Director - Data Analytics

ADP
Cheadle
1 month ago
Applications closed

Related Jobs

View all jobs

Director, Quantitative Imaging or Imaging Biomarkers (London Area)

Director, Quantitative Imaging or Imaging Biomarkers (City of London)

Director, Quantitative Imaging or Imaging Biomarkers

Director, Quantitative Imaging or Imaging Biomarkers

Research Data Analytics Expert

Research Data Analytics Expert

Job Title: Director – Business Analytics
Department: ESI (Employer Services International)
Reporting to: Senior Director Service Delivery & Business Excellence


Overview

The Director – Business Analytics will play a strategic and vital role within the ESI Business Excellence and Transformation senior leadership team, reporting directly to the Senior Director Business Excellence. This high-profile position is responsible for spearheading the ESI Business Analytics strategy across the organization. The Director will harmonize resources across teams and establish a best-in-class hub for business insights to support over 10,000+ Associates within ESI, ensuring transparency, quality, and forward-looking intelligence for leadership teams. This role will create a team of data analysts and data scientists across ESI , leveraging AI and data analytics technology to provide a comprehensive view of process performance, workload, and transformation outcomes. These insights are essential for delivering significant bottom-line benefits each year and for driving new data mining capabilities in support of major transformation initiatives.


Essential Responsibilities

  • Define and execute the ESI analytics strategy, ensuring alignment with business priorities and transformation goals aligned with ESI and Corporate strategies.
  • Act as a trusted advisor to senior leaders, challenging assumptions and shaping business decisions through data-driven insights.
  • Champion a culture of data-driven decision-making across the organization, embedding data literacy and adoption.
  • Lead the development of BI solutions, dashboards, and advanced analytics to provide leaders with timely, accurate, and actionable insights.
  • Proactively use analytics to address strategic questions, uncover operational risks, and highlight opportunities to support growth, drive efficiency, and improve the client experience.
  • Establish a single trusted source of metrics covering workload, quality, efficiency, and transformation outcomes.
  • Drive integration of data sources to create a connected, transparent view of operations.
  • Monitor performance trends, provide predictive insights, and deliver early warning signals to leadership.
  • Develop a standardized, data-driven framework for workforce planning, capacity management, and productivity tracking.
  • Strengthen data quality, governance, and consistency to enable reliable decision-making.
  • Create a high-performance, collaborative culture that thrives in a complex, matrixed environment.
  • Lead any assigned projects or initiatives as agreed with the Senior Director Business Excellence.

Specific Experiences / Knowledge

  • 10+ years in analytics, BI, or transformation roles within a complex, global organization.
  • Proven track record of establishing and scaling analytics functions — including vision, operating models, and team structures.
  • Strong expertise in BI platforms (e.g., Power BI, Tableau) and data governance best practices.
  • Hands‑on operational experience preferred.
  • Knowledge of advanced analytics, predictive modeling, and AI readiness.
  • Demonstrated success in leading multi‑country transformation programs.
  • Ability to execute at pace in a global, matrix environment.
  • Excellent stakeholder management and influencing skills, with experience engaging senior executives.
  • Bachelor’s degree in Data Science, Analytics, IT, or Business (Masters preferred).

Personal Attributes

  • Energetic, passionate about the importance of data.
  • Strategic thinker who balances vision with execution.
  • Analytical and data-driven, with strong problem-solving skills.
  • Strong communicator who can simplify complexity and inspire adoption of insights.
  • Collaborative and adaptable, thriving across different cultures and environments.
  • Innovative yet pragmatic, with a relentless focus on measurable outcomes.

Reporting Relationships

  • Immediate Manager: Senior Director Service Delivery & Business Excellence
  • Direct Management Reports: Two and to further grow
  • Location: Global
  • Geographical Scope: Global


#J-18808-Ljbffr

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.

Careers

How Many Data Science Tools Do You Need to Know to Get a Data Science Job?

If you’re trying to break into data science — or progress your career — it can feel like you are drowning in names: Python, R, TensorFlow, PyTorch, SQL, Spark, AWS, Scikit-learn, Jupyter, Tableau, Power BI…the list just keeps going. With every job advert listing a different combination of tools, many applicants fall into a trap: they try to learn everything. The result? Long tool lists that sound impressive — but little depth to back them up. Here’s the straight-talk version most hiring managers won’t explicitly tell you: 👉 You don’t need to know every data science tool to get hired. 👉 You need to know the right ones — deeply — and know how to use them to solve real problems. Tools matter, but only in service of outcomes. So how many data science tools do you actually need to know to get a job? For most job seekers, the answer is not “27” — it’s more like 8–12, thoughtfully chosen and well understood. This guide explains what employers really value, which tools are core, which are role-specific, and how to focus your toolbox so your CV and interviews shine.

Jobs

What Hiring Managers Look for First in Data Science Job Applications (UK Guide)

If you’re applying for data science roles in the UK, it’s crucial to understand what hiring managers focus on before they dive into your full CV. In competitive markets, recruiters and hiring managers often make their first decisions in the first 10–20 seconds of scanning an application — and in data science, there are specific signals they look for first. Data science isn’t just about coding or statistics — it’s about producing insights, shipping models, collaborating with teams, and solving real business problems. This guide helps you understand exactly what hiring managers look for first in data science applications — and how to structure your CV, portfolio and cover letter so you leap to the top of the shortlist.

Education

The Skills Gap in Data Science Jobs: What Universities Aren’t Teaching

Data science has become one of the most visible and sought-after careers in the UK technology market. From financial services and retail to healthcare, media, government and sport, organisations increasingly rely on data scientists to extract insight, guide decisions and build predictive models. Universities have responded quickly. Degrees in data science, analytics and artificial intelligence have expanded rapidly, and many computer science courses now include data-focused pathways. And yet, despite the volume of graduates entering the market, employers across the UK consistently report the same problem: Many data science candidates are not job-ready. Vacancies remain open. Hiring processes drag on. Candidates with impressive academic backgrounds fail interviews or struggle once hired. The issue is not intelligence or effort. It is a persistent skills gap between university education and real-world data science roles. This article explores that gap in depth: what universities teach well, what they often miss, why the gap exists, what employers actually want, and how jobseekers can bridge the divide to build successful careers in data science.

🍪 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.