- Company Name
- trg.recruitment
- Job Title
- Data Scientist
- Job Description
-
Job Title: Data Scientist
Role Summary: Design, develop, and deploy production-grade machine learning and generative AI (GenAI) solutions for health and wellbeing data, from data pre‑processing through to operational model delivery in a cloud‑native Azure environment.
Expectations: Own the full model lifecycle—data collection, feature engineering, algorithm selection, training, evaluation, and monitoring—while collaborating with data engineers, DevOps, and peers to integrate solutions into the platform.
Key Responsibilities:
- Prepare and transform large, real‑world datasets using Spark, Kafka, and Python.
- Build and tune ML models with scikit‑learn, PyTorch, or TensorFlow, and develop LLM‑based RAG systems using LangChain.
- Deploy models and pipelines on Azure Databricks, ensuring scalability, reliability, and observability.
- Collaborate with cross‑functional teams to define use cases, assess feasibility, and refine model specifications.
- Monitor model performance in production, applying drift detection, retraining, and rollback procedures as needed.
- Document architecture, code, and best‑practice guidelines for reproducibility.
Required Skills:
- Strong programming in Python, with experience in data manipulation libraries (pandas, NumPy).
- Expertise in ML frameworks: scikit‑learn, PyTorch, or TensorFlow.
- Proficiency in distributed data processing (Spark) and streaming (Kafka).
- Familiarity with Azure cloud services, Databricks, and modern DevOps practices (CI/CD, containerization).
- Knowledge of GenAI techniques, LLMs, and RAG pipelines (LangChain or equivalent).
- Ability to design and conduct rigorous A/B testing and model validation.
- Excellent communication skills to translate technical insights for non‑technical stakeholders.
Required Education & Certifications:
- Bachelor’s or Master’s degree in Computer Science, Data Science, Statistics, or a related field.
- 3+ years of industrial data science or machine‑learning engineering experience.
- Optional: Certifications in Azure Data Science, Machine Learning, or relevant cloud platforms are advantageous.