OverviewRole OverviewThe 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 ResponsibilitiesData Exploration & Feature EngineeringPerform 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 ModellingImplement both 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 & MLOpsIntegrate 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 SupportCommunicate analytical findings to key stakeholders in clear actionable terms.Provide data-driven guidance to inform product strategies and business initiatives.Ethical AI & GovernanceEnsure compliance with regulations (GDPR) and implement bias mitigation.Employ model explainability methods (SHAP, LIME) and adopt best practices for responsible AI.QualificationsTechnical SkillsProgramming: 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 CompetenciesAwareness of data pipelines, infrastructure scaling and cloud-native AI architectures.Alignment of ML solutions with overall data governance and security frameworks.Soft SkillsCritical 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 InformationDiscover some of the global benefits that empower our people to become the best version of themselves:Finance: Competitive salary package, share plan, company performance bonuses, value-based recognition awards, referral bonus.Career Development: Career coaching, global career opportunities, non-linear career paths, internal development programmes for management and technical leadership.Learning Opportunities: Complex projects, rotations, internal tech communities, training certifications, coaching, online learning platforms, subscriptions, pass-it-on sessions, workshops, conferences.Work-Life Balance: Hybrid work and flexible working hours, employee assistance programme.Health: Global internal wellbeing programme, access to wellbeing apps.Community: Global internal tech communities, hobby clubs, inclusion and diversity programmes, events and celebrations.At Endava, we are committed to creating an open, inclusive and respectful environment where everyone feels safe, valued and empowered to be their best. We welcome applications from people of all backgrounds, experiences and perspectives because we know that inclusive teams help us deliver smarter, more innovative solutions for our customers. Hiring decisions are based on merit, skills, qualifications and potential. If you need adjustments or support during the recruitment process please let us know.Remote Work: NoEmployment Type: Full-timeKey SkillsLaboratory Experience, Mammalian Cell Culture, Biochemistry, Assays, Protein Purification, Research Experience, Next Generation Sequencing, Research & Development, cGMP, Cell Culture, Molecular Biology, Flow CytometryExperience: yearsVacancy: 1 #J-18808-Ljbffr