Digica is a company specializing in the application of Artificial Intelligence (AI) and Machine Learning (ML) methods in research and development projects for leading global clients. We work with partners in the defense, healthcare, and entertainment industries, building innovative AI-driven solutions that bridge the gap between research and production.
Our teams operate in an international environment, collaborating with customers from the US and Europe.
Job DescriptionWe’re looking for an experienced Data Scientist who will also act as a Technical Lead.
We need someone who not only masters Data Science techniques but can also lead projects end-to-end – from initial client discussions and solution design to production deployment of ML models.
You will be responsible for:
- Designing and implementing CV/ML/AI models (predictive, classification, LLM, recommendation systems, etc.),
- Selecting and optimizing algorithms (regression, tree-based models, neural networks, etc.),
- Integrating models into production environments,
- Performing data cleaning, feature engineering, and model validation,
- Identifying tools and specifying processes
- Mentoring junior team members and contributing to solution architecture,
- Preparing and presenting analytical results to business and technical stakeholders.
- 6–8+ years of professional experience in data analysis, statistical modeling, computer vision or machine learning, including at least 4 years as a Data Scientist,
- Hands-on experience deploying ML models to production, not just research-level familiarity,
- Strong proficiency in Python (NumPy, pandas, scikit-learn, matplotlib, pytorch),
- Understanding of Windows or Linux software development platforms
- Excellent command of English – both written and spoken (international client communication, presentations),
- Expertise in at least one of the following domains:
- Computer Vision,
- Large Language Models (LLMs),
- Time Series Analysis,
- Experience with TensorFlow, PyTorch, XGBoost, LightGBM,
- Proficiency with Git, Linux, Docker, MLflow, Airflow, AWS/GCP/Azure,
- Solid SQL and data visualization skills.
Nice to have:
- Proven experience leading projects and managing teams,
- Experience in presales, client workshops, or building Proof-of-Concepts (PoCs),
- Familiarity with Hadoop, Spark,
- Research or R&D background.
Soft Skills
- Ability to structure projects teams, make technical decisions, and own outcomes,
- Ability to manage multiple projects at the same time
- Proactive and self-driven approach, with strong organizational skills,
- Excellent presentation and communication skills,
- Business-oriented mindset – ability to translate insights into actionable recommendations,
- Mentoring attitude and willingness to support team growth.
What We Offer
- Opportunity to work on cutting-edge AI and ML projects,
- Collaboration with international clients (US and Europe),
- Hybrid working model – 3 days per week in the office, with the option to work remotely on the remaining days,
- Choice of employment type
- Supportive, innovation-driven work environment focused on continuous learning and growth.
Skills Required
- 6–8+ years of professional experience in data analysis, statistical modeling, computer vision, or machine learning
- At least 4 years of experience as a Data Scientist
- Hands-on experience deploying machine learning models to production
- Strong proficiency in Python, NumPy, pandas, scikit-learn, Matplotlib, and PyTorch
- Understanding of Windows or Linux software development platforms
- Excellent written and spoken English
- Expertise in Computer Vision, Large Language Models, or Time Series Analysis
- Experience with TensorFlow, PyTorch, XGBoost, and LightGBM
- Proficiency with Git, Linux, Docker, MLflow, Airflow, and AWS, GCP, or Azure
- Solid SQL and data visualization skills
- Experience leading projects and managing teams
- Experience in presales, client workshops, or building Proofs of Concept
- Familiarity with Hadoop and Spark
- Research or R&D background
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?









