We are looking for 8+ years experienced candidates for this role.
- A minimum of 8 years of professional experience, with at least 6 years in a data science role.
- Strong knowledge of statistical modeling, machine learning, deep learning and GenAI.
- Proficiency in Python and hands on experience optimizing code for performance.
- Experience with data preprocessing, feature engineering, data visualization and hyperparameter tuning.
- Solid understanding of database concepts and experience working with large datasets.
- Experience deploying and scaling machine learning models in a production environment.
- Familiarity with machine learning operations (MLOps) and related tools.
- Good understanding of Generative AI concepts and LLM finetuning.
- Excellent communication and collaboration skills.
Responsibilities
- Lead a high performance team, guide and mentor them on the latest technology landscape, patterns and design standards and prepare them to take on new roles and responsibilities.
- Provide strategic direction and technical leadership for AI initiatives, guiding the team in designing and implementing state-of-the-art AI solutions.
- Lead the design and architecture of complex AI systems, ensuring scalability, reliability, and performance.
- Lead the development and deployment of machine learning/deep learning models to address key business challenges.
- Apply statistical modeling, data preprocessing, feature engineering, machine learning, and deep learning techniques to build and improve models.
- Utilize expertise in at least two of the following areas: computer vision, predictive analytics, natural language processing, time series analysis, recommendation systems.
- Design, implement, and optimize data pipelines for model training and deployment.
- Experience with model serving frameworks (e.g., TensorFlow Serving, TorchServe, KServe, or similar).
- Design and implement APIs for model serving and integration with other systems.
- Collaborate with cross-functional teams to define project requirements, develop solutions, and communicate results.
- Mentor junior data scientists, providing guidance on technical skills and project execution.
- Stay up-to-date with the latest advancements in data science and machine learning, particularly in generative AI, and evaluate their potential applications.
- Communicate complex technical concepts and analytical findings to both technical and non-technical audiences.
- Serves as a primary point of contact for client managers and liaises frequently with internal stakeholders to gather data or inputs needed for project work