Associate Manager, Enterprise Analytics, Insights

Responsibilities

• Leads, mentors, and develops a team of Data Scientists and analytics professionals
• Provides technical guidance, career development, and performance feedback
• Balances people leadership with hands‑on contributions, dedicating approximately half of the time to analytics, machine learning, and AI solution development
• Establishes team standards, workflows, and best practices
• Partners with business stakeholders to identify and prioritize high‑value analytics and AI opportunities aligned with organizational goals
• Guides the design, development, deployment, and operationalization of machine learning and LLM‑powered solutions
• Drives Generative AI use cases such as summarization, classification, embeddings, and decision support
• Enables scalable deployment through CI/CD pipelines, Airflow orchestration, and MLOps practices
• Ensures model performance, governance, and reliability
• Translates analytical outcomes into actionable business insights
• Builds executive‑ready dashboards and data storytelling capabilities using Power BI or similar tools
• Collaborates cross‑functionally with Engineering, Product, IT, and business teams
• Promotes responsible AI and data governance practices
• Drives process improvements and operational efficiencies
• Supports hiring and onboarding
• Fosters a collaborative, innovative, and continuous learning culture across the team

Requirements

• 5+ years of experience in data science, advanced analytics, AI, or related fields
• 1+ years of people leadership, technical leadership, or team lead experience preferred
• Proven experience delivering production‑grade ML or AI solutions
• Experience leading cross‑functional analytics initiatives
• Experience operationalizing GenAI or LLM‑based applications preferred
• Strong leadership and team management skills with the ability to mentor and develop high‑performing analytics teams
• Expertise in machine learning, statistical modeling, and advanced analytics techniques
• Hands‑on experience with Generative AI, Large Language Models (LLMs), and related use cases (e.g., summarization, classification, retrieval, embeddings)
• Proficiency in Python (preferred), SQL, and data manipulation frameworks (e.g., pandas, NumPy)
• Experience with ML frameworks and libraries (e.g., scikit‑learn, LightGBM, TensorFlow, PyTorch)
• Knowledge of MLOps practices, including model deployment, monitoring, CI/CD pipelines, and workflow orchestration (e.g., Airflow)
• Experience working with cloud platforms (e.g., GCP, Azure, AWS) for scalable analytics and AI solutions
• Strong data visualization and storytelling skills using tools such as Power BI, Tableau, or similar platforms
• Ability to translate complex analytical and AI concepts into clear, actionable business insights
• Strong problem‑solving and critical thinking skills with a data‑driven mindset
• Effective stakeholder management and cross‑functional collaboration skills
• Understanding of data governance, responsible AI practices, and data privacy standards
• Ability to manage multiple priorities and drive initiatives in a fast‑paced environment