Digica are AI and Software Experts delivering tomorrow's AI-powered technology today. We develop intelligent software across AI domains, focusing on Deep Learning in Computer Vision, object recognition, AI on the edge, and embedded AI systems.
Keywords: Machine Learning, Computer Vision, Artificial Intelligence, Data Science, Robotics.
We work with global companies and innovative start-ups in industries such as Defence, Medical, Agricultural and Telecoms. At Digica, we transform cutting-edge science into practical technology for a better tomorrow.
Job DescriptionWe’re looking for a passionate Data Scientist with experience in Computer Vision who enjoys solving real business problems with data and machine learning. You’ll take part in designing and delivering ML solutions end-to-end — from exploration and experimentation to deployment. If you like working with diverse data, collaborating with others, and seeing your models used in production, we’d love to meet you!
QualificationsYour responsibilities will include:
- Designing and developing ML/AI models (predictive, classification, recommendation, LLM-based),
- Selecting and optimizing algorithms (regression, tree-based, neural networks, etc.),
- Performing data cleaning, feature engineering, and model validation,
- Collaborating with clients and internal teams to translate analytical results into actionable insights,
Requirements
We don’t expect you to know everything — but we’re looking for someone who has:
- 3–6 years of experience in data analysis, machine learning, or statistical modeling,
- Solid programming skills in Python (NumPy, pandas, scikit-learn, matplotlib, pytorch, PyTorch or TensorFlow),
- Practical experience with ML model deployment (on cloud or on-premise),
- Good understanding of statistics and data preparation,
- Working knowledge of SQL and version control tools (Git),
- Fluent English – for international communication and collaboration.
Nice to have:
- Experience with Computer Vision, LLMs, or Time Series,
- Familiarity with tools like Docker, MLflow, Airflow, AWS/GCP/Azure,
- Background in research or R&D,
- Experience working in cross-functional or international teams.
Soft Skills:
- Curiosity and problem-solving mindset,
- Clear communication and teamwork,
- Proactive attitude and sense of ownership,
- Ability to explain technical concepts to non-technical audiences.
What We Offer
- Exciting projects in AI and ML with real-world impact,
- Collaboration with international clients (US and Europe),
- Full-time position based in our office in Manchester.
- Supportive, growth-oriented culture that values innovation,
Skills Required
- 3-6 years of experience in data analysis, machine learning, or statistical modeling
- Solid programming skills in Python (NumPy, pandas, scikit-learn, matplotlib, PyTorch or TensorFlow)
- Practical experience with ML model deployment (cloud or on-premise)
- Good understanding of statistics and data preparation
- Working knowledge of SQL
- Version control tools (Git)
- Fluent English for international communication
- Experience with Computer Vision, LLMs, or Time Series
- Familiarity with Docker, MLflow, Airflow, AWS/GCP/Azure
- Background in research or R&D
- Experience working in cross-functional or international teams
- Curiosity, problem-solving mindset, clear communication, teamwork, and proactive ownership
What We Do
85% of AI pilots die in PowerPoint. Digica exists for the other 15%, where algorithms meet atoms and theory meets Thursday’s target. We build AI forged in production, proven under pressure, deployed where failure costs lives and livelihoods. What makes us different: We don't transform operations - we fortify them. We don't replace your workforce - we amplify them. While others promise perfect conditions, we specialise in making AI work with legacy equipment, sparse data, and real-world constraints. Where we operate: Manufacturing floors facing 2.1 million unfilled jobs. Combat zones where $500 drones defeat $5M systems. Anywhere operations matter more than innovation theatre. Our track record: 300+ deployments across manufacturing and defence. Zero still in PowerPoint. From predictive maintenance preventing $47,000/hour downtime to radar systems operational in Ukraine today. Who we serve: Operations directors who need Thursday's results, not next year's promises. Programme managers deploying in 90 days because threats evolve in 30. Engineers who know constraints aren't limitations - they're competitive advantages. Ready to join the 15% Club?
