performance and model improvement.
  • Context switch across labeling, quality analysis, scripting, and process work as priorities evolve.
  • Document QC processes and annotation guidelines to support team scaling and onboarding.
About You
  • Solid programming ability, with hands-on Python experience and a willingness to dig into scripts, SQL, and data wrangling.
  • Comfortable using agentic development tools, or eager to ramp up on them fast.
  • A quality-first mindset. You notice when something is off in the data and won't let it slide.
  • Dependable and adaptable. Teammates can count on you, and you stay effective as priorities shift.
  • Energized by messy, real-world data and by working alongside other data-minded people.
  • Hungry, self-directed, and ready to grow with Teleskope as we scale.
Nice to Have
  • Familiarity with feedback loops in ML systems and how label quality connects to model performance.
  • Experience with annotation platforms (Label Studio, Prodigy, Scale, or custom-built systems).
  • Familiarity with active learning or online learning approaches.
  • Experience with SQL and building lightweight dashboards to track quality metrics.
  • Background in NLP or text classification workflows.
What You'll Get
  • A seat alongside data scientists and ML engineers, data-minded people to learn from every day.
  • Work that visibly matters. Your labels feed the models that protect real customers' most sensitive data.
  • Ownership of the annotation and quality processes that determine classification accuracy across the platform.
  • Room to grow fast, with real ownership from day one as Teleskope scales.
  • A beautiful, well-stocked office in NYC's Financial District.
  • Flexible vacation and work-from-home days.
  • Competitive salary and meaningful equity.
  • Health, vision, dental, 401k, and more benefits, heavily subsidized by Teleskope.
What We Value
At Teleskope, we value builders who care about the details. This role is for someone who sees data quality not as a support function but as a force multiplier, and who takes pride in making the people around them more effective. We look for dependable teammates who ship iteratively, take ownership, and understand that great ML starts with great data.

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