Data Manager Jobs

About The Position

Requirements

• Bachelor's Degree in Computer Science, Data Science, Statistics, Mathematics, Engineering, Business Analytics, Information Systems, or related field required.
• Four or more years of experience in Data Analytics, Product Analytics, Data Science, Business Intelligence, or related analytical disciplines.
• Experience working within Agile software delivery environments.
• Demonstrated success influencing cross-functional teams through data-driven recommendations.
• Experience managing complex initiatives involving multiple stakeholders and competing priorities.
• Python
• SQL
• Power BI
• Data Modeling
• APIs
• Advanced Excel
• Machine Learning
• Statistical Analysis
• Cloud Analytics Platforms (GCP/LUMI)
• AI/ML Frameworks
• Business Intelligence
• Workflow Automation
• Data Visualization

Nice To Haves

• Master's degree preferred.
• Experience with one or more of the following: Large Language Models (OpenAI, Claude)
• Retrieval Augmented Generation (RAG)
• LangChain
• LangGraph
• Vector Databases
• Embeddings (OpenAI, BGE, TF-IDF, GloVe)
• Agentic AI Frameworks
• AI Evaluation and Monitoring

Responsibilities

• Lead complex and ambiguous business problems from definition through recommendation by developing structured analytical approaches.
• Frame business questions into measurable hypotheses and identify the data required to validate assumptions.
• Conduct root cause analysis across product, operational, and portfolio performance challenges, synthesizing multiple data sources into actionable recommendations.
• Evaluate competing priorities using quantitative analysis, business context, customer impact, and strategic objectives.
• Challenge assumptions by using data to validate or disprove existing beliefs while encouraging evidence-based decision making.
• Influence product strategy by providing analytical recommendations that balance customer experience, operational efficiency, technical feasibility, and business value.
• Partner with Product Managers, Engineering, and Business stakeholders to define meaningful success metrics, KPIs, OKRs, Portfolio Metrics, Productivity Metrics, Agility Metrics, Capacity, and Demand Metrics.
• Support roadmap planning through analytical insights that inform prioritization and investment decisions.
• Participate throughout the Agile delivery lifecycle, contributing to Program Increment planning, backlog refinement, and feature prioritization.
• Translate customer, operational, and portfolio data into actionable recommendations that improve product outcomes.
• Design, develop, and deploy advanced analytics solutions using Python, Power BI, SQL, APIs, and modern cloud-based analytics platforms.
• Build and operationalize machine learning models using regression, classification, and predictive analytics techniques.
• Develop AI-powered automation workflows utilizing approved Generative AI capabilities, LLMs, Retrieval Augmented Generation (RAG), LangChain, vector databases, embeddings, and Agentic AI frameworks.
• Evaluate AI use cases based on measurable business value, scalability, and operational risk.
• Contribute to AI governance, model monitoring, and responsible AI implementation.
• Build trusted partnerships across Product, Technology, Architecture, Operations, and Business teams.
• Influence decisions through compelling storytelling, executive-ready presentations, and evidence-based recommendations.
• Facilitate discussions that align diverse stakeholder perspectives into shared priorities.
• Promote a culture where hypotheses are tested, assumptions are challenged, and decisions are grounded in data.