Company Description
Technology is our how. And people are our why. For over two decades, we have been harnessing technology to drive meaningful change. By combining world‑class engineering, industry expertise and a people‑centric mindset, we consult and partner with leading brands to create dynamic platforms and intelligent digital experiences that drive innovation and transform businesses. From prototype to real‑world impact – be part of a global shift by doing work that matters.
Role Overview
The Lead Data Scientist is responsible for developing and deploying advanced AI/ML models, leveraging statistical techniques, machine learning, and deep learning to extract actionable insights. This role requires strong expertise in Python‑based AI/ML development, big data processing, and cloud‑based AI platforms (Databricks, Azure ML, AWS SageMaker, GCP Vertex AI).
Key Responsibilities
Data Exploration & Feature Engineering
* Perform thorough Exploratory Data Analysis (EDA) and identify key variables, patterns, and anomalies.
* Engineer and select features for optimal model performance, leveraging domain understanding.
Machine Learning & Statistical Modelling
* Implement classical ML methods (regression, clustering, time‑series forecasting) and advanced algorithms (XGBoost, LightGBM).
* Address computer vision, NLP, and generative tasks using PyTorch, TensorFlow, or Transformer‑based models.
Model Deployment & MLOps
* Integrate CI/CD pipelines for ML models using platforms like MLflow, Kubeflow, or SageMaker Pipelines.
* Monitor model performance over time and manage retraining to mitigate drift.
Business Insights & Decision Support
* Communicate analytical findings to key stakeholders in clear, actionable terms.
* Provide data‑driven guidance to inform product strategies and business initiatives.
Ethical AI & Governance
* Ensure compliance with regulations (GDPR) and implement bias mitigation.
* Employ model explainability methods (SHAP, LIME) and adopt best practices for responsible AI.
Qualifications
* Technical Skills
* Programming: Python (NumPy, Pandas), R, SQL.
* ML/DL Frameworks: Scikit‑learn, PyTorch, TensorFlow, Hugging Face Transformers.
* Big Data & Cloud: Databricks, Azure ML, AWS SageMaker, GCP Vertex AI.
* Automation: MLflow, Kubeflow, Weights & Biases for experiment tracking and deployment.
* Architectural Competencies: Awareness of data pipelines, infrastructure scaling, and cloud‑native AI architectures.
* Alignment of ML solutions with overall data governance and security frameworks.
* Soft Skills
* Critical Thinking: Identifies business value in AI/ML opportunities.
* Communication: Distils complex AI concepts into stakeholder‑friendly insights.
* Leadership: Mentors junior team members and drives innovation in AI.
Additional Information
Benefits include competitive salary package, share plan, company performance bonuses, and value‑based recognition awards. Career coaching, global opportunities, and internal development programmes support growth. Learning opportunities cover complex projects, training, certifications, coaching, workshops, and conferences. Work‑life balance is supported through hybrid work, flexible hours, and employee assistance programme. Health benefits feature a global internal wellbeing programme with access to wellbeing apps. Community engagement includes global tech communities, hobby clubs, and diversity programmes.
At Endava, we’re committed to creating an open, inclusive, and respectful environment where everyone feels safe, valued, and empowered. We welcome applications from people of all backgrounds, experiences, and perspectives. Hiring decisions are based on merit, skills, qualifications, and potential. If you need adjustments or support during the recruitment process, please let us know.
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