Data Science Manager (Solution Architect)

Key Responsibilities :

• Technical Strategy & Roadmap : Define and execute comprehensive ML / AI strategy

aligned with business objectives, including LLM infrastructure, retrieval pipelines, and

generative workflows

ensuring robust model deployment and operational excellence

and business stakeholders to translate requirements into technical solutions

learning models, maintaining technical currency with 20-30% hands-on contribution

technical mentorship to ensure engineering excellence across the team

researchers while fostering a culture of innovation and continuous learnin

development, and best practices in ML engineering

Required 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, computer

vision, and generative AI technologies

Infrastructure & Deployment : Hands-on experience with cloud platforms (AWS, Azure, GCP),

containerization (Docker, Kubernetes), and ML pipeline orchestration

Data Engineering : Strong understanding of data architectures, feature engineering, and big data

technologies (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 effectively

with non-technical stakeholders.

Problem-Solving Abilities : Excellent analytical skills to address complex technical challenges and

devise innovative solutions.