Associate Director, Data Analytics - Value Creation & Deals

Interpath
Leeds
2 months ago
Applications closed

Related Jobs

View all jobs

Research Data Analytics Expert

Research Data Analytics Expert

Research Data Analytics Expert

Research Data Analytics Expert

Research Data Analytics Expert

Research Data Analytics Expert

Associate Director, Data Analytics - Value Creation & Deals

1 day ago Be among the first 25 applicants


Get AI-powered advice on this job and more exclusive features.


Associate Director, Data Analytics - Value Creation


Interpath


Leeds or Birmingham or Belfast or Manchester or Glasgow


Interpath is an international and fast-growing advisory business with deep expertise in a broad range of specialisms spanning deals, advisory and restructuring capabilities.


We deliver tangible results for global businesses, their investors, and stakeholders when complex problems arise, and critical decisions need to be made. Interpath is agile, independent, and conflict-free, and our passion for doing what's right, every time, sets us apart.


Our diverse teams provide specialist technical knowledge combined with deep sector experience across our service line specialisms. Since our foundation in 2021, Interpath has grown rapidly, and we now have a presence across the UK, Ireland, France, Germany, Austria, Spain, BVI, Cayman Islands, Bermuda, Barbados, and Hong Kong. By 2030 we aim to be one of the world's leading advisory firms with a truly global footprint.


Interpath is looking for an experienced candidate to help develop Interpath's Data & Technology consulting group, of which the Data Analytics team is part. Our Data Analytics team is a busy group serving analytics requirements across multiple service lines at Interpath.


We will consider Data Analytics specialists with experience in various areas, in particular experience of Value Creation, Transaction Services, Forensic or Compliance would be relevant.


The successful applicant will bring fresh data solutions and ideas for the variety of client projects, covering the way the data is collected, stored, applied and presented.


This is an opportunity to join a fast-growing unit and to play a key role in its development and growth.


Key Accountabilities:



  • Deals Analytics support
  • Building new data capabilities covering Customer profiling, segmentation & profitability; demand forecasting & inventory management; supply chain optimisation; (Procurement) spend analytics to compliment the mature working capital capability in place today.
  • Create a Data Insight playbook covering the topics above.
  • Accelerate delivery timelines through better solutions.
  • Act as central point of contact for the team and create great working relationships.
  • Show the "art of the possible" and be integral in the change management process.
  • Help the team to extract information and provide insightful reports (using different techniques).
  • Create meaningful dashboards to help inform/set strategy and predict trends (for clients).
  • Work with the data team to determine the best data infrastructure to maximise analysis.
  • Design a blue-print architecture of the tools and techniques to use for value creation and client facing projects.
  • Lead the charge in building new data capabilities within the team.
  • Accelerate delivery of key data projects through new ‘ways of thinking'.

Requirements



  • At least 4 years of experience in the Data Analytics space (preferably in a consulting context).
  • University degree 2.1 or higher (or equivalent) in Computer Science / Mathematics / Statistics or equivalent.
  • End to end knowledge of data warehouse and reporting processes.
  • Ability to identify and implement process improvements in a controlled manner.
  • Have strong consulting skills, having applied business intelligence and data analytics techniques in that context.
  • Be very hands-on, technically strong on data engineering, reporting and analysis.
  • Be commercially savvy and articulate in ‘data' story-telling to clients and hence a trusted adviser to key stakeholders.
  • Numerate & analytical with knowledge of data management.
  • Proficient in BI tools like PowerBI, Qlik, Tableau.
  • Proficient in Microsoft SQL.
  • Proficient in Python / R.
  • Strong knowledge of statistical methodologies and data analysis techniques (eg clustering).
  • Passionate about data analytics. Technically self-sufficient with a desire and ability to research and pick up new tools and techniques quickly.
  • Ability to visualise data effectively and communicate findings and recommendations clearly.
  • Proven experience of cloud technologies (AWS, MS Azure, GCP).

Advantageous competencies (but not essential):



  • Exposure to AI/ML.
  • Exposure to the open source stack.
  • Experience in price modelling techniques.
  • Experience in managing a small data team and mentoring.
  • Some exposure to behavioural data (eg Google or Adobe analytics).

At Interpath, our people lie at the heart of our business. That's why we provide employees with a competitive and comprehensive reward package including compelling salaries and a range of core and optional benefits. Read more about our benefits; Company Benefits - Interpath


Unsolicited Resumes from Third-Party Recruiters


Please note that Interpath do not accept unsolicited resumes from third-party recruiters. Any employment agency, person or entity that submits an unsolicited resume does so with the understanding that Interpath will have the right to hire that applicant at its discretion without any fee owed to the submitting employment agency, person or entity.


Seniority level

  • Seniority levelMid-Senior level

Employment type

  • Employment typeFull-time

Job function

  • Job functionConsulting, General Business, and Strategy/Planning
  • IndustriesFinancial Services, Professional Services, and Venture Capital and Private Equity Principals

Referrals increase your chances of interviewing at Interpath by 2x


Leeds, England, United Kingdom 1 week ago


Data, Insights & Analytics Graduate Programme

Leads, England, United Kingdom 1 week ago


Normanton, England, United Kingdom 1 month ago


Leeds, England, United Kingdom 5 days ago


Senior Analyst - HR Data and People Analytics

Leeds, England, United Kingdom 1 month ago


Leeds, England, United Kingdom 1 week ago


Leeds, England, United Kingdom 6 days ago


We’re unlocking community knowledge in a new way. Experts add insights directly into each article, started with the help of AI.


#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.

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.

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.

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.