At a Glance
- Tasks: Design and deploy machine learning models to enhance workplace safety and compliance.
- Company: Join a forward-thinking tech company dedicated to creating safer workplaces globally.
- Benefits: Enjoy flexible working, generous leave, health plans, and continuous learning opportunities.
- Other info: Be part of a diverse team in a supportive, inclusive environment.
- Why this job: Make a real impact by using AI to improve safety and compliance for thousands.
- Qualifications: Degree in data science or related field; experience with Python, SQL, and ML frameworks.
The predicted salary is between 50000 - 70000 £ per year.
Building innovative solutions; enabling safer workplaces for everyone. We’ll create a safer working world, building software to support a global network of responsible buyers, suppliers and partners. We take the pain out of compliance for over 50,000 organisations globally, helping them protect their people, their operations, and the planet. Keeping our network of hiring clients, suppliers, and contractors compliant with the standards that matter most, from health and safety and sustainability to ethical behaviour by building best in class solutions.
Veriforce is seeking a data scientist with hands‑on experience building models to power workflows for business applications and internal processes. You will join a growing team of talented data modeling, data engineering, AI engineers, and DevOps engineers, to expand our platforms to integrate with LLMs, MCPS, APIs, and enterprise data. Your work will help shape the way our clients and contractors get to work faster, stay compliant, and come home safely every day.
What that means day to day:
- Design, develop, and deploy machine learning models for risk scoring, compliance prediction, churn analysis, and contractor performance analytics.
- Build and deploy Large Language Models (LLMs) based solutions for text data insights, anomaly detection, and automated compliance checks.
- Collaborate with engineering and product teams to integrate models into production systems hosted on AWS and Azure.
- Utilize Microsoft Fabric for data ingestion, transformation, and feature engineering.
- Implement best practices for model monitoring, retraining, and performance optimization.
- Participate as an integral member of a cross‑functional team using agile methodologies.
- Work in an Agile‑based SDLC that embraces the principles of transparency, cooperation, decomposing work, and rapid iteration.
- Stay current with emerging technologies in AI/ML, predictive analytics, and supply chain risk management.
- Ability to communicate with non‑engineers about how technology is solving business needs, including demonstrating features for feedback.
What you’ll need to be successful:
- Education: Bachelor’s or master’s in data science, Computer Science, Statistics, or related fields.
- Experience: Proven experience with Python, SQL, and ML frameworks (e.g., TensorFlow, PyTorch, Jupyter Notebooks).
- Familiarity with AWS services (S3, SageMaker, Lambda) and Microsoft Fabric.
- Strong understanding of predictive modeling, NLP, and LLM architectures.
- Excellent problem‑solving skills and ability to communicate complex concepts to non‑technical stakeholders.
- Exceptional communication skills, able to translate business requirements into technical output and relay outcomes back to the appropriate audience.
What you'll get in return:
- We have a hybrid workplace policy, where you will work from the office 3 days per week.
- We want you to be able to do your best work here. We emphasize providing many ways to support our team to do their best work and below are some of the perks and benefits we offer.
Personal Health & Wellbeing / Benefits:
- Enhanced Parental Leave
- Generous annual leave
- Healthcare Plan
- Annual Giving Day – an extra day to give back to yourself or your community
- Cycle‑to‑work Scheme
- Pension scheme with employer contributions
- Life Assurance – 3X base salary
- Rewards Program – access to discounts and cashback
- LinkedIn Learning License for upskilling & development
Bring Your Whole Self to Work. We are proudly an equal‑opportunity employer. We are committed to ensuring that no candidate is discriminated against because of gender identity and expression, race, disability, ethnicity, sexual orientation, age, colour, region, creed, national origin, or sex. We are dedicated to growing a diverse team while continuing to create an inclusive environment where everyone feels safe and empowered to be themselves.
Data Scientist in London employer: Cognibox
Veriforce is an exceptional employer that prioritises innovation and employee well-being, offering a hybrid workplace policy that fosters collaboration and flexibility. With a strong commitment to personal health and development, employees benefit from generous leave, enhanced parental support, and access to continuous learning opportunities. The inclusive work culture encourages diversity and empowers team members to bring their whole selves to work, making it a rewarding environment for those looking to make a meaningful impact in the field of data science.
StudySmarter Expert Advice🤫
We think this is how you could land Data Scientist in London
✨Get Involved in Data Science Meetups
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✨Leverage Professional Networks
Join professional bodies related to data science, like the Data Science Society or similar organisations. Getting involved can lead to mentorship opportunities and insider knowledge about full-time positions at companies like Cognibox.
✨Apply Directly through Our Website
When you find a suitable opening like Data Scientist at Cognibox, make sure to apply directly through our website. It gives you an edge and shows you're keen to join our team. Plus, who doesn’t love a direct application? It’s easier than navigating through job boards!
We think you need these skills to ace Data Scientist in London
Some tips for your application 🫡
Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!
Quantify Your Achievements:Employers love numbers! When drafting your CV, highlight your achievements with quantifiable results. For instance, mention how your data analysis led to a certain percentage increase in efficiency or revenue at a previous job or project. These details can really make your application pop!
Craft a Tailored Cover Letter:For a full-time role at Cognibox, your cover letter should reflect your passion for data science and your excitement about the specific projects or values of the company. Dive into why you’re a good fit, how your skills align with their needs, and any unique perspectives you can bring to the team.
Stand Out with Relevant Courses and Certifications:Although experience talks, relevant courses or certifications can be your ticket to impressing hiring managers at Cognibox. Mention any standout courses you've completed that equipped you with essential skills, such as machine learning certifications or data visualisation courses. This shows your commitment to continuously developing your skills in the field!
How to prepare for a job interview at Cognibox
✨Brush Up on Your Statistics
For a data science role, we need to seriously sharpen our statistics skills. Get ready to tackle technical questions on probability distributions, hypothesis testing, and regression analysis. These are often the bread and butter of data science interviews, so don't just skim over them!
✨Showcase Your Projects
Prepare a killer portfolio showcasing your data science projects. We should include details about the datasets used, the tools and techniques applied, and the impact of your findings. If we can walk them through a particularly challenging project or a cool visualisation that had real-world implications, it’ll really make us stand out!
✨Get Comfortable with Python and R
Most data science positions require us to be proficient in programming languages like Python and R. We should practice common libraries like pandas, NumPy, and scikit-learn, and be ready for live coding exercises or algorithm questions. Showing off our coding chops can really impress the interviewers at Cognibox!
✨Prepare for Case Studies
Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.