Associate Director - Java Engineer / Technical Data Analyst - Derivatives Technology

Talensa Partners
London
2 months ago
Applications closed

Related Jobs

View all jobs

Data Scientist KTP Associate - Salford

Data Scientist KTP Associate - Salford

Data Scientist KTP Associate - Salford

Data Scientist KTP Associate - Salford

Data Scientist KTP Associate - Salford

Data Scientist KTP Associate - Salford

Associate Director - Java Engineer for Derivatives Trade Technology

  • Derivatives knowledge
  • High proficiency in Java IDE Code development
  • Strong stakeholder engagement
  • London, City - Hybrid


Working as part of the Technology Solutions team you will be responsible for code development projects to map / analyse proprietary data models and manage technical queries related to the regulatory technology models and codebase.


-Hands on coding in Java essential with Python, exposure to Domain Specific or Functional Languages, Code Generators, Build and Release best practices, Testing frameworks and using the Github repository and issue management environment.


-Working with clients on technical business analysis, mapping of proprietary data models and other technical queries relating to Trading technology and regulatory reporting use cases.


Experience & Skills required:

High Proficiency of hands on coding ability in Java / Python and has worked in data formats: (JSON, DSL, FpML), Code Editors such as (IntelliJ, PyCharm, VSCode, Eclipse)

  • Preferably Data modelling of financial products, transactions and lifecycle events
  • Proactive worker on Technical projects, able to engage stakeholders and drive work through to completion that meet deadlines.
  • Working knowledge of the financial markets: trade processing, settlements, derivatives, commodities, collateral management markets with proven technical expertise
  • Adaptable, quick learner and team player are essential skills.


Qualifications

· Bachelor’s degree in any speciality (although prefer computer science, engineering or technology related)

· Further business analysis, engineering or technology qualifications an advantage


Great opportunity to work in a highly engaged team and gain market leading experience in Derivatives Trade technology!

Competitive and Rewarding compensation package.


Get in touch or share CV to find out more....

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.

Careers

How Many Machine Learning Tools Do You Need to Know to Get a Machine Learning Job?

Machine learning is one of the most exciting and rapidly growing areas of tech. But for job seekers it can also feel like a maze of tools, frameworks and platforms. One job advert wants TensorFlow and Keras. Another mentions PyTorch, scikit-learn and Spark. A third lists Mlflow, Docker, Kubernetes and more. With so many names out there, it’s easy to fall into the trap of thinking you must learn everything just to be competitive. Here’s the honest truth most machine learning hiring managers won’t say out loud: 👉 They don’t hire you because you know every tool. They hire you because you can solve real problems with the tools you know. Tools are important — no doubt — but context, judgement and outcomes matter far more. So how many machine learning tools do you actually need to know to get a job? For most job seekers, the real number is far smaller than you think — and more logically grouped. This guide breaks down exactly what employers expect, which tools are core, which are role-specific, and how to structure your learning for real career results.

Jobs

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.

Careers Jobs

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.

🍪 We use cookies to enhance your browsing experience on our website. By continuing to use this site, you consent to the use of cookies as described in our Cookie Policy. You can review our Cookie Policy for more information.