Job DescriptionYour 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.
Your Profile:- Bachelor's degree in Data Science, Machine Learning, Computer Science, Statistics, or a related field. Master's degree or Ph.D. is a plus.
- 7+ years of experience in data science, machine learning, or AI, with demonstrated success in building models that drive business outcomes.
- 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
#IncludingYouDiversity, equity, inclusion and belonging are cornerstones of ADM's efforts to continue innovating, driving growth, and delivering outstanding performance. We are committed to attracting and retaining a diverse workforce and create welcoming, truly inclusive work environments - environments that enable every ADM colleague to feel comfortable on the job, make meaningful contributions to our success, and grow their career. We respect and value the unique backgrounds and experiences that each person can bring to ADM because we know that diversity of perspectives makes us better, together.
For more information regarding our efforts to advance Diversity, Equity, Inclusion & Belonging, please visit our website here: Culture, Engagement & Inclusion | ADM.