FAI
Junior Data Scientist - Insite
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About the Role
We're looking for a curious and driven Junior Data Scientist to join our growing analytics team. You'll work alongside experienced data scientists, supply chain experts and sustainability scientists to turn commercial datasets into actionable insights that shape animal supply chain direction. This is a great opportunity to develop your skills in a collaborative team, passionate about building better food systems.
Location: Remote (United Kingdom)
Position: Full time Employee, 35.5 hours/week.
Team: Data Science Team
Responsibilities
As a Junior Data Scientist, you will work closely with FAI’s consultancy and data teams to develop efficient and impactful methods to analyse, interpret and present supply chain data. You will be a creative and motivated individual capable of independent and collaborative outputs that can support our supply chain partners to better our food system. In this role you will:
- Understand key issues in agriculture and aquaculture and supply chains and metrics for assessing supply chain sustainability
- Clean, integrate and analyse structured and unstructured supply chain data from multiple sources, including farms, factories, IoT sensors, ERP systems, open-source data and FAI’s custom-built applications
- Collaborate with FAI’s consultants and industry experts to define and solve data problems
- Conduct exploratory data analysis (EDA) to surface trends, patterns, and anomalies
- Create clear visualizations and decision-support dashboards to communicate findings to both technical and non-technical stakeholders
- Translate findings into practical recommendations that clients and industry can act on
- Build and validate predictive models and machine learning algorithms
- Document methodologies, code, and results and present findings to ensure reproducibility and shared understanding
- Stay current with developments in data science, ML, and relevant industry trends
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Requirements
Qualifications & Experience
Essential
- Bachelor's degree in Data Science, Statistics, Computer Science, Mathematics, or another quantitative subject (or equivalent practical experience)
- Proficiency in Python and/or R, with experience in data wrangling and modelling
- Solid understanding of SQL and working with relational databases
- Understanding of core machine learning concepts (regression, classification, clustering, etc.)
- Experience with data visualization tools (e.g., Matplotlib, Seaborn, Tableau, Power BI)
- Strong analytical thinking and problem-solving skills
- Strong communication skills — able to explain and present data-driven insights to technical and non-technical audience
- Comfortable working with messy, real-world datasets
- Willingness to engage with research to gather domain specific knowledge
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Desirable
- Experience working closely with clients/customer to understand their needs and requirements
- Experience in the challenges of deploying analytics models in the real world
- Experience of model monitoring, scalability, optimisation and review
- Interest in farming, animal health, welfare or sustainability
- Knowledge of agricultural and/or animal sciences
- Experience with cloud platforms (AWS, GCP, or Azure)
- Exposure to MLOps practices or model deployment
- Knowledge of version control with Git
Benefits
What We Offer
- 33 days annual leave inclusive of bank holidays (pro rata for part time)
- Additional holiday awarded for long service
- Holiday purchase scheme (up to one week per year)
- Contributory auto-enrolment pension scheme
- Private health insurance scheme
- Discretionary bonus scheme
- Generous Company sick pay scheme (12 weeks full pay, 12 weeks half pay, after successful completion of probation)
- Enhanced Maternity and Adoption Pay (full pay for 18 weeks, after 26 weeks service by the qualifying week)
- Enhanced Paternity Pay, full pay for 2 weeks (after 26 weeks service by the qualifying week)
- Sabbatical leave opportunity for long service
Join FAI Farms as a Junior Data Scientist - Insite to drive sustainable change in global supply chains using your analytical skills and passion for impactful, science-led solutions.
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