Python/Data Science Developer

City of London
10 months ago
Applications closed

Related Jobs

View all jobs

Data Science & Prototyping Developer

Data Scientist and Developer

Data Scientist/Developer

Data Scientist/Developer

MLOps Python Engineer - SageMaker & AWS

Senior Python & MLOps Engineer — AWS SageMaker

Python - Data Science Developer

Contract Type: Contract To Perm (inside IR35 via umbrella)
Location: Canary Wharf, London (4 minutes walk from Canary Wharf train station)
Work Arrangement: Hybrid Working - 3 days onsite

Are you a passionate Python Developer with a strong background in Data Science? Do you thrive in an agile environment and want to play a pivotal role in transforming financial data into actionable insights? Our client, a leading organisation in the financial sector, is seeking an experienced Python - Data Science Developer to join their dynamic Technology team.

Key Responsibilities:

As a Data Scientist Lead, you will:

Develop and coordinate plans for analytical initiatives, ensuring alignment with business objectives.
Manage deliverables in an agile setting, maintaining clear communication with all stakeholders.
Present analytical findings, status updates, and potential issues to various audience groups, including business, technology management, and model governance.
Conduct data modelling and cleaning from both internal and external sources to ensure data integrity.
Build predictive and prescriptive models, utilising advanced techniques to manipulate and clean data results.
Develop, manage, and deploy analytical solutions using Machine Learning (ML), Deep Learning (DL), and Large Language Models (LLMs), ensuring production systems adhere to technology SDLC processes.
Implement features through the full ML lifecycle, including Development, Testing, Training, and Monitoring/Evaluation to guarantee scalability and reliability.Qualifications:

PhD or Master's degree in Computer Science, Data Science, Statistics, Mathematics, Engineering, or a related field.
A minimum of 5 years of industry experience as a Data Scientist, specialising in ML Modelling, Ranking, Recommendations, or Personalization systems.
Proven experience in designing and developing scalable machine learning systems for training, inference, monitoring, and iteration.
Strong understanding of ML/DL/LLM algorithms, model architectures, and training methodologies.
Proficient in Python, SQL, Spark, PySpark, TensorFlow, or other analytical/model-building programming languages.
Familiarity with tools and Large Language Models (LLMs).
Ability to work both independently and collaboratively within a team.Preferred Skills:

Experience in Generative AI (GenAI) and LLM projects.
Familiarity with distributed data/computing tools (e.g., Hadoop, Hive, Spark, MySQL).
Background in the financial industry, particularly in banking and risk management.
Knowledge of capital markets, financial instruments, and modelling techniques.Education:

Bachelor's degree or equivalent experience in a STEM field.

Join us in shaping the future of data science in finance!

Adecco is a disability-confident employer. It is important to us that we run an inclusive and accessible recruitment process to support candidates of all backgrounds and all abilities to apply. Adecco is committed to building a supportive environment for you to explore the next steps in your career. If you require reasonable adjustments at any stage, please let us know and we will be happy to support you

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.

How to Write an AI Job Ad That Attracts the Right People

Artificial intelligence is now embedded across almost every sector of the UK economy. From fintech and healthcare to retail, defence and climate tech, organisations are competing for AI talent at an unprecedented pace. Yet despite the volume of AI job adverts online, many employers struggle to attract the right candidates. Roles are flooded with unsuitable applications, while highly capable AI professionals scroll past adverts that feel vague, inflated or disconnected from reality. In most cases, the issue isn’t a shortage of AI talent — it’s the quality of the job advert. Writing an effective AI job ad requires more care than traditional tech hiring. AI professionals are analytical, sceptical of hype and highly selective about where they apply. A poorly written advert doesn’t just fail to convert — it actively damages your credibility. This guide explains how to write an AI job ad that attracts the right people, filters out mismatches and positions your organisation as a serious employer in the AI space.

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

If you are a software engineer, data scientist or analyst looking to move into AI or you are a UK undergraduate or postgraduate in computer science, maths, engineering or a related subject applying for AI roles, the maths can feel like the biggest barrier. Job descriptions say “strong maths” or “solid fundamentals” but rarely spell out what that means day to day. The good news is you do not need a full maths degree worth of theory to start applying. For most UK roles like Machine Learning Engineer, AI Engineer, Data Scientist, Applied Scientist, NLP Engineer or Computer Vision Engineer, the maths you actually use again & again is concentrated in a handful of topics: Linear algebra essentials Probability & statistics for uncertainty & evaluation Calculus essentials for gradients & backprop Optimisation basics for training & tuning A small amount of discrete maths for practical reasoning This guide turns vague requirements into a clear checklist, a 6-week learning plan & portfolio projects that prove you can translate maths into working code.

Neurodiversity in AI Careers: Turning Different Thinking into a Superpower

The AI industry moves quickly, breaks rules & rewards people who see the world differently. That makes it a natural home for many neurodivergent people – including those with ADHD, autism & dyslexia. If you’re neurodivergent & considering a career in artificial intelligence, you might have been told your brain is “too much”, “too scattered” or “too different” for a technical field. In reality, many of the strengths that come with ADHD, autism & dyslexia map beautifully onto AI work – from spotting patterns in data to creative problem-solving & deep focus. This guide is written for AI job seekers in the UK. We’ll explore: What neurodiversity means in an AI context How ADHD, autism & dyslexia strengths match specific AI roles Practical workplace adjustments you can ask for under UK law How to talk about your neurodivergence during applications & interviews By the end, you’ll have a clearer picture of where you might thrive in AI – & how to set yourself up for success.