Data Scientist [T500-22493]

About ADM:

We are one of the world’s largest nutrition companies and a global leader in human and animal nutrition. We unlock the power of nature to provide nourishing quality of life by transforming crops into ingredients and solutions for foods, beverages, supplements, livestock, aquaculture, and pets.

About ADM India Hub:

At ADM, we have long recognized the strength and potential of India’s talent pool, which is why we have maintained a presence in the country for more than 25 years. Building on this foundation, we have now established ADM India Hub, our first GCC in India.

At ADM India Hub, we are hiring for IT and finance roles across diverse technology and business functions. We stand at the intersection of global expertise and local excellence, enabling us to drive innovation and support our larger purpose of unlocking the power of nature to enrich quality of life.

Data Scientist

Bengaluru, India

Position Summary:

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.

Key Responsibilities:

• 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. Master’s 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.