Market Data Product Manager

DIGITEC

London

1 year ago

Applications closed

Related Jobs

View all jobs

Lead Data Engineer Technology (Product, Engineering, Design) · London ·

Data Science Manager

Data Science Manager Riga, Latvia

Data Science Manager London, UK

Data Analyst

Senior Data Management Professional - Data Quality - Equity Corporate Actions

Joins us as a Product Manager at our London office!Join DIGITEC’s market data team and help drive the success of ourleading SDF product! At the same time, you'll identify and developnew product opportunities to overcome growth barriers and expandDIGITEC's market data offerings. About SDF:DIGITEC, together with360T, have created a data pool with major banks, who provide FXSwaps data through the award-winning 360T platform. The Swaps DataFeed (SDF) offers a unique, independent, and reliable source of FXOTC market data for swaps, helping financial institutions make moreinformed decisions in the swaps market. Prioritize and plan newfeatures based on client insights and competitive analysis whiledriving continuous improvement to maintain the SDF's competitiveedge and operational reliability. Identify and validate new growthopportunities for the market data division, including potentialenhancements to the SDF and new product lines. Work closely withdevelopment, operations, and sales teams to ensure successfulproduct delivery. Lead discussions with key stakeholders to exploreproduct advancements and ensure effective communication aboutchanges and enhancements. Build data analysis capabilities toassess product performance and identify areas for improvement.Collaborate with Business Development to identify strategicpartnerships for market growth. Define and track KPIs for productperformance and customer satisfaction. 3+ years of productmanagement experience, ideally in fintech or market data. ~Proficient in English. ~ Relevant academic degree in BusinessAdministration, Finance, Economics, Computer Science, InformationTechnology, or a related field. ~ Ability to analyze market data tospot trends and areas for improvement. ~ Familiarity with technicalsystems and processes related to data feeds. ~ Enjoy theflexibility of working hours and a hybrid work model, where you canwork from home up to three days a week. Enjoy 30 vacation days torelax and recharge. Benefit from a performance-based bonus. Accessa yearly budget dedicated to further education and professionaldevelopment. Work from our beautiful office in Liverpool Street.Join in on our vibrant team and company events, including a summerevent and a Christmas party. Immerse yourself in ourperformance-driven culture, where excellence is celebrated, andexperience a warm and inclusive working environment. DIGITECFinancial Technologies and Services GmbH stands at the forefront ofthe financial technology sector, renowned for developingcutting-edge software solutions. Our innovative products encompassa wide spectrum, from pricing and settlement solutions for FX/MMbusinesses to FX market data services. With over 40 prominent banksworldwide, spanning Europe, America, Asia, and Australia, among ouresteemed clientele, we have solidified our position as a globalleader.At the heart of our success is our exceptional team,comprised of approximately 60 dedicated professionals boastingexpertise in software development, financial mathematics, sales, ITsystems, and more. Join us as we continue to redefine the landscapeof financial technology with DIGITEC.

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

Industry Insights

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

Jan 18, 2026

Careers Jobs

Data Science Jobs for Career Switchers in Their 30s, 40s & 50s (UK Reality Check)

Thinking about switching into data science in your 30s, 40s or 50s? You’re far from alone. Across the UK, businesses are investing in data science talent to turn data into insight, support better decisions and unlock competitive advantage. But with all the hype about machine learning, Python, AI and data unicorns, it can be hard to separate real opportunities from noise. This article gives you a practical, UK-focused reality check on data science careers for mid-life career switchers — what roles really exist, what skills employers really hire for, how long retraining typically takes, what UK recruiters actually look for and how to craft a compelling career pivot story. Whether you come from finance, marketing, operations, research, project management or another field entirely, there are meaningful pathways into data science — and age itself is not the barrier many people fear.

Jan 13, 2026

Jobs

How to Write a Data Science Job Ad That Attracts the Right People

Data science plays a critical role in how organisations across the UK make decisions, build products and gain competitive advantage. From forecasting and personalisation to risk modelling and experimentation, data scientists help translate data into insight and action. Yet many employers struggle to attract the right data science candidates. Job adverts often generate high volumes of applications, but few applicants have the mix of analytical skill, business understanding and communication ability the role actually requires. At the same time, experienced data scientists skip over adverts that feel vague, inflated or misaligned with real data science work. In most cases, the issue is not a lack of talent — it is the quality and clarity of the job advert. Data scientists are analytical, sceptical of hype and highly selective. A poorly written job ad signals unclear expectations and immature data practices. A well-written one signals credibility, focus and serious intent. This guide explains how to write a data science job ad that attracts the right people, improves applicant quality and positions your organisation as a strong data employer.

Jan 6, 2026

Education Jobs

Maths for Data Science Jobs: The Only Topics You Actually Need (& How to Learn Them)

If you are applying for data science jobs in the UK, the maths can feel like a moving target. Job descriptions say “strong statistical knowledge” or “solid ML fundamentals” but they rarely tell you which topics you will actually use day to day. Here’s the truth: most UK data science roles do not require advanced pure maths. What they do require is confidence with a tight set of practical topics that come up repeatedly in modelling, experimentation, forecasting, evaluation, stakeholder comms & decision-making. This guide focuses on the only maths most data scientists keep using: Statistics for decision making (confidence intervals, hypothesis tests, power, uncertainty) Probability for real-world data (base rates, noise, sampling, Bayesian intuition) Linear algebra essentials (vectors, matrices, projections, PCA intuition) Calculus & gradients (enough to understand optimisation & backprop) Optimisation & model evaluation (loss functions, cross-validation, metrics, thresholds) You’ll also get a 6-week plan, portfolio projects & a resources section you can follow without getting pulled into unnecessary theory.