Lead - Business Data Analytics, Insights & AI

Job Description

Job Description

The Crosby Company of New Hampshire is a single-family office dedicated to the long-term stewardship, management, and preservation of family assets. The Crosby Company of New Hampshire provides administrative and advisory services including investment, finance, technology, risk management, human resources, compliance, curatorial, and trust oversight services to various family office entities.

The Crosby Company of New Hampshire (CCNH) Technology team is a trusted service provider and strategic partner to CCNH and its business leaders. Team members possess a deep understanding of enterprise business processes, maintain strong relationships with key stakeholders across the organization, and demonstrate the ability to operate at both strategic and tactical levels.

The Lead Business Analytics, Insights & AI role is a senior-level position responsible for defining, establishing, and executing CCNH’s enterprise data insights strategy. This role will lead the adoption and effective use of a new enterprise data lake built on Microsoft Fabric , ensuring high-quality, trusted, and well-governed data is used consistently across five core business departments.

This role will champion a data-driven culture by enabling advanced analytics, self-service reporting, and actionable insights that improve decision-making, operational efficiency, and strategic outcomes. The Lead Business Analytics & Insights professional will manage a small team of data and reporting analysts, providing technical leadership, coaching, and direction while serving as a key advisor to business and technology leadership.

Successful candidate in this role will be chartered to establish and scale a center of excellence (COEs) for tools like PowerBI for analytics and insights, Synapse for AI and Data Science, and frameworks for Data Lifecycle Management & Operations.

POSITION DUTIES / ACCOUNTABILITIES: Work as a leader of cross-functional technology and business teams to deliver and mature CCNH’s enterprise analytics and insights capabilities.

• Data & Analytics Strategy
  • Define and own the enterprise data insights strategy , aligning analytics initiatives with business priorities across five departments.
  • Establish a roadmap for analytics maturity, including descriptive, diagnostic, predictive, and prescriptive analytics.
  • Partner with business leaders to translate strategic objectives into measurable analytics use cases.

• Microsoft Fabric & Data Lake Adoption
  • Lead adoption of the Microsoft Fabric data platform, ensuring consistent design patterns, best practices, and scalable architecture.
  • Oversee integration of structured and unstructured data sources into the enterprise data lake.
  • Ensure semantic models and data products are designed to support enterprise reporting, analytics, and self-service consumption
• Data Quality, Governance & Trust
  • Champion the use of high-quality, trusted data across the organization.
  • Partner with data governance stakeholders to define and enforce standards related to data quality, lineage, security, and access.
  • Establish data quality monitoring, validation, and remediation practices.
  • Promote consistent definitions, KPIs, and metrics across departments.
• Analytics Delivery & Enablement
  • Oversee development of executive, operational, and analytical dashboards using Power BI.
  • Enable and scale self-service analytics through governed datasets, documentation, and user enablement.
  • Serve as an analytics thought partner to business leadership, delivering insights that drive measurable business outcomes.
  • Support external audit or regulatory reviews related to analytics, reporting, and data platforms as required.
• People Leadership & Collaboration
  • Lead, coach, and develop a small team of data and reporting analysts.
  • Set clear priorities, goals, and performance expectations for the team.
  • Foster a collaborative, continuous-learning environment focused on innovation and improvement.
  • Work closely with IT, Finance, Operations, and other business teams to ensure analytics solutions meet enterprise needs.

QUALIFICATIONS:

• Bachelor’s degree in Information Systems, Data Analytics, Computer Science, Business Analytics, or a related field required.
• Master’s degree preferred.
• 8+ years of progressive experience in data analytics, business intelligence, or data platform roles.
• 3+ years of experience in a technical or analytics leadership role, including direct people management.
• Demonstrated experience leading enterprise analytics initiatives and data platform adoption
• Strong expertise in modern data platforms and lakehouse architectures, with hands-on experience in Microsoft Fabric or similar cloud platforms. Familiarity with enterprise data lakes and cloud data platforms, such as Snowflake, is highly desirable.
• Ability to guide business teams in leveraging LLMs for productivity, insights, and workflow automation.
• Advanced experience with Power BI , including semantic modeling, performance optimization, and enterprise reporting standards.
• Proven background in dimensional data modeling and analytics-ready data design.
• Strong SQL skills; Python experience preferred.
• Deep understanding of data governance, data quality management, and master/metadata concepts.
• Ability to translate complex data into clear, actionable insights for executive and non-technical audience.
• Experience operating in agile delivery environments (Scrum, Kanban); familiarity with Jira or similar tools preferred.
• Demonstrated ability to influence without authority and drive adoption across multiple departments.
• Excellent strategic thinking, problem-solving, and prioritization skills.
• Experience working with integrated enterprise data in cross-functional teams, skillfully evaluating alternative solutions and recommending optimal approaches
• Data modeling with Power Designer or similar tools would be a plus.
• Ability to identify, evaluate, and prioritize AI / ML use cases across business domains (predictive analytics, decision intelligence, automation, risk detection, etc.).
• Understanding of LLM governance, including model safety, bias detection, confidentiality controls, and appropriate enterprise use cases.
• Results-oriented leader with a strong sense of ownership and accountability.
• Excellent interpersonal, written, and verbal communication skills.
• Ability to balance strategic vision with hands-on execution.
• Comfortable navigating ambiguity and change in a fast-paced environment.
• Strong collaboration skills and ability to build trusted partnerships across the organization.
• High attention to detail while maintaining an enterprise-level perspective.
• Ability and experience in establishing COEs