Head of Data Science

London
5 months ago
Applications closed

Related Jobs

View all jobs

Head of Data

Head of Data & AI

Head of Data & AI

Head of CRM & Loyalty

Principal Data Scientist - NLP

Senior Software Developer

Role: Head of Data Science
Location: London (Hybrid)
Salary: £115,000-£120,000 (+bens +bonus)

83DATA are partnered with a fast growing scale-up consultancy focused on building the best AI applications for their clients across multiple industry verticals, They are currently building out their healthcare, telco and utilities domain.

They are offering a competitive salary, an attractive bonus package, and hybrid working. They are growing rapidly, and this role is vital to their further growth. You will be a significant member of the SLT, and be joining at the fore front of their continuous successes.

Responsibilities:

Collaborate hands-on with teams to solve complex problems, efficiently.
Provide visionary leadership to the analytics team, setting strategic
goals, and driving the development of innovative analytics solutions for our clients in the booming industry.
Collaborate with cross-functional teams to integrate data science and machine learning.
Work with clients and the commercial team to build and maintain a roadmap for new data products. Collaborate with product managers and stakeholders to define the technical strategy and product roadmap
Oversee the analysis of large-scale datasets, leveraging machine learning and statistical techniques to identify trends, patterns, and insights
Build and manage a high-performing team of data scientists, analysts, and consultants, fostering a collaborative and innovative work environment that encourages professional growth and excellenceRequirements:

Minimum of 8 years of experience in DS and analytics,
Experience in leadership role, successfully building dynamic, high performing teams.
Strong proficiency in statistical analysis, machine learning, data mining, and predictive modelling techniques.
Proficiency in programming languages such as Python or R is required.
In-depth understanding of the one of the relevant industry
Passion for driving technical excellence and innovation.
Advanced degree in a relevant field. If you are interested and qualified for this role, please click apply and submit your most up-to-date CV

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.

Careers

Tips for Staying Inspired: How Machine Learning Pros Fuel Creativity and Innovation

Machine learning (ML) continues to reshape industries—from personalised e-commerce recommendations and autonomous vehicles to advanced healthcare diagnostics and predictive maintenance in manufacturing. Yet behind every revolutionary model lies a challenging and sometimes repetitive process: data cleaning, hyperparameter tuning, infrastructure management, stakeholder communications, and constant performance monitoring. It’s no wonder many ML professionals can experience creative fatigue or get stuck in the daily grind. So, how do machine learning experts keep their spark alive and continually generate fresh ideas? Below, you’ll find ten actionable strategies that successful ML engineers, data scientists, and research scientists use to stay innovative and push boundaries. Whether you’re an experienced practitioner or just breaking into the field, these tips can help you fuel creativity and discover new angles for solving complex problems.

Careers

Top 10 Machine Learning Career Myths Debunked: Key Facts for Aspiring Professionals

Machine learning (ML) has become one of the hottest fields in technology—touching everything from recommendation engines and self-driving cars to language translation and healthcare diagnostics. The immense potential of ML, combined with attractive compensation packages and high-profile success stories, has spurred countless professionals and students to explore this career path. Yet, despite the boom in demand and innovation, machine learning is not exempt from myths and misconceptions. At MachineLearningJobs.co.uk, we’ve had front-row seats to the real-life career journeys and hiring needs in this field. We see, time and again, that outdated assumptions—like needing a PhD from a top university or that ML is purely about deep neural networks—can mislead new entrants and even deter seasoned professionals from making a successful transition. If you’re curious about a career in machine learning or looking to take your existing ML expertise to the next level, this article is for you. Below, we debunk 10 of the most persistent myths about machine learning careers and offer a clear-eyed view of the essential skills, opportunities, and realistic paths forward. By the end, you’ll be better equipped to make informed decisions about your future in this dynamic and rewarding domain.

Careers

Global vs. Local: Comparing the UK Machine Learning Job Market to International Landscapes

How to evaluate opportunities, salaries, and work culture in machine learning across the UK, the US, Europe, and Asia Machine learning (ML) has rapidly transcended the research labs of academia to become a foundational pillar of modern technology. From recommendation engines and autonomous vehicles to fraud detection and personalised healthcare, machine learning techniques are increasingly ubiquitous, transforming how organisations operate. This surge in applications has fuelled an extraordinary global demand for ML professionals—data scientists, ML engineers, research scientists, and more. In this article, we’ll examine how the UK machine learning job market compares to prominent international hubs, including the United States, Europe, and Asia. We’ll explore hiring trends, salary ranges, workplace cultures, and the nuances of remote and overseas roles. Whether you’re a fresh graduate aiming to break into the field, a software engineer with an ML specialisation, or a seasoned professional seeking your next challenge, understanding the global ML landscape is essential for making an informed career move. By the end of this overview, you’ll be equipped with insights into which regions offer the best blend of salaries, work-life balance, and cutting-edge projects—plus practical tips on how to succeed in a domain that’s constantly evolving. Let’s dive in.

🍪 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.