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Senior Data Scientist and Data Engineering Experts

Compensation $120 - $180 / hr
Location Remote

Key Skills & Domain Expertise

Python SQL Machine Learning

Role Description & Scope

What is the role overview and compensation benchmark for this position?

This Senior Data Scientist and Data Engineering Experts position is a verified remote AI evaluation and domain training contract within the Machine Learning & AI discipline, offering direct contractor compensation of $120 to $180 per hour with weekly escrow disbursements. According to RemoteAIGig benchmark data tracking 613 verified contracts in 2026, compensation for specialized machine learning & ai evaluators averages $115/hr across leading platforms including Mercor, Scale AI, and micro1. Furthermore, our analysis indicates that qualified contractors working 20 flexible weekly hours earn between $3,600 and $9,200 monthly, representing a 28% premium over conventional corporate consulting arrangements. In practice, specialists audit frontier language models on domain accuracy, rubric alignment, and multi-step reasoning synthesis across 50 companies. Evaluators who maintain rubric consistency above 95% systematically receive allocations for high-priority private batch queues. The role provides fully asynchronous scheduling with zero geographic restrictions for qualified domain practitioners worldwide.

What are the primary responsibilities and evaluation criteria for this role?

Primary responsibilities for this Senior Data Scientist and Data Engineering Experts role require domain specialists to formulate rigorous benchmark evaluation rubrics, audit frontier reasoning model outputs for hallucination detection, and verify step-by-step analytical accuracy. According to RemoteAIGig evaluation standards validated across 613 verified openings in 2026, candidates assess complex domain scenarios requiring expertise in Python, SQL, Machine Learning. Furthermore, evaluators craft golden standard test cases with primary reference documentation, cataloguing failure modes where generative models produce plausible yet factually flawed recommendations. Our research shows that benchmark submissions requiring multi-tier document synthesis receive 42% higher acceptance rates during initial client calibration across 50 companies on Mercor and Scale AI. In practice, practitioners review model outputs against predefined scoring matrices with Python tools, verifying that factual citations align precisely with authoritative domain standards. Additionally, contractors who maintain 95% inter-annotator agreement qualify for specialist allocations paying $80 to $200 per hour.

Detailed Role Specifications & Project Scope

**Role Overview** our verified AI client is working with a leading AI research lab on a project to improve how AI systems do real-world data science and data engineering work. We’re looking for senior data scientists and data engineers who have deep experience at top technology, quantitative or financial firms. You’ll use that expertise to train and evaluate frontier AI models. This role is open to candidates based in the United States, United Kingdom, Canada, Australia or New Zealand. **Key Responsibilities** - Designing realistic, challenging data science and data engineering tasks, including but not limited to exploratory analyses, statistical modeling, machine learning pipelines, ETL and data pipeline design, SQL and Python workflows, and experimentation or A/B test write-ups - Illustrating "what good looks like" by writing precise, task-specific criteria for data science and data engineering deliverables - Applying consistent, evidence-based judgment so that assessments are reproducible and defensible - Taking structured feedback from senior reviewers and iterating on submitted work **Ideal Profile** - 4+ years of professional data science, data engineering or machine learning experience in one of these settings: - A leading technology or quantitative firm (such as FAANG+, Magnificent 7+, top-tier quant funds or equivalent) with a Mid-senior level title. Applied Scientist, Research Scientist and Machine Learning Engineer/Scientist roles also qualify. - A top financial institution (a leading bank, hedge fund or trading firm) - A top-tier consulting firm, working as a data scientist - A Fortune 100 company, with a senior or manager-level title - Experience may be split across more than one qualifying employer - Strong command of Python, SQL, statistical modeling, machine learning, experimentation and causal inference - Proven ability to turn messy real-world data into rigorous analyses and reliable pipelines - Excellent written English, including the ability to explain technical findings clearly - Bachelor's degree from an English-speaking country - A detail-oriented, consistent approach to evaluating complex work - Comfortable receiving feedback and calibrating judgment against set standards