Be at the heart of actionFly remote-controlled drones into enemy territory to gather vital information.

Apply Now

Senior Data Scientist

InfoSum
Basingstoke
5 days ago
Applications closed

Related Jobs

View all jobs

Senior Data Scientist

Senior Data Scientist

Senior Data Scientist

Senior Data Scientist

Senior Data Scientist

Senior Data Scientist/AI Engineer (Remote)

An engineering team is responsible for designing, developing, and maintaining products or systems, ensuring they meet performance, safety, and reliability standards. This involves planning and managing projects, collaborating with other teams, conducting thorough testing, and troubleshooting issues. They also focus on continuous innovation and improvement, compliance with regulations, and providing technical support to stakeholders. By documenting their processes and designs, they ensure clarity and consistency, contributing to the delivery of high-quality, reliable, and innovative solutions.


Sub Department Summary

The data science team currently supports multiple areas of the business through knowledge of modeling and manipulating datasets. We assist testing new use cases through production of new datasets and understanding data analysis use-cases.. We also support the engineering and architecture teams through research of new technologies, performance testing, and investigation into new initiatives E.g. Synthetic Data, Data Modeling and Data Analysis.


In the future the Data Science team should additionally be capable of supporting Product through reporting on customer usage, enabling data-driven decision making.


Job Overview

The Senior Data Scientist will work closely with the domain area specialists to improve, optimise and validate the core capabilities of the InfoSum Platform. Manage bespoke data driven projects to support stakeholders with individual experiment needs and define success metrics in close collaboration with the Product and Engineering teams to help evaluate and communicate experiment insights to relevant stakeholders.


Core Responsibilities

  • Carrying out research activities.
  • Leading data mining and collection procedures.
  • Ensuring data quality and integrity.
  • Interpreting and analyzing data problems.
  • Conceive, plan and prioritize data projects.
  • Building analytic systems and predictive models.
  • Additional responsibilities as and when required by the business.

Additional company wide requirements

  • Understand and comply with InfoSum’s security and privacy policies, and be attentive to information security at all times in the performance of duties for InfoSum.

The main skills needed to deliver the core responsibilities

  • Understanding of computer science fundamentals including; data structures, algorithms, data modeling and software architecture.
  • Proven experience with Machine Learning algorithms, such as; Logistic Regression, Random Forest, XGBoost, Supervised and unsupervised ML algorithms - as well as innovative research areas such as Deep Learning algorithms.
  • Knowledge of SQL and Python's ecosystem for data analysis, using; Jupyter, Pandas, Scikit Learn, Matplotlib.
  • Analytical mindset, self starter and proactive
  • Solid understanding of model evaluation and data pre-processing techniques, such as standardisation, normalisation, and handling missing data.
  • Proven experience of productionisation of Machine Learning based products.
  • Excellent communication skills, experience working in cross-functional teams and communicating technical results to stakeholders.

What are the key indicators of success in this role?

Critical success factors include:



  • Providing analytical insights
  • Models
  • Data visualizations
  • Analytical direction that shapes the future technology strategy of InfoSum.

As well as working as part of an amazing, engaging and collaborative team, we offer our staff a wide range of benefits to motivate them to be the best they can be! Here’s an overview of everything we offer right now!


You will receive

A competitive salary based on your experience and ability to perform in role


25 days annual leave (excluding bank holidays) + a day off for your birthday + 2 Volunteering days


Private medical insurance


Life assurance - 4x your base salary


Fantastic corporate discounts and mental wellbeing support, including a top of line EAP.


Salary sacrifice schemes


Enhanced Maternity, Adoption & Share Parental Leave


We have fantastic offices in Basingstoke and London complete with a fully stocked fridge / snacks and catered lunches 2 times a week.


We also reward our teams with monthly socials,4pm finishes on a Friday & 3pm Fridays finishes during the summer months of June, July and August, 3 extra days off during the Christmas holidays and a culture built on recognition, collaboration and success.


#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.

Neurodiversity in Data Science Careers: Turning Different Thinking into a Superpower

Data science is all about turning messy, real-world information into decisions, products & insights. It sits at the crossroads of maths, coding, business & communication – which means it needs people who see patterns, ask unusual questions & challenge assumptions. That makes data science a natural fit for many neurodivergent people, including those with ADHD, autism & dyslexia. If you’re neurodivergent & thinking about a data science career, you might have heard comments like “you’re too distracted for complex analysis”, “too literal for stakeholder work” or “too disorganised for large projects”. In reality, the same traits that can make traditional environments difficult often line up beautifully with data science work. This guide is written for data science job seekers in the UK. We’ll explore: What neurodiversity means in a data science context How ADHD, autism & dyslexia strengths map to common data science roles Practical workplace adjustments you can request under UK law How to talk about your neurodivergence in applications & interviews By the end, you’ll have a clearer sense of where you might thrive in data science – & how to turn “different thinking” into a real career advantage.

Data Science Recruitment Trends 2025 (UK): What Job Seekers Need To Know About Today’s Hiring Process

Summary: UK data science hiring has shifted from title‑led CV screens to capability‑driven assessments that emphasise rigorous problem framing, high‑quality analytics & modelling, experiment/causality, production awareness (MLOps), governance/ethics, and measurable product or commercial impact. This guide explains what’s changed, what to expect in interviews & how to prepare—especially for product/data scientists, applied ML scientists, decision scientists, econometricians, growth/marketing analysts, and ML‑adjacent data scientists supporting LLM/AI products. Who this is for: Product/decision/data scientists, applied ML scientists, econometrics & causal inference specialists, experimentation leads, analytics engineers crossing into DS, ML generalists with strong statistics, and data scientists collaborating with platform/MLOps teams in the UK.

Why Data Science Careers in the UK Are Becoming More Multidisciplinary

Data science once meant advanced statistics, machine learning models and coding in Python or R. In the UK today, it has become one of the most in-demand professions across sectors — from healthcare to finance, retail to government. But as the field matures, employers now expect more than technical modelling skills. Modern data science is multidisciplinary. It requires not just coding and algorithms, but also legal knowledge, ethical reasoning, psychological insight, linguistic clarity and human-centred design. Data scientists are expected to interpret, communicate and apply data responsibly, with awareness of law, human behaviour and accessibility. In this article, we’ll explore why data science careers in the UK are becoming more multidisciplinary, how these five disciplines intersect with data science, and what job-seekers & employers need to know to succeed in this transformed field.