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

Apply Now

Senior Data Scientist

InfoSum
Basingstoke
3 days ago
Create job alert

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

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)

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.

Machine Learning Hiring Trends 2026: What to Watch Out For (For Job Seekers & Recruiters)

As we move into 2026, the machine learning jobs market in the UK is going through another big shift. Foundation models and generative AI are everywhere, companies are under pressure to show real ROI from AI, and cloud costs are being scrutinised like never before. Some organisations are slowing hiring or merging teams. Others are doubling down on machine learning, MLOps and AI platform engineering to stay competitive. The end result? Fewer fluffy “AI” roles, more focused machine learning roles with clear ownership and expectations. Whether you are a machine learning job seeker planning your next move, or a recruiter trying to build ML teams, understanding the key machine learning hiring trends for 2026 will help you stay ahead.

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

Summary: UK machine learning hiring has shifted from title‑led CV screens to capability‑driven assessments that emphasise shipped ML/LLM features, robust evaluation, observability, safety/governance, cost control and measurable business impact. This guide explains what’s changed, what to expect in interviews & how to prepare—especially for ML engineers, applied scientists, LLM application engineers, ML platform/MLOps engineers and AI product managers. Who this is for: ML engineers, applied ML/LLM engineers, LLM/retrieval engineers, ML platform/MLOps/SRE, data scientists transitioning to production ML, AI product managers & tech‑lead candidates targeting roles in the UK.

Why Machine Learning Careers in the UK Are Becoming More Multidisciplinary

Machine learning (ML) has moved from research labs into mainstream UK businesses. From healthcare diagnostics to fraud detection, autonomous vehicles to recommendation engines, ML underpins critical services and consumer experiences. But the skillset required of today’s machine learning professionals is no longer purely technical. Employers increasingly seek multidisciplinary expertise: not only coding, algorithms & statistics, but also knowledge of law, ethics, psychology, linguistics & design. This article explores why UK machine learning careers are becoming more multidisciplinary, how these fields intersect with ML roles, and what both job-seekers & employers need to understand to succeed in a rapidly changing landscape.