Data Science Manager

5 days ago

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Key Responsibilities:•Technical Strategy & Roadmap: Define and execute comprehensive ML/AI strategyaligned with business objectives, including LLM infrastructure, retrieval pipelines, andgenerative workflows•Architecture Oversight: Lead system architecture decisions for scalable ML platforms,ensuring robust model deployment and operational excellence•Cross-functional Collaboration: Partner closely with product management, engineering,and business stakeholders to translate requirements into technical solutions•Model Development: Actively participate in designing, training, and optimizing machinelearning models, maintaining technical currency with 20-30% hands-on contribution•Code Reviews & Technical Guidance: Conduct thorough code reviews and providetechnical mentorship to ensure engineering excellence across the team•Team Building: Recruit, hire, and develop top-tier ML engineers, data scientists, andresearchers while fostering a culture of innovation and continuous learnin•Mentorship: Guide team members through complex technical challenges, careerdevelopment, and best practices in ML engineeringRequired Skills:Programming Proficiency: Expert-level skills in Python, R, with deep knowledge of ML frameworks(TensorFlow, PyTorch, Scikit-learn, Pandas, NumPy)Machine Learning: Extensive experience with statistical modeling, deep learning, NLP, computervision, and generative AI technologiesInfrastructure & Deployment: Hands-on experience with cloud platforms (AWS, Azure, GCP),containerization (Docker, Kubernetes), and ML pipeline orchestrationData Engineering: Strong understanding of data architectures, feature engineering, and big datatechnologies (Spark, Hadoop, Kafka)Programming Proficiency: Expert-level skills in Python, R, with deep knowledge of ML frameworks(TensorFlow, PyTorch, Scikit-learn, Pandas, NumPy)Leadership Skills: Strong leadership abilities to guide technical teams and communicate effectivelywith non-technical stakeholders.Problem-Solving Abilities: Excellent analytical skills to address complex technical challenges anddevise innovative solutions.Background in building and scaling ML platforms in high-growth technology companies

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