Senior Data Scientist

Informed Solutions
Altrincham
3 weeks ago
Create job alert
The Opportunity

We're seeking a passionate Data Scientist to own the end-to-end implementation and design of data science applications for various clients. You will join a growing practice and champion and actively contribute to the growth of the discipline, enabling the ongoing growth of the data science capability. You'll join a talented team of dynamic and driven professional problem solvers; creative thinkers and solutions builders who thrive on helping clients meet the most exciting digital transformation challenges.


Make a difference and advance your career by helping deliver some of the UK's most important #tech4good projects, making the world a smarter, safer, greener, and healthier place.


At a certified Great Place to Work® you'll experience a dynamic and nurturing environment that rewards initiative and flexibility and enjoy a career path tailored to your own aspirations.


About Us

Founded in 1992, we are a successful, growing International digital transformation consultancy. We deliver multi-Queen's Award for innovation winning platforms and services that support large-scale digital transformation. Our digital, data and technology solutions are used by globally recognised public and private sector brands operating in a variety of sectors including Civil Defence, Healthcare, Sustainable Environment and Land Asset Management, and Digital Democracy.


Key Accountabilities And Responsibilities

  • Senior Data Scientists enable the design, development, integration and testing of complex, high quality data science solutions and services to meet user needs, continually improving the application of best practice patterns, methods and tools. This includes:
  • Build effective working relationships with client counterparts in your practitioner domain, and those of a partner / 3rd party organisation
  • Own the end-to-end implementation and design of data science models/components, seeking guidance and input from Lead and Principal Data Scientists where necessary
  • Help structure and provide technical assurance for the work of less experienced practitioners, enabling them to maximise quality and velocity. Monitor the application of the methods and requirements, pro-actively managing technical risks and issues
  • Collaborating with practitioners from other disciplines (e.g. UCD, Engineering) to ensure the solution meets user and business needs
  • Take technical responsibility for the delivery of high-quality data science services on smaller engagements, across all stages (design, build, test, deploy, operate and continually improve), in line with best practice
  • Work with Delivery Managers to inform estimates for research and development activities, enabling them to plan technical activities, including how teams and work should be structured
  • Proactively identify and help mitigate technical risks, issues, assumptions and dependencies
  • Maintain relevant, up-to-date practitioner skills through training and accreditation, including a domain-relevant accreditation/certification at professional level
  • Being an active member of the Data Science discipline, identifying area for growth across the business, and providing coaching for less experienced practitioners

Requirements

  • Background in Agile delivery environments, delivering software solutions in controlled increments (e.g., following Scrum, Agile Delivery phases, etc.)
  • Experience working with cloud-based solutions and technologies (Google Cloud Platform, AWS, Azure)
  • Hands‑on knowledge of designing and implementing solutions capable of handling sensitive data (e.g., Personally Identifiable Information).
  • Strong knowledge of a programming languages for data science (Python, R, etc.) including best practices using this language to write robust software
  • An understanding of data governance and best practices to ensure data protection
  • Experience planning technical activities and structuring work for a team
  • Being able to provide commercially robust estimates of development activities
  • Experience providing practitioner guidance to junior colleagues and peers
  • Understanding of how to operationalise and deploy a Data Science solution in a live environment
  • A bachelor's degree in a STEM field

Desirable Skills And Experience

  • Experience working in a professional services/consultancy environment preferred
  • Experience solving natural language processing problems
  • Experience creating generative AI applications, such as chatbots or RAG retrieval systems
  • Stay up to date with cutting edge of AI, reading research papers, attending conferences, etc
  • Ability to work effectively across multiple teams and projects
  • Ability to explain and simplify complex information to stakeholders, gathering and translating business requirements, anticipating any obstacles to information flow
  • Understanding of different databases (Relational and NoSQL) and optimising queries for effective data manipulation
  • A master's degree or PhD in a STEM field

Personal Qualities

  • You are hands on, working within a team to solve complex software and feature problems
  • Inquisitive, using critical thinking to ask lots of questions, overcome biases, break assumptions and consider different perspectives
  • Strong analytical and problem‑solving skills
  • Excellent communication and interpersonal skills
  • Detail-oriented with a focus on accuracy
  • Able to plan and organise your own work, effectively negotiating priorities across multiple teams across the business
  • Able to collaborate with other areas of the business to solve problems
  • Able to quickly learn and adapt to new technologies

Benefits

  • InformedACADEMY© - We offer excellent career development opportunities through our award‑winning personal and professional development programmes, including support with professional certifications.
  • Industry leading health and wellbeing plan - We partner with several wellbeing support functions to cater to each individual's need, including 24/7 GP services, mental health support and physical health support.
  • Hybrid working*
  • Private Health Care Cover*
  • Generous life assurance cover*
  • Gym Membership*
  • Monthly office lunch
  • Onsite massage sessions
  • 25 paid working days holiday per year plus bank holidays*
  • Sabbatical Leave Scheme*
  • Enhanced Maternity Leave and Pay*
  • Enhanced Paternity Leave and Pay*
  • Company Pension Contribution
  • Profit Share Scheme
  • Payment of professional subscriptions
  • Generous referral scheme with no limits on the number of referrals
  • Salary Sacrifice scheme*
  • Qualifying period applies

Culture

We are proud to nurture a workplace culture that is diverse, inclusive, rewarding, and egalitarian.


We strive to live up to our values of Innovation, Excellence, and Integrity by thinking about things differently, always doing our best, and acting in good faith at all times.


We're a team of passionate problem solvers. We take pride in helping our clients accelerate and de‑risk digital business change so that we can collaborate and codesign world‑class digital services that solve complex business and safety‑critical problems, particularly where place, location or geography are important.


Our workplace culture reflects how we go about our work, the type of work that we choose to do, and our commitment and contribution to the sustainable social, environmental, and economic development aims of the communities that we are part of.


We focus both on technical skills and equally importantly, on the cultural fit of prospective new colleagues. Our success relies on fostering an environment where creativity and collaboration produce great outcomes for our people, our clients, and our partners.


#J-18808-Ljbffr

Related Jobs

View all jobs

Senior Data Scientist

Senior Data Scientist

Senior Data Scientist

Senior Data Scientist

Senior Data Scientist

Senior Data Scientist (GenAI)

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.