Introduction
Join us at AIT, where we believe every day presents an opportunity to make a global impact! We’re problem solvers, driven by our curiosity and creativity, in endless pursuit of solutions for our customers. Together, we champion the strength of our global teams. And, as trusted advisors, we go above and beyond, working together in a supportive and collaborative environment to ensure customer satisfaction. Through the company's continued growth, we challenge ourselves to be better, continuously learning and growing in our dynamic environment. Helping others is at the core of our culture, join us in finding fulfillment by giving back to our local communities as the united team that is AIT. Find out what our people deliver.® means when you come move the world with us! Hear directly from our teammates at AIT Worldwide Logistics and make us the next stop on your career journey.
Overview
The Senior Manager, AI & Data Science is responsible for assessing existing data and processing ecosystems while collaborating with IT and business teams to develop AI, Generative AI (GenAI), Machine Learning (ML), and Deep Learning (DL) programs. This role is critical in designing predictive models and strategies that enhance business capabilities, drive customer growth, and create value through AI-driven solutions.
Responsibilities
- AI & ML Strategy Development: Partner with Business and IT enterprise architecture teams to design and implement AI/ML solutions. Lead the development of custom ML, GenAI, NLP, and Large Language Models (LLMs) for batch and stream processing AI/ML pipelines. Oversee model components, including data ingestion, preprocessing, search and retrieval, Retrieval-Augmented Generation (RAG), NLP/LLM development, fine-tuning, and prompt engineering, ensuring technical and business alignment.
- Model Deployment & Performance Optimization: Lead the deployment of NLP, LLM, and GenAI models in production environments in collaboration with the MLOps team to ensure scalability and reliability. Establish frameworks for model evaluation, working alongside data scientists to develop robust validation tools that assess performance, accuracy, consistency, and reliability throughout development and user acceptance testing (UAT). Optimize models to enhance efficiency and maintain performance at scale.
- AI Use Cases & Emerging Technologies: Develop AI-driven business solutions, leveraging hands-on experience with AI Agents such as ChatGPT and Copilot. Apply expertise in NLP, LLMs (extractive and generative), fine-tuning, and LLM model development, staying informed on industry trends and advancements in open-source AI platforms.
- MLOps & Data Science Lifecycle Management: Oversee the data science lifecycle, including data gathering, transformation, modeling, validation, serving, monitoring, and retraining. Ensure models adhere to industry standards, governance, and best practices in AI/ML development as outlined by senior Data Science and MLOps leadership.
- Technical Expertise & Leadership: Work with major MLOps providers and programming languages such as Python, R, SQL to develop scalable AI solutions. Lead the GenAI Community of Practice, fostering a collaborative environment to develop talent and successfully execute AI, ML, and GenAI strategies. Stay ahead of emerging technologies, innovation, and industry best practices through continuous research and development.
- Performs other duties as assigned
- Complies with all policies and standards
Qualifications
Education• Bachelor's Degree in a relevant field such as Computer Science, Mathematics, Data Science, and/or Engineering (Required) • Master's Degree in machine learning and/or AI strategy (Preferred)
Experience• 7+ years in data science, analytics, or AI/ML Gen AI (Required) • 10+ years in a leadership or managerial role ()
Knowledge, Skills, and Abilities • Technical Skills: Proficiency in Python, R, SQL, and data visualization tools (e.g., Tableau, Power BI). Deep understanding of machine learning, deep learning, NLP, and statistical modeling .Knowledge of Databricks and measurable hands-on experience with developing or tuning Large Language Models (LLM) and GenAI including RAG approaches. Experience with cloud platforms (AWS, Azure, GCP) and big data tools (Spark, Hadoop). Familiarity with MLOps, model deployment, and monitoring. High • Leadership & Strategy: Proven ability to lead cross-functional teams and mentor junior data scientists. Experience in project management, agile methodologies, and stakeholder communication. Ability to translate business problems into data science solutions. Strong storytelling and presentation skills to communicate insights to executives High • Business Acumen: Experience applying AI/ML to solve real-world business problems. Ability to drive data strategy, influence product roadmaps, and measure ROI. Familiarity with regulatory and ethical considerations in AI High
Licenses and Certifications • - Microsoft Azure AI Engineer Associate (Preferred) • - Senior Data Scientist (SDS) – DASCA (Preferred) • Certified Analytics Professional (CAP) - (Preferred)
