Data Scientist
Bengaluru, India
The Data Scientist will lead the development of data-driven solutions by leveraging traditional data science techniques and recent advancements in Generative AI to bring value to ADM. The role is integral to the Digital & Innovation team, driving rapid prototyping efforts, collaborating with cross-functional teams, and developing innovative approaches to solve business problems. This position requires a blend of expertise in traditional machine learning models, data science practices, and emerging AI technologies to create value and improve business outcomes.
- Lead end-to-end machine learning projects, from data exploration, modeling, and deployment, ensuring alignment with business objectives.
- Utilize traditional AI/data science methods (e.g., regression, classification, clustering) and advanced AI methods (e.g., neural networks, NLP) to address business problems and optimize processes.
- Implement and experiment with Generative AI models based on business needs using Prompt Engineering, Retrieval Augmented Generation (RAG) or Finetuning, using LLM's, LVM's, TTS etc.
- Collaborate with teams across Digital & Innovation, business stakeholders, software engineers, and product teams, to rapidly prototype and iterate on new models and solutions.
- Mentor and coach junior data scientists and analysts, fostering an environment of continuous learning and collaboration.
- Adapt quickly to new AI advancements and technologies, continuously learning and applying emerging methodologies to solve complex problems.
- Work closely with other teams (e.g., Cybersecurity, Cloud Engineering) to ensure the successful integration of models into production systems.
- Ensure models meet rigorous performance, accuracy, and efficiency standards, performing cross-validation, tuning, and statistical checks.
- Communicate results and insights effectively to both technical and non-technical stakeholders, delivering clear recommendations for business impact.
- Ensure adherence to data privacy, security policies, and governance standards across all data science initiatives.
- Standard Job Requirements:
- Proficient in Python, R, and SQL for data analysis, modeling, and data pipeline development.
- Experience with DevSecOps practices, and tools such as GitHub, Azure DevOps, Terraform, Bicep, AquaSec etc.
- Experience with cloud platforms (Azure, AWS, Google Cloud) and large-scale data processing tools (e.g., Hadoop, Spark).
- Strong understanding of both supervised and unsupervised learning models and techniques.
- Experience with frameworks like TensorFlow, PyTorch, and working knowledge of Generative AI models like GPT and GANs.
- Hands-on experience with Generative AI techniques, but with a balanced approach to leveraging them where they can add value.
- Proven experience in rapid prototyping and ability to iterate quickly to meet business needs in a dynamic environment.
- Educational Requirements:
- Bachelor's degree in data science, Machine Learning, Computer Science, Statistics, or a related field. Masters degree or Ph.D. is a plus.
- 4+ years of experience in data science, machine learning, or AI, with demonstrated success in building models that drive business outcomes.
