- Company Name
- Synechron
- Job Title
- Data Scientist
- Job Description
-
**Job Title:** Senior Data Scientist – Credit Risk Technology
**Role Summary:**
Lead the full lifecycle of data and AI solutions for credit risk, driving advanced machine learning and generative AI initiatives. Own model development, deployment, monitoring, and governance while collaborating with cross‑functional stakeholders to deliver production‑grade risk analytics.
**Expectations:**
- Own end‑to‑end delivery of credit risk analytics products in a regulated environment.
- Maintain high standards for model performance, explanation, and ethical compliance.
- Influence strategy, product roadmap, and technology choices across teams.
**Key Responsibilities:**
- Develop and deploy predictive models using scikit‑learn, XGBoost, LightGBM, PyTorch, or TensorFlow.
- Design and operationalise Retrieval‑Augmented Generation workflows and LLM applications for unstructured data.
- Build and maintain MLOps pipelines (MLflow, Airflow) for versioning, monitoring, and drift remediation.
- Conduct model optimisation, variance, and time‑series analysis; automate monitoring dashboards.
- Create explainable AI artefacts to diagnose risk changes and support regulatory reporting.
- Build reusable data‑science frameworks to accelerate model deployment.
- Lead product life‑cycle from ideation to launch, ensuring post‑launch performance targets.
- Engage with senior leadership, business, risk, compliance, and ops to set priorities and achieve consensus.
- Enforce responsible AI practices, data governance, privacy and fairness in fully regulated settings.
**Required Skills:**
- 5–8 years deployment of ML/Gen AI in production.
- Deep quantitative techniques: probability, statistics, numerical computing.
- Proven MLOps expertise: model deployment, versioning, lifecycle management, drift detection and correction.
- Proficiency with scikit‑learn, XGBoost, LightGBM, PyTorch, TensorFlow, Pandas, NumPy.
- Experience with MLOps tools: MLflow, Airflow; database knowledge: Neo4j, MongoDB; API: FastAPI.
- Knowledge of RAG, LLMs, and NLP for generative AI applications.
- Strong communication, presentation, and stakeholder‑management skills.
- Ability to work in highly regulated, regulated financial or credit‑risk environments.
**Required Education & Certifications:**
- Master’s degree in Data Science, Computer Science, Statistics, Applied Mathematics, or a related quantitative field.
- Certifications in MLOps, machine‑learning, or relevant AI platforms are a plus.