Über
This role focuses on two key pathways:
Machine Learning (ML):
Specialising in advanced ML algorithms and MLOps practices.
Generative AI (Gen AI):
Focusing on deploying Retrieval‑Augmented Generation (RAG) workflows and managing Large Language Model (LLM) applications.
What You’ll Do As a Senior Data Scientist at Synechron, you will operate as a vital contributor, overseeing the full lifecycle of Data and AI products within a dynamic financial environment. Your core responsibilities include:
Advanced Data Analysis & Modeling:
Uncover hidden patterns and develop insights pertinent to Credit Risk via sophisticated statistical, quantitative, and machine learning techniques.
Generative AI Applications:
Leverage unstructured data, NLP, and LLMs to automate data lineage modeling and documentation processes.
Model Optimisation & Monitoring:
Enhance model performance, detect anomalies, conduct variance and time‑series analysis, and develop automated solutions for model monitoring—covering data drift and correction strategies.
Explainable AI for Risk:
Apply advanced analytics to interpret root causes behind changes in pre‑settlement risk.
Framework Development:
Build scalable, reusable data science frameworks enabling efficient deployment of financial models.
Strategic Product Leadership:
Lead end‑to‑end product lifecycle—from ideation and requirements to development, launch, and post‑launch performance management.
Stakeholder Collaboration:
Partner with senior leadership, business units, tech teams, risk, compliance, and operations to gather requirements, align priorities, and drive consensus.
Responsible AI & Governance:
Ensure your solutions comply with strict risk, privacy, and ethical standards, including data governance and fairness in highly regulated financial settings.
Key Technologies & Tools
Databases:
Neo4j, MongoDB
API Development:
FastAPI
Big Data (Beneficial):
Apache Hadoop, Apache Spark (PySpark)
What We Need From You
5‑8 years of hands‑on experience developing and deploying ML and/or Gen AI solutions in production.
Deep expertise in quantitative methods, probability, statistics, and numerical computing.
Proven MLOps proficiency—model deployment, versioning, lifecycle management, and data drift monitoring/correction.
Experience working in a highly regulated environment, with a bonus for Financial or Credit Risk industry exposure.
Exceptional communication, presentation, and stakeholder management skills—ability to influence across diverse teams.
Master’s degree in Data Science, Computer Science, or a related quantitative discipline.
#J-18808-Ljbffr
Sprachkenntnisse
- English
Hinweis für Nutzer
Dieses Stellenangebot stammt von einer Partnerplattform von TieTalent. Klicken Sie auf „Jetzt Bewerben“, um Ihre Bewerbung direkt auf deren Website einzureichen.