Actuary - AI Trainer

DataAnnotation
Liverpool
2 weeks ago
Applications closed

Related Jobs

View all jobs

Graduate Analyst

Director of Healthcare Analytics

Prinicpal Pricing Analyst - Actuarial Pricing

Data Science Manager - Insurance (Propensity models)

Data Business Analyst - Risk Rating & Pricing

Underwriting Product Manager – US Flood (for CAT modellers)

We are looking for an actuary to join our team to train AI models. You will measure the progress of these AI chatbots, evaluate their logic, and solve problems to improve the quality of each model.

In this role you will need to hold an expert level of mathematical reasoning- a completed or in progress Masters/PhD is preferred but not required. Other related fields include, but are not limited to: Statistics, Applied Math and/or Computer Science.

Benefits:
This is a full-time or part-time REMOTE position
You'll be able to choose which projects you want to work on
You can work on your own schedule
Projects are paid hourly starting at USD $40+ per hour, with bonuses on high-quality and high-volume work

Responsibilities:
Give AI chatbots diverse and complex mathematics problems and evaluate their outputs
Evaluate the quality produced by AI models for correctness and performance

Qualifications:
Fluency in English (native or bilingual level)
Detail-oriented
Proficient in data science, arithmetic, algebra, geometry, calculus, probability, statistics, and inductive/ deductive reasoning
A current, in progress, or completed Masters and/or PhD is preferred but not required

Note: Payment is made via PayPal. We will never ask for any money from you.

Job Types: Full-time, Part-time

Pay: From £30.36 per hour

Expected hours: 1 - 40 per week

Work Location: On the roadTracking.aspx?KCYdemPV80P0MH9oG2EgOhQeDEzpeRhOl

Get the latest insights and jobs direct. Sign up for our newsletter.

By subscribing you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

Machine‑Learning Jobs for Non‑Technical Professionals: Where Do You Fit In?

The Model Needs More Than Math When ChatGPT went viral and London start‑ups raised seed rounds around “foundation models,” many professionals asked, “Do I need to learn PyTorch to work in machine learning?” The answer is no. According to the Turing Institute’s UK ML Industry Survey 2024, 39 % of advertised ML roles focus on strategy, compliance, product or operations rather than writing code. As models move from proof‑of‑concept to production, demand surges for specialists who translate algorithms into business value, manage risk and drive adoption. This guide reveals the fastest‑growing non‑coding ML roles, the transferable skills you may already have, real transition stories and a 90‑day action plan—no gradient descent necessary.

Quantexa Machine‑Learning Jobs in 2025: Your Complete UK Guide to Joining the Decision‑Intelligence Revolution

Money‑laundering rings, sanctioned entities, synthetic identities—complex risks hide in plain sight inside data. Quantexa, a London‑born scale‑up now valued at US $2.2 bn (Series F, August 2024), solves that problem with contextual decision‑intelligence (DI): graph analytics, entity resolution and machine learning stitched into a single platform. Banks, insurers, telecoms and governments from HSBC to HMRC use Quantexa to spot fraud, combat financial crime and optimise customer engagement. With the launch of Quantexa AI Studio in February 2025—bringing generative AI co‑pilots and large‑scale Graph Neural Networks (GNNs) to the platform—the company is hiring at record pace. The Quantexa careers portal lists 450+ open roles worldwide, over 220 in the UK across data science, software engineering, ML Ops and client delivery. Whether you are a graduate data scientist fluent in Python, a Scala veteran who loves Spark or a solutions architect who can turn messy data into knowledge graphs, this guide explains how to land a Quantexa machine‑learning job in 2025.

Machine Learning vs. Deep Learning vs. MLOps Jobs: Which Path Should You Choose?

Machine Learning (ML) continues to transform how businesses operate, from personalised product recommendations to automated fraud detection. As ML adoption accelerates in nearly every industry—finance, healthcare, retail, automotive, and beyond—the demand for professionals with specialised ML skills is surging. Yet as you browse Machine Learning jobs on www.machinelearningjobs.co.uk, you may encounter multiple sub-disciplines, such as Deep Learning and MLOps. Each of these fields offers unique challenges, requires a distinct skill set, and can lead to a rewarding career path. So how do Machine Learning, Deep Learning, and MLOps differ? And which area best aligns with your talents and aspirations? This comprehensive guide will define each field, highlight overlaps and differences, discuss salary ranges and typical responsibilities, and explore real-world examples. By the end, you’ll have a clearer vision of which career track suits you—whether you prefer building foundational ML models, pushing the boundaries of neural network performance, or orchestrating robust ML pipelines at scale.