Synechron
Data Scientist
⭐ - Featured Role | Apply direct with Data Freelance Hub
This role is for a Senior Data Scientist with a contract length of "unknown," offering a pay rate of "unknown," based in "unknown." Key skills include advanced ML and Gen AI expertise, MLOps proficiency, and experience in regulated environments, preferably in Credit Risk. A Master's degree in a related field is required.
🌎 - Country
United Kingdom
💱 - Currency
£ GBP
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💰 - Day rate
Unknown
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🗓️ - Date
January 8, 2026
🕒 - Duration
Unknown
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🏝️ - Location
Unknown
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📄 - Contract
Unknown
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🔒 - Security
Unknown
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📍 - Location detailed
London Area, United Kingdom
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🧠 - Skills detailed
#Spark (Apache Spark) #Hadoop #Data Lineage #PySpark #TensorFlow #Apache Spark #Apache Airflow #API (Application Programming Interface) #Leadership #MLflow #Neo4J #MongoDB #Big Data #NumPy #Airflow #Computer Science #PyTorch #Statistics #Data Science #Data Manipulation #Pandas #Model Deployment #NLP (Natural Language Processing) #Monitoring #AI (Artificial Intelligence) #FastAPI #Documentation #Databases #Compliance #Scala #Deployment #ML (Machine Learning) #Data Analysis #Data Governance
Role description
Synechron UK is seeking highly experienced Senior Data Scientists to lead innovative initiatives within our Credit Risk Technology team. This critical role offers the opportunity to shape the future of data and AI products through the strategic development of cutting-edge Machine Learning (ML) and Generative AI (Gen AI) solutions.
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
• Core ML: scikit-learn, PyTorch, TensorFlow, XGBoost, LightGBM
• Data Manipulation: Pandas, NumPy, LangGraph
• MLOps & Orchestration: MLflow, Apache Airflow
• 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.
Synechron UK is seeking highly experienced Senior Data Scientists to lead innovative initiatives within our Credit Risk Technology team. This critical role offers the opportunity to shape the future of data and AI products through the strategic development of cutting-edge Machine Learning (ML) and Generative AI (Gen AI) solutions.
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
• Core ML: scikit-learn, PyTorch, TensorFlow, XGBoost, LightGBM
• Data Manipulation: Pandas, NumPy, LangGraph
• MLOps & Orchestration: MLflow, Apache Airflow
• 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.
