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Über
An experienced Data Scientist to lead end-to-end AI/ML solution design and implementation across a range of business domains in financial services. You will be responsible for architecting robust, scalable, and secure data science solutions that drive innovation and competitive advantage in the BFSI sector. This includes selecting appropriate technologies, defining solution blueprints, ensuring production readiness, and mentoring cross-functional teams. You will work closely with stakeholders to identify high-value use cases and ensure seamless integration of models into business applications. Your deep expertise in machine learning, cloud-native architectures, MLOps practices, and financial domain knowledge will be essential to influence strategy and deliver transformative business impact
Key Skills and Responsibilities:
Architect and drive the design, development, and deployment of scalable ML/AI solutions. Lead data science teams through complete project lifecycles - from ideation to production. Define standards, best practices, and governance for AI/ML solutioning and model management. Collaborate with data engineering, MLOps, product, and business teams. Oversee integration of data science models into production systems. Evaluate and recommend ML tools, frameworks, and cloud-native solutions. Guide feature engineering, data strategy, and feature store design. Promote innovation with generative AI, reinforcement learning, and graph-based learning. Knowledge of Spark, PySpark, Scala. Experience leading CoEs or data science accelerators. Open-source contributions or published research. Qualifications:
10+ years of experience in ML/AI with at least 4 years in architectural leadership. Proficient in Python, scikit-learn, TensorFlow, PyTorch, HuggingFace. Strong BFSI domain knowledge. Experience with NLP, LLMs (GPT), and deep learning. Hands-on with MLOps pipelines and tools. Experience with graph analytics tools (Neo4j, TigerGraph, NetworkX).
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Wünschenswerte Fähigkeiten
- PySpark
- PyTorch
- Python
- Scala
- Scikit-learn
- Spark
- TensorFlow
Berufserfahrung
- Machine Learning
- Data Scientist
Sprachkenntnisse
- English
Hinweis für Nutzer
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