Digica

Senior Data Scientist (UK)

Digica Trafford, England, United Kingdom

IT Services and IT Consulting · 51-200 employees

7 h ago
data-scientist Senior (5-10 yrs) Full-time United Kingdom
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About the role

You will design and implement AI/ML models while leading projects from initial client discussions through to production deployment. Additionally, you will mentor junior team members and present analytical results to both business and technical stakeholders.

What they look for

Python Machine Learning Computer Vision Large Language Models Data Science SQL PyTorch TensorFlow XGBoost Docker MLflow Airflow AWS GCP Azure Git

Requirements

Candidates must have 6-8+ years of professional experience in data analysis or machine learning, with at least 4 years specifically as a Data Scientist. Strong proficiency in Python and hands-on experience deploying ML models to production environments are required.

Benefits

Hybrid working model Continuous learning and growth opportunities International collaboration

Full description

Company Description

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 Description

We’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.​​​​​

Qualifications

  • 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.

Additional Information

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,
  • Supportive, innovation-driven work environment focused on continuous learning and growth.

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