Data Scientist/ML Engineer

Snaphunt
1 year ago
Applications closed

Related Jobs

View all jobs

London Data Scientist & ML Engineer | AWS, Python

Data Scientist - ML for Risk & Pricing (Hybrid)

Consumer Lending Data Scientist

DV-Cleared Data Scientist: ML & MLOps in Secure Env

Data Scientist — ML & Feature Engineering (Hybrid)

Data Scientist

The Offer

  • Work within a company with a solid track record of success
  • Leadership Role
  • Flexible working options

The Job

You will be responsible for :

  • Developing scripts to process structured and unstructured data.
  • Recommending, developing and implementing ways to improve data reliability, efficiency and quality.
  • Supporting translation of data business needs into technical system requirements.
  • Working with stakeholders to understand needs in order with respect to data structure, availability, scalability and accessibility.
  • Defining, developing and maintaining reports to support decision making.
  • Processing & Interpreting data to get actionable insights.
  • Working closely with business users to understand their data analysis needs/requirements.
  • Developing high-quality code to build and deploy machine learning models.
  • Identifying trends, doing follow-up analysis, preparing visualizations.

The Profile

  • You possess a degree in Computer Science, Applied Mathematics, Engineering or related field.
  • You have at least 3 years experience, ideally within a Data Analyst or Data Engineer role.
  • Demonstrated experience working with large and complex data sets as well as experience analyzing volumes of data.
  • You have good presentation and communication skills and the ability to present you findings clearly and accessibly in the form of reports and presentations to senior colleagues.
  • You have working knowledge of Artificial intelligence
  • You are highly goal driven and work well in fast paced environments
  • You possess strong analytical skills and are comfortable dealing with numerical data
  • You enjoy finding creative solutions to problems

The Employer

Our client is a progressive and flourishing prop trading firm, and trading education provider. Our client is based in London, and at the moment have a team of highly trained properly trading professionals, managing the company’s extensive funds on our City of London based trading floor.

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

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

Industry Insights

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

What Hiring Managers Look for First in Machine Learning Job Applications (UK Guide)

Whether you’re applying for machine learning engineer, applied scientist, research scientist, ML Ops or data scientist roles, hiring managers scan applications quickly — often making decisions before they’ve read beyond the top third of your CV. In the competitive UK market, it’s not enough to list skills. You must send clear signals of relevance, delivery, impact, reasoning and readiness for production — and do it within the first few lines of your CV or portfolio. This guide walks you through exactly what hiring managers look for first in machine learning applications, how they evaluate CVs and portfolios, and what you can do to improve your chances of getting shortlisted at every stage — from your CV and LinkedIn profile to your cover letter and project portfolio.

MLOps Jobs in the UK: The Complete Career Guide for Machine Learning Professionals

Machine learning has moved from experimentation to production at scale. As a result, MLOps jobs have become some of the most in-demand and best-paid roles in the UK tech market. For job seekers with experience in machine learning, data science, software engineering or cloud infrastructure, MLOps represents a powerful career pivot or progression. This guide is designed to help you understand what MLOps roles involve, which skills employers are hiring for, how to transition into MLOps, salary expectations in the UK, and how to land your next role using specialist platforms like MachineLearningJobs.co.uk.

The Skills Gap in Machine Learning Jobs: What Universities Aren’t Teaching

Machine learning has moved from academic research into the core of modern business. From recommendation engines and fraud detection to medical imaging, autonomous systems and language models, machine learning now underpins many of the UK’s most critical technologies. Universities have responded quickly. Machine learning modules are now standard in computer science degrees, specialist MSc programmes have proliferated, and online courses promise to fast-track careers in the field. And yet, despite this growth in education, UK employers consistently report the same problem: Many candidates with machine learning qualifications are not job-ready. Roles remain open for months. Interview processes filter out large numbers of applicants. Graduates with strong theoretical knowledge struggle when faced with practical tasks. The issue is not intelligence or effort. It is a persistent skills gap between university-level machine learning education and real-world machine learning jobs. This article explores that gap in depth: what universities teach well, what they routinely miss, why the gap exists, what employers actually want, and how jobseekers can bridge the divide to build successful careers in machine learning.