Senior Director, Data Science

Terex
Dungannon
1 month ago
Applications closed

Related Jobs

View all jobs

Senior Product Director, Data, Martech & Experimentation (Viator)

Senior Data Scientist

Senior Data Scientist

Director - AI Strategy & Enablement

Senior Credit Risk Analyst - Consumer Lending / Loans

Senior Credit Risk Analyst (Lead) - Consumer Lending

Description

:

Title: Sr Director, Data Science

Reports to: VP, IT Platforms and Applications

Location: UK

Position Overview:

The Senior Director, Data Science is responsible for leading the data science strategy and associated technology initiatives across the enterprise.

This is a great opportunity to play a significant role in digital transformation at Terex by overseeing the architecture of data pipelines and platforms to ensure performance, scalability, and security, and leading the development and deployment of scalable AI models, predictive analytics, and machine learning solutions. The successful candidate will have a strong background in data science, leadership capabilities, and a passion for leveraging data to drive business decisions, improve customer experiences, and enhance operational efficiencies.

Key Responsibilities:

Strategy: Develop and implement the data science strategy in alignment with our digital transformation goals. Identify and prioritize data initiatives that drive innovation and competitive advantage. Stay abreast of industry trends, emerging technologies, and best practices to inform strategic planning.

Leadership: Lead, mentor, and develop teams fostering a culture of collaboration and continuous improvement. Provide direction and support to ensure the successful execution of digital transformation initiatives.

Digital Transformation: Drive digital transformation initiatives by leveraging advanced data science capabilities, machine learning, and AI to optimize business processes and enhance customer experiences.

Advanced Analytics & Data-Driven Insights: Utilize advanced analytics to generate actionable insights, support decision-making, and identify opportunities for business growth. Develop and deploy predictive models to support various business functions.

Data Governance: Establish and maintain data governance policies and procedures to ensure data quality, security, and compliance. Oversee data management practices, including data collection, storage, and analysis.

Collaboration: Work closely with cross-functional teams to integrate data science solutions across the organization.

Innovation: Stay abreast of industry trends, emerging technologies, and best practices in data science and digital transformation to continually enhance the organization's capabilities.

Project Management: Drive data science projects from inception to completion, ensuring they meet business objectives and are delivered on time and within budget.

Required Qualifications:

Bachelors or Masters degree in Data Science, Computer Science, Statistics, or a related field.

10+ years of experience in data science, with at least 5 years in a leadership role. Proven track record of driving digital transformation initiatives.

Proficiency in data warehouse platforms (e.g. AWS Redshift), business intelligence platforms (e.g. Qlik), data science tools & programming languages (e.g. Python, SQL).

Experience with AI, machine learning frameworks and integrating large language models into AI-powered applications (e.g. Palantir AIP).

Strong analytical and problem-solving skills. Ability to translate complex data into actionable insights.

Demonstrated leadership abilities with experience managing and mentoring teams.

Excellent verbal and written communication skills. Ability to effectively communicate technical concepts to non-technical stakeholders.

Experience in facilitating change, including collaboration with senior-level stakeholders.

Proven internal and external influencing skills at senior and executive management levels.

Working knowledge of data structures of various ERP, PLM, MES, CRM and eCommerce platforms.

Preferred Qualifications:

Working knowledge and previous use of strategic planning tools and execution, especially in the areas of large-scale change and business process re-engineering.

Experience in a large, complex, industrial B2B or technology company

Why Join Us

We are a global company, and our culture is defined by ourValues— Integrity, Respect, Improvement, Servant Leadership, Courage, and Citizenship. Check out this video!

Safetyis an absolute way of life. We expect all team members to prioritize safety and commit to Zero Harm.

Our top priority is creating aninclusiveenvironment where every team member feels safe, supported, and valued.

We make a positive impact by providing innovative solutions, engaging our people, and operating in asustainableway.

We arecommitted to helping team membersreach their full potential.

Throughinnovationand collaboration, our vision remains forward-looking, and we aim to be a catalyst for change, inspiring others to build a better world for generations.

We offer competitive salaries, Team Member bonus of 25%, private healthcare, car allowance, pension, life assurance, LinkedIn Learning, on site free parking, perks discount card,

For more information on why Terex is a great place to work click on the link!

Travel:

Estimated 30% travel, both domestic and international.

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

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.

Jobs

Machine Learning Leadership for Managers: Strategies to Motivate, Mentor, and Set Realistic Goals in Data-Driven Teams

Machine learning (ML) has become an indispensable force in the modern business world, influencing everything from targeted marketing campaigns to advanced medical diagnostics. As industries integrate predictive algorithms and data-driven decision-making into their core operations, the need for effective leadership in machine learning environments has never been greater. Whether you’re overseeing a small team of data scientists or spearheading an enterprise-scale ML project, your leadership style must accommodate rapid innovation, complex problem-solving, and diverse stakeholder expectations. This guide provides actionable insights into how you can motivate, mentor, and establish achievable goals for your machine learning teams—ensuring they thrive in data-driven environments.

🍪 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.