The Role
Design, develop, and deploy machine learning and LLM-based solutions for risk scoring, compliance prediction, churn analysis, and contractor analytics. Integrate models into production on AWS and Azure, use Microsoft Fabric for data pipelines and feature engineering, implement model monitoring and retraining, and collaborate cross-functionally within an Agile SDLC.
Summary Generated by Built In
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, being able to translate business requirement into technical output, and the ability to 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
Future Planning
>💰Pension scheme with employer contributions
>🧬 Life Assurance – 3X base salary
>💸 Rewards Program – access to discounts and cashback
>🏫 LinkedIn Learning License for upskilling & development
Interested but don’t feel you meet all the requirements?
Our recruitment team assesses and reviews all applications against the role and business needs. We believe in people having transferable and soft skills and want you to know that we do consider where an individual might not meet all the criteria, but have the aptitude and capability, nonetheless. Our priority is to ensure we set people up for success. We will make a final call based on our determining whether we can offer the necessary support to upskill or provide the developmental support needed for you to get the best out of this opportunity with us!
Bring Your Whole Self to Work.
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.
What you can expect if you apply:
What you can expect if you apply:
- A response to your application within 15 working days
- An interview process consisting of:
- An initial discovery call with the recruiter
- A first stage interview via Microsoft Teams
- Additional interview (likely face to face) with the stakeholders you’ll be working with closely in the role
We’re keen to ensure our hiring process allows you to be at your best, so if you need us to make any adjustments, please just let us know.
#GTECH
#GTECH
About
Equal Employment Opportunity We are an equal opportunity workplace. All candidates will be afforded equal opportunity through the recruiting process. We do not discriminate against any employee or applicant for employment because of race, color, sex, age, national origin, religion, sexual orientation, disability, gender identity and/or expression. We are dedicated to growing a diverse team of highly talented individuals and creating an inclusive environment where everyone feels empowered to bring their authentic selves to work. If you are contacted for an interview and require accommodation/adjustments during the interviewing process, please let us know.
Skills Required
- Bachelor's or master's in Data Science, Computer Science, Statistics, or related field
- Proven experience with Python
- Proven experience with SQL
- Experience with ML frameworks (TensorFlow, PyTorch) and Jupyter Notebooks
- Familiarity with AWS services (S3, SageMaker, Lambda)
- Familiarity with Microsoft Fabric
- Strong understanding of predictive modeling, NLP, and LLM architectures
- Ability to communicate complex concepts to non-technical stakeholders
- Experience working in Agile SDLC and cross-functional teams
Am I A Good Fit?
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The Company
What We Do
We help create better workplaces, and help to keep people safe, reduce risks and simplify processes through our expert teams and technology. Since 1979, we’ve been providing our clients with market-leading compliance and risk management solutions. We have expanded over the years to include certification, accreditation, HR and health and safety consultancy for SMEs, and training expertise, resulting in the Alcumus business that exists today. By building great relationships with our customers, we understand their needs and provide a range of technology solutions, advice and support that helps to identify and minimise risks, navigate compliance and create better workplaces to keep people safe. Our solutions go beyond simple box ticking exercises, where we constantly look for new and innovative ways to support and enhance our clients’ businesses and make it easier for them to keep their workforce safe by embracing new and evolving technology. Our team includes over 1,000 employees across our UK, North American, American and APAC offices. We take great pride in being an inclusive organisation by respecting and appreciating each individual, regardless of age, gender, ethnicity, religion, disability, sexual orientation, education, or nationality, creating a safe, positive, and nurturing environment. Whether you’re a contractor, SME or multi-national enterprise, we’re here to help create safe and effective workplaces.
