About the Role

As a Data Scientist specializing in Generative AI within the Business Technology team, you will focus on analyzing available data to determine the most relevant inputs for developing models that drive specific business outcomes. You will work closely with cross-functional teams to understand the data needs for building efficient models, such as those used in document processing, classification, scoring, and more, ensuring that the AI solutions meet the intended objectives. You will play a pivotal role in defining the Generative AI strategy in conjunction with business leaders and product owners.

What the Candidate Will Need / Bonus Points

---- What the Candidate Will Do ----

1. Analyze Available Data: Examine and evaluate existing datasets to determine their suitability for use in AI models, ensuring that the selected data will drive efficient and accurate outcomes.
2. Data-Driven Model Development: Collaborate with cross-functional teams to understand specific use cases and identify the appropriate data inputs for models focused on document processing, classification, scoring, and other related applications.
3. Outcome-Focused AI Implementation: Work with stakeholders to define success metrics and ensure that AI models are designed with the right data to achieve targeted business outcomes.
4. Model Optimization: Continuously assess the performance of AI models, making adjustments to data inputs and algorithms as needed to maintain alignment with desired outcomes.
5. Monitoring - Continuously monitor and improve the performance, reliability, and scalability of AI models and systems, implement Observability for AI solution
6. Cross-functional Collaboration: Partner with data engineers, domain experts, and other stakeholders to ensure that AI models are integrated effectively into business processes and that the right data is used for each application.
7. Outcome Reporting: Develop reports or dashboards that track the performance of AI models, providing insights into how data inputs are impacting outcomes.
8. Mentorship: Provide guidance to junior data scientists on best practices for data selection and analysis in AI model development.

1. Educational Background: Master's or Ph.D. in Computer Science, Data Science, Machine Learning, Statistics, or a related field.
2. Experience:
3. Minimum of 3-5 years of experience in data science with a focus on machine learning, Generative AI, and data analysis.
4. Proven experience in developing AI models that are aligned with measurable business outcomes, particularly in applications such as document processing, classification, and scoring.
5. Technical Skills:
6. Proficiency in programming languages such as Python, R, or Julia.
7. Proven 5+ years of experience in developing and deploying ML/AI models and 2+ years of experience in developing and deploying generative AI models.
8. Strong background in deep learning frameworks such as TensorFlow, PyTorch, or similar.
9. Experience with advanced Retrieval-Augmented Generation (RAG) techniques, particularly for processing large documents.
10. Familiarity with natural language processing (NLP) and computer vision
11. Strong understanding of model development, including those for document processing, classification, and scoring, and the selection of appropriate data inputs.
12. Familiarity with cloud platforms such as AWS, GCP, or Azure for deploying AI models.
13. A deep passion for AI and its potential to solve complex problems, with a continuous desire to learn and innovate
14. Analytical Skills: Strong analytical mindset with the ability to determine the best data inputs for achieving specific business goals.
15. Communication Skills: Excellent communication skills, with the ability to articulate data-driven insights and recommendations to non-technical stakeholders.

1. Experience collaborating with operations teams in SG&A domains for workflow optimization
2. Experience in working within the Business technology domain which has a combination of 3P and homegrown solutions