About Company
Princes Ltd is a leading international food and drink group, with a portfolio of much-loved brands including Princes, Napolina, Mazola, and Batchelors. Headquartered in Liverpool, we operate across the UK, mainland Europe, and beyond, sourcing, manufacturing, and distributing high-quality food and drink products to millions of consumers every day. Innovation is at the heart of our operations, and we are constantly striving to leverage cutting-edge technology to enhance our efficiency, product quality, and market responsiveness. Join a dynamic team committed to shaping the future of the food and drink industry through data-driven insights and advanced analytics.
Job Description
We are seeking an innovative and passionate Machine Learning Developer to join our growing data science and analytics team, focused on building and deploying advanced predictive systems. In this critical role, you will be instrumental in transforming raw data into actionable insights, driving significant improvements across our supply chain, manufacturing processes, demand forecasting, and customer experience. You will work on the full lifecycle of machine learning projects, from data exploration and model development to deployment, monitoring, and optimization in a production environment. This is an exciting opportunity to apply your expertise to real-world challenges within a fast-paced and data-rich consumer goods environment, making a tangible impact on business operations and strategic decisions. You will collaborate closely with data scientists, data engineers, and various business stakeholders to understand their needs, translate them into technical requirements, and deliver robust, scalable, and impactful ML solutions. If you are passionate about machine learning, have a strong engineering mindset, and are eager to contribute to a company that values innovation and data-driven decision-making, we encourage you to apply.
Key Responsibilities
- Design, develop, and implement machine learning models and algorithms for various business applications, including demand forecasting, supply chain optimization, quality prediction, and anomaly detection.
- Perform extensive data preprocessing, feature engineering, and data analysis to prepare datasets for model training and evaluation.
- Evaluate model performance, fine-tune parameters, and conduct A/B testing to ensure optimal accuracy and reliability.
- Develop and maintain robust, scalable, and efficient data pipelines for both training and inference.
- Collaborate with data scientists and engineers to integrate ML models into existing production systems and applications.
- Implement MLOps practices for model versioning, deployment, monitoring, and retraining to ensure continuous model performance.
- Translate complex analytical findings and model results into clear, understandable insights for non-technical stakeholders.
- Stay current with the latest advancements in machine learning, artificial intelligence, and data science, proposing new technologies and methodologies.
- Document all development processes, model architectures, and deployment procedures thoroughly.
Required Skills
- Proficiency in Python and its data science ecosystem (Pandas, NumPy, Scikit-learn).
- Strong experience with major machine learning frameworks such as TensorFlow, PyTorch, or Keras.
- Solid understanding of statistical modeling, machine learning algorithms, and predictive analytics.
- Experience with SQL and relational databases for data querying and manipulation.
- Familiarity with cloud platforms (e.g., Azure, AWS, GCP) and their ML services.
- Experience with version control systems, particularly Git.
- Excellent problem-solving skills and the ability to work independently and as part of a team.
- Strong communication skills, capable of explaining complex technical concepts to diverse audiences.
Preferred Qualifications
- Master’s or Ph.D. in Computer Science, Data Science, Statistics, Mathematics, or a related quantitative field.
- Experience with MLOps tools and practices (e.g., MLflow, Kubeflow, Docker, Kubernetes).
- Familiarity with big data technologies such as Apache Spark.
- Domain knowledge in FMCG, supply chain, logistics, or manufacturing.
- Experience with time series forecasting techniques.
- Proficiency in data visualization tools (e.g., Matplotlib, Seaborn, Power BI, Tableau).
Perks & Benefits
- Competitive salary and annual bonus scheme.
- Comprehensive health and dental insurance.
- Generous pension contributions.
- 25 days annual leave plus bank holidays, with options to purchase additional leave.
- Opportunities for professional development, training, and continuous learning.
- Employee discounts on Princes products and a range of retail partners.
- A vibrant, collaborative, and inclusive work environment.
- Cycle-to-work scheme.
- Employee assistance program.
How to Apply
If you are ready to apply your machine learning expertise to real-world challenges within a dynamic and innovative company, we encourage you to click on the application link below to submit your resume and cover letter. We look forward to reviewing your application!