Senior Software Engineer designing, building, and deploying production - grade GenAI solutions at Bank of America. Collaborating across teams to deliver AI - powered capabilities impacting traders and clients.
About the role
- Data Scientist exploring complex, high-dimensional datasets at IFF, focusing on predictive and optimization models. Collaborate across teams to enhance flavor creation insights with practical outcomes.
Responsibilities
- Explore complex, high-dimensional datasets, developing and validating predictive and optimization models.
- Collaborate closely with cross-functional experts in various fields related to flavor creation to bridge data-driven insights with practical outcomes.
- Monitor advancements in data science and ML/AI, conduct competitive analysis, and identify opportunities for innovation.
- Test new techniques, tools, and technologies to drive continuous improvement and stay current with industry & academic developments.
- Partner with operations, marketing, and R&D to understand business needs and deliver impactful, data-driven solutions.
- Explore large datasets to uncover patterns, trends, and insights that inform strategic decisions.
- Build and implement ML/AI models using leading frameworks to solve business challenges such as optimization, prediction, and forecasting.
- Document and present findings, best practices, and methodologies to foster collaboration and continuous learning.
- Work with structured and experimental datasets while adhering to data governance and compliance standards.
- Utilize cloud computing environments (AWS, Azure, Google Cloud) for scalable data solutions.
- Incorporate principles of flavor chemistry, sensory evaluation, and experimental design into data-driven approaches.
Requirements
- Master’s or Ph.D. in Data Science, Computer Science, Statistics, or a related field with strong foundations in mathematical and statistical modeling.
- Minimum 8 years of experience in data science, ML/AI, optimization techniques (e.g., linear/nonlinear programming, Bayesian optimization, or multi-objective optimization), statistical modeling, computational chemistry, or related areas.
- Hands-on experience with complex datasets, ideally within the chemical or manufacturing industry, including data preprocessing, feature engineering, and model evaluation.
- Proven expertise in experimental design and optimization of complex systems, with practical experience deploying ML/AI models using popular frameworks (TensorFlow, PyTorch, Scikit-learn, or Keras).
- Proficiency in one or more programming languages (Python or R)
- Strong understanding of statistical principles, hypothesis testing, and advanced modeling techniques; familiarity with cloud platforms (AWS, Azure, Google Cloud) is a plus.
- Ability to collaborate effectively across disciplines and work closely with subject matter experts (chemical and flavor specialists).
- Excellent communication skills—able to translate complex technical concepts for both technical and non-technical stakeholders; fluency in English required, additional languages preferred.
- Demonstrated project management skills with timely decision-making and ability to thrive in a multicultural, highly diverse environment.
- Strong customer focus, problem-solving ability, creativity, and adaptability when dealing with ambiguity.
- Drive for results and commitment to continuous learning and innovation in data science and cognitive technologies.
Benefits
- Be part of a mission-driven culture where your work truly makes a difference.
- Join a team that values individuality and fosters collaboration.
- Drive digital transformation in a global manufacturing environment.
- Access to cutting-edge technologies and tools and opportunities for learning, career advancement, and personal growth.
- Enjoy competitive compensation and benefits designed to support your well-being.
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