Business Insights and Analytics Manager

Business Insights and Analytics Manager Job Summary The Business Insights and Analytics Manager will establish and lead the organization’s enterprise analytics capability by transforming trusted, multi-source business data into actionable insights, predictive models, executive dashboards, and decision-support solutions. The role will provide strategic direction for analytics across revenue and sales performance, marketing and growth, client technical support and lifecycle management, internal business operations, and enterprise data governance. The successful candidate will lead and develop the analytics team, collaborate closely with business and technology stakeholders, and ensure that data products are accurate, secure, well-documented, scalable, and aligned with data privacy, quality, and governance standards. The role will also champion the adoption of AI, machine learning, self-service analytics, and modern data operations to improve business performance, operational efficiency, customer retention, and management decision-making. Key ResponsibilitiesStrategy, Leadership & Analytics Delivery Define and execute the enterprise data and analytics roadmap in alignment with business objectives. Lead, mentor, and develop a high-performing team of data analysts and BI professionals. Translate business questions and requirements into scalable analytics solutions. Provide strategic insights and data-driven recommendations to senior management and business leaders. Prioritize and manage analytics projects and deliverables across multiple stakeholders. Establish best practices for analytics development, documentation, reporting, and self-service analytics. Technical & Data Analytics Oversight Oversee data architecture, analytics pipelines, BI platforms, and reporting solutions to ensure accuracy, reliability, and scalability. Partner with Data Engineering and Architecture teams to define data requirements and ensure the availability and quality of required source data. Promote the use of standardized and trusted enterprise data models for analytics and reporting. Ensure analytics solutions comply with data privacy, security, quality, and governance requirements. Revenue & Sales Analytics Develop and maintain analytical models for B2B sales pipeline health, win/loss ratios, deal velocity, and sales performance. Build data-driven revenue forecasting and projection models. Identify opportunities for cross-selling, upselling, and account growth within enterprise clients. Analyze pricing, discounts, contract profitability, and margins, including ARPA, to support commercial decision-making. Growth & Marketing Analytics Oversee marketing performance and attribution analytics across campaigns, ABM, sales funnels, CRM, digital channels, and marketing automation platforms. Measure marketing contribution to pipeline, conversion, and revenue outcomes. Analyze digital performance, content effectiveness, brand sentiment, media coverage, social listening, and competitive share of voice. Lead market research, customer insights, and competitive intelligence initiatives. Translate market and customer data into strategic recommendations and growth opportunities. Client Support & Customer Lifecycle Analytics Analyze support ticket volumes, resolution times, MTTR, SLA performance, and operational bottlenecks. Develop analytics to improve client technical support efficiency and service delivery. Monitor contract expirations, maintenance agreements, hardware/software warranties, and software renewals. Develop customer health scoring models using product usage, support history, engagement, and other relevant data. Develop predictive analytics to identify churn risks and support customer retention strategies. Internal Business Operations & Executive Reporting Identify operational bottlenecks, resource utilization issues, and process inefficiencies across business units. Lead the development and maintenance of standardized, automated executive dashboards using platforms such as Power BI or Tableau. Deliver clear and actionable reports for Senior Management and C-Suite stakeholders. Conduct ad-hoc and exploratory analyses to address critical business and operational questions. Translate complex data into clear, concise, and business-focused recommendations. Data Governance & Quality Establish and enforce standards for data quality, documentation, usage, and analytics development. Ensure responsible consumption of standardized enterprise data models. Work closely with governance, risk, compliance, and technology teams to maintain data privacy and security standards. Promote consistent definitions, metrics, KPIs, and reporting standards across the organization. AI, Machine Learning & Data Operations Champion the adoption of AI and machine learning for predictive analytics and advanced decision support. Identify and implement practical AI use cases that improve business efficiency and organizational capabilities. Design, build, and deploy AI agents to support business processes and operational improvements. Support data management and data operations initiatives for internal and external stakeholders. QualificationsEducation Bachelor’s degree in Computer Science, Data Analytics, Business, Statistics, Information Technology, or a related field. Experience 6–8 years of experience in data analytics, business intelligence, data science, or a related field. At least 2–3 years of experience in a supervisory, management, or team leadership role. Experience working in a B2B and/or B2C corporate environment. Strong understanding of enterprise sales cycles, contract-based customer lifecycles, marketing funnels, and business operations. Technical Competencies Advanced proficiency in SQL for data extraction, transformation, and analysis. Expert-level experience with BI and data visualization platforms such as Power BI or Tableau. Experience with web analytics platforms such as Google Analytics. Strong understanding of modern data warehousing and data architecture concepts. Familiarity with platforms such as Snowflake, Databricks, BigQuery, or similar technologies. Working knowledge of Python or R for analytics and data processing. Knowledge of statistical modeling and predictive analytics. Understanding of machine learning fundamentals, including regression, classification, and clustering. Familiarity with AI tools, AI-driven analytics, and agentic AI development. Experience with CRM, marketing automation, customer support, or enterprise business systems is an advantage. Soft Skills & Leadership Competencies Excellent communication, presentation, and data storytelling skills. Ability to translate complex analytical findings into clear, actionable business recommendations. Strong stakeholder management and consultative problem-solving skills. Strong business acumen and curiosity to understand business drivers. Strategic and analytical mindset with strong attention to detail. Ability to manage multiple priorities and deliver results in a fast-paced environment. Strong leadership, coaching, mentoring, and team development capabilities. Working Conditions May require extended working hours, weekends, or holidays when necessary to meet critical project deadlines or address urgent business requirements.