Data Scientist ...

Sneak Peek Tech
London
1 week ago
Applications closed

Related Jobs

View all jobs

Data Scientist

Data Scientist

Data Scientist

Data Scientist

Data Scientist

Data Scientist

We are looking for a junior or medior data scienceengineer to complement our data science team working with many ofour industrial customers from various sectors, including (petro-)chemical, paper and pulp, automotive, metallurgy, telecom andfood-and beverage. You will use various ML / AI / data sciencelibraries and work on a variety of applications. You will get touse various state of the art technologies including Elastic, Kafka,Kubernetes and Luigi. Finally, you will have the opportunity tolook behind the scenes of many domains and data. What are yourresponsibilities? You will typically work together with a moresenior member of the team on projects and your day job typicallyconsists of: - Help build and improve the algorithms in a scalablemanner for AI-based anomaly detection and predictive modelling. -Apply and sometimes (co-)invent and implement AI/ML algorithms forprocessing various types of data (timeseries, tabular, etc.). -Develop computer models and perform predictive and prescriptiveanalytics for various applications. - Build Proof of Concepts innotebooks, integrate these algorithms into the operational flow ofthe customer, train the users, and provide support. - Interfacewith various data sources over various connector pipelines (SQL,Elasticsearch, Kafka, REST APIs, etc.). - Tune algorithms and datapipelines for optimal performance. - Train, tune, and deployanomaly detection and predictive models on industrial or IoT data.- Knack/experience in consultancy services. Qualifications: -Previous hands-on experience in Data Science, delivering machinelearning models to production. - Bachelor's or Master's degree inData Science, Statistics, Computer Science, Mathematics, orEngineering – or equivalent. - Proficiency in Python and relevantdata science libraries (NumPy, pandas, scikit-learn, etc.). -Experience with SQL, Power BI, Git & GitHub. - Strong knowledgeof Machine Learning Algorithms and respective theory. - Ability towork within a team, collaborating effectively with colleagues. -Strong stakeholder management skills and the ability to influence.- A drive to learn new technologies and techniques. -Experience/aptitude towards research and openness to learn newtechnologies. - Experience with Azure, Spark (PySpark), andKubeflow - desirable. We pay competitive salaries based onexperience of the candidates. Along with this, you will be entitledto an award-winning range of benefits including: - Access to ourcompany car scheme or car allowance. - Free confidential 24/7 GPservice. - Hundreds of discounts (including retail, childcare +gym). - Affordable loans & enhanced pension scheme.#J-18808-Ljbffr

Get the latest insights and jobs direct. Sign up for our newsletter.

By subscribing you agree to our privacy policy and terms of service.

Industry Insights

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

Jobs

How to Write a Winning Cover Letter for Machine Learning Jobs: Proven 4-Paragraph Structure

Learn how to craft the perfect cover letter for machine learning jobs with this proven 4-paragraph structure. Ideal for entry-level candidates, career switchers, and professionals looking to advance in the machine learning sector. When applying for a machine learning job, your cover letter is a vital part of your application. Machine learning is an exciting and rapidly evolving field, and your cover letter offers the chance to demonstrate your technical expertise, passion for AI, and your ability to apply machine learning techniques to solve real-world problems. Writing a cover letter for machine learning roles may feel intimidating, but by following a clear structure, you can showcase your strengths effectively. Whether you're just entering the field, transitioning from another role, or looking to advance your career in machine learning, this article will guide you through a proven four-paragraph structure. We’ll provide practical tips and sample lines to help you create a compelling cover letter that catches the attention of hiring managers in the machine learning job market.

Jobs Careers

Veterans in Machine Learning: A Military‑to‑Civilian Pathway into AI Careers

Introduction Artificial intelligence is no longer relegated to sci‑fi films—it underpins battlefield decision‑support, fraud detection, and even supermarket logistics. The UK Government’s 2025 AI Sector Deal forecasts an additional £200 billion in GDP by 2030, with machine‑learning (ML) engineers cited as the nation’s second most in‑demand tech role (Tech Nation 2024). The Ministry of Defence’s Defence AI Strategy echoes that urgency, earmarking £1.6 billion for FY 2025–28 to embed ML into planning, logistics, and autonomous systems. If you have ever tuned a radar filter, plotted artillery trajectories, or sifted sensor data for actionable intel, you have already worked with statistical modelling—the backbone of machine learning. This guide shows UK veterans how to reframe military experience for ML roles, leverage MoD transition funding, and land high‑impact positions building the models shaping tomorrow’s defence and commercial landscapes. Quick Win: Bookmark our live board for Machine‑Learning Engineer roles to see who’s hiring today.

Jobs

Rural-Remote Machine Learning Jobs: Finding Balance Beyond the Big Cities

Over the past decade, machine learning (ML) has transformed from a niche research domain into a pervasive technology underpinning everything from recommendation systems and voice assistants to financial forecasting and autonomous vehicles. Historically, the UK’s major tech hubs—particularly London—have been magnets for top ML talent and corporate headquarters. However, remote work has become mainstream, and many ML professionals are realising they can excel in their field while living far beyond the city limits. At MachineLearningJobs.co.uk, we’ve observed a growing interest in positions that allow for a rural lifestyle or a coastal environment, often reflected in search terms like “ML remote countryside” or “tech jobs by the sea.” This surge is no coincidence. Flexible work policies, better rural broadband, and the nature of machine learning tasks—much of which can be done through cloud platforms—are bringing new opportunities to those who wish to swap urban hustle for fresh air and scenic views. Whether you’re a data scientist, ML engineer, researcher, or product manager, a rural or seaside move could reinvigorate your work-life balance. In this article, we’ll unpack why rural-remote ML jobs are on the rise, how you can navigate the challenges of leaving the city, and what you need to do to thrive in a machine learning career beyond the M25. If you’ve dreamt of looking up from your laptop to rolling fields or ocean waves, keep reading—your rural ML role might be closer than you think.

🍪 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.