Engineering Manager - Data Science Team

Femtech Insider Ltd.
City of London
4 days ago
Applications closed

Related Jobs

View all jobs

Engineering Manager - MLOps & Analytics

Engineering Manager, MLOps, Marketplace, Ecommerce, | 35 Million Users | UK Remote OR London, H[...]

Engineering Manager, MLOps, Marketplace, Ecommerce, | 35 Million Users | UK Remote OR London, H[...]

Engineering Manager, Machine Learning, Marketplace, Ecommerce, | 35 Million Users | UK Remote O[...]

Engineering Manager, Data Science – Growth & pLTV Lead

Engineering Manager - MLOps & Analytics

The Job

Looking for an experienced & collaborative Engineering Manager to lead our AdTech team. This role partners with User Acquisition & Privacy to drive data-driven decision-making, optimise ad network integrations & onboard new ones, balancing privacy compliance with business goals. You’ll lead impactful initiatives, integrating new tools like Firebase, refining existing ones (Google Tag Manager, Appsflyer) & explore innovative ways to enrich signals for better performance. You’ll drive the expansion of Promo Codes across web & mobile. Ideal candidate is a strategic thinker, strong collaborator, a privacy-conscious leader fostering team growth & delivering scalable solutions. You’ll be measured by the ability to deliver impactful projects & maintain high standards of technical excellence.


What you'll be doing

You’ll be responsible for:



  • Lead and scale a team of 5+ engineers and organise work towards the product vision
  • Work closely with the development team and Product Manager to deliver business value in a timely manner while following and improving upon established quality metrics.
  • Orchestrate technical aspects of the product development
  • Implement the most suitable development processes (principles, rules) for the team
  • Coach the team to learn and apply engineering best practices in various areas starting from UI standards and CI/CD to API design and Secure SDLC
  • Continue to form and grow your team – hire and onboard new members, perform training activities, help team members to follow their path for professional growth
  • Solve or elevate issues within and outside the team
  • Ensure healthy collaboration with other teams, identify and manage technical and organisational dependencies
  • Support an environment of transparency by providing prompt feedback, both gently and honestly

Your Experience
Must have

  • 4+ years of team management: establishing processes in a cross-functional team, building tech roadmaps, experience in change management
  • People management skills – providing one-on-ones, resolving conflicts, creating career development plans, mentoring and growing engineers
  • Extensive knowledge of engineering practices and Agile methodologies
  • Technical Proficiency: Solid understanding of both frontend and backend development practices, enabling effective guidance of a diverse engineering team.
  • AdTech Integration: Demonstrated experience in implementing and managing advertising technologies, including tools like Google Tag Manager and Appsflyer, with a focus on optimizing ad performance and data accuracy.

Nice to have

  • Privacy Compliance: Good understanding of data privacy regulations (e.g., GDPR, CCPA) and experience implementing compliant data practices.
  • Emerging Technologies: Knowledge of trends in artificial intelligence, machine learning, or augmented reality that can impact ad tech strategies
  • Communication Skills: Strong verbal and written communication skills to convey complex technical concepts to non-technical stakeholders

Ranges may vary depending on your skills, competencies and experience.


Salary Range - per year: £115,000 — £140,000 GBP


Reward

People perform better when they’re happy, paid well, looked after and supported.


On top of competitive salaries, Flo's employees have access to:



  • A flexible working environment with the opportunity to come into the office and work from home
  • Company equity grants through Flo’s Employee Share Option Plan (ESOP)
  • Paid holiday and sick leave
  • Fully paid female health and sick leave, in addition to holiday and regular sick leave
  • Workations - an opportunity to work abroad for two months a year
  • Six months paid maternity leave, and one months paid paternity leave (subject to qualifying conditions) inclusive of same-sex and adoptive parents
  • Career growth, progression, and learning development resources
  • Annual salary reviews
  • Unlimited free premium Flo subscriptions
  • A whole host of other benefits (health/pension/social schemes)

Our Culture

We’re problem solvers, we’re adaptable, we’re empathy driven and results led.


People here like working in a fast-paced, multi-national, multi-cultural and ever changing environment. Everyone has an impact on a powerful mission, and is happy to roll their sleeves up to ideate solutions and put them in place. Being part of a growing business means that sometimes it's not easy and we work hard, but our mission is always at the forefront of what we do.


Diversity, Equity and Inclusion

The strength of our workforce is in the diverse backgrounds of our employees, and Flo is committed to applying its equal opportunities policy at all stages of recruitment and selection. This means recruitment and selection of talent into Flo Health companies is only based on individual merit and qualifications directly related to professional competence. Shortlisting, interviewing, and selection will always be carried out without regard to gender identity or expression, sexual orientation, marital or civil partnership status, color, race, nationality, ethnic or national origins, religion or beliefs, ancestry, age, veteran status, mental or physical disability, medical condition, pregnancy or maternity status, trade union membership, or any other protected characteristics.


Privacy & Job Applicants

By applying for the above role, you confirm that you have reviewed our privacy notice for job applicants: https://flo.health/privacy-policy-for-job-applicants


#J-18808-Ljbffr

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.

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

Are you considering a career change into machine learning in your 30s, 40s or 50s? You’re not alone. In the UK, organisations across industries such as finance, healthcare, retail, government & technology are investing in machine learning to improve decisions, automate processes & unlock new insights. But with all the hype, it can be hard to tell which roles are real job opportunities and which are just buzzwords. This article gives you a practical, UK-focused reality check: which machine learning roles truly exist, what skills employers really hire for, how long retraining realistically takes, how to position your experience and whether age matters in your favour or not. Whether you come from analytics, engineering, operations, research, compliance or business strategy, there is a credible route into machine learning if you approach it strategically.

How to Write a Machine Learning Job Ad That Attracts the Right People

Machine learning now sits at the heart of many UK organisations, powering everything from recommendation engines and fraud detection to forecasting, automation and decision support. As adoption grows, so does demand for skilled machine learning professionals. Yet many employers struggle to attract the right candidates. Machine learning job adverts often generate high volumes of applications, but few applicants have the blend of modelling skill, engineering awareness and real-world experience the role actually requires. Meanwhile, strong machine learning engineers and scientists quietly avoid adverts that feel vague, inflated or confused. In most cases, the issue is not the talent market — it is the job advert itself. Machine learning professionals are analytical, technically rigorous and highly selective. A poorly written job ad signals unclear expectations and low ML maturity. A well-written one signals credibility, focus and a serious approach to applied machine learning. This guide explains how to write a machine learning job ad that attracts the right people, improves applicant quality and strengthens your employer brand.

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

Machine learning job adverts in the UK love vague phrases like “strong maths” or “solid fundamentals”. That can make the whole field feel gatekept especially if you are a career changer or a student who has not touched maths since A level. Here is the practical truth. For most roles on MachineLearningJobs.co.uk such as Machine Learning Engineer, Applied Scientist, Data Scientist, NLP Engineer, Computer Vision Engineer or MLOps Engineer with modelling responsibilities the maths you actually use is concentrated in four areas: Linear algebra essentials (vectors, matrices, projections, PCA intuition) Probability & statistics (uncertainty, metrics, sampling, base rates) Calculus essentials (derivatives, chain rule, gradients, backprop intuition) Basic optimisation (loss functions, gradient descent, regularisation, tuning) If you can do those four things well you can build models, debug training, evaluate properly, explain trade-offs & sound credible in interviews. This guide gives you a clear scope plus a six-week learning plan, portfolio projects & resources so you can learn with momentum rather than drowning in theory.