- Company Name
- Endava
- Job Title
- Senior Data Scientist
- Job Description
-
**Job Title:** Senior Data Scientist
**Role Summary:**
Lead the design, development, and deployment of advanced AI/ML solutions to generate actionable business insights. Drive end‑to‑end model pipelines, ensure ethical AI practices, and translate complex analytical results into clear recommendations for stakeholders. Mentor junior team members and collaborate across functions to align data science initiatives with strategic objectives.
**Expectations:**
- Deliver high‑impact ML models on schedule, meeting accuracy and performance targets.
- Maintain robust, production‑ready pipelines with monitoring and continuous improvement.
- Uphold data privacy, bias mitigation, and model explainability standards.
- Foster knowledge sharing and guide junior data scientists.
**Key Responsibilities:**
- Conduct exploratory data analysis and feature engineering using domain knowledge.
- Build and evaluate classical (regression, clustering, time‑series) and advanced models (XGBoost, LightGBM, CNNs, RNNs, Transformers).
- Develop computer vision, NLP, and generative AI solutions with PyTorch, TensorFlow, or Hugging Face.
- Implement MLOps practices: CI/CD pipelines, model versioning, and automated retraining (MLflow, Kubeflow, SageMaker Pipelines).
- Monitor model performance, detect drift, and trigger retraining as needed.
- Communicate findings and strategic recommendations to non‑technical stakeholders.
- Ensure compliance with GDPR and other regulations; apply bias mitigation and explainability tools (SHAP, LIME).
- Collaborate with data engineers to design scalable data pipelines and cloud‑native architectures.
**Required Skills:**
- Programming: Python (NumPy, Pandas), R, SQL.
- ML/DL frameworks: scikit‑learn, PyTorch, TensorFlow, Hugging Face Transformers.
- Big‑data & cloud platforms: Databricks, Azure ML, AWS SageMaker, GCP Vertex AI.
- MLOps tools: MLflow, Kubeflow, Weights & Biases, CI/CD for ML.
- Statistical analysis, feature selection, model evaluation, and hyperparameter tuning.
- Strong problem‑solving, critical thinking, and business acumen.
- Excellent communication; ability to simplify complex concepts.
- Leadership/mentoring experience.
**Required Education & Certifications:**
- Bachelor’s degree in Computer Science, Statistics, Mathematics, Engineering, or related field (minimum).
- Master’s degree preferred; Ph.D. in a quantitative discipline is a plus.
- Relevant certifications (e.g., AWS Certified Machine Learning – Specialty, Azure AI Engineer, Google Professional Machine Learning Engineer) are advantageous.