Mid-Level Data Scientists Needed |Financial Services | Guildford Area

Guildford
9 months ago
Applications closed

Related Jobs

View all jobs

Data Analyst Placement Programme

Data Analyst Placement Programme

Data Analyst Placement Programme

Data Analyst Placement Programme

Data Analyst Placement Programme

Data Engineer

Mid-Level Data Scientists Needed |Financial Services | Guildford Area

Are you a passionate data scientist with a knack for engineering solutions? Our established financial services client is seeking a talented Mid-Level Data Scientist to join their growing Analytics team at their office near Guildford.

About the Role:

Working in a Data Science role you will also perform some Data Engineering and Analysis tasks. You'll help transform complex financial data into actionable insights that drive business decisions. You'll collaborate with cross-functional teams to develop predictive models using a range of Data Science techniques. They are also planning to implement some Generative AI tools that optimize internal operations. They are still early in their Data Science journey and this will be area they are investing over the next few years so need people who can help shame their Data and AI tools.

Responsibilities:

  • Design, develop and implement predictive models and machine learning algorithms including building Gen-AI tools.

  • Build and maintain data pipelines to support analytical workflows

  • Transform raw financial data into structured formats suitable for analysis

  • Create visualizations and reports to communicate findings to stakeholders

  • Collaborate with business teams to understand requirements and deliver solutions

  • Optimize existing models and processes for improved performance

    Requirements:

  • 3+ years of experience in data science using a range of predictive modelling and Machine Learning techniques

  • Strong programming skills in Python and SQL

  • Experience with data engineering concepts and tools (ETL pipelines, data warehousing – they are using SnowFlake)

  • Knowledge of machine learning libraries and frameworks (e.g., scikit-learn, TensorFlow)

  • Bachelor's degree in Computer Science, Statistics, Mathematics, or related field

    Technical Skills:

  • Data manipulation: Pandas, NumPy

  • Data engineering: Snowflake, Apache Spark, Airflow or similar

  • Database management: SQL, NoSQL databases

  • Visualization: Power BI, Tableau, or equivalent

  • Version control: Git

    Salary: £45,000 - £65,000 DOE + good pension contribution + private medical + 25 days holiday + discretionary bonus

    Join their team and help shape business success through data-driven decision making.

    Location: Guildford area, Surrey Work Model: Hybrid (3 days in office, 2 days remote)

    APPLY TODAY for immediate consideration and interview in the next week

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.