Vice President, Business Intelligence / Data & Analytics

Location: Remote - United States

Reports to: CFO

About AlphaSense: 

The world’s most sophisticated companies rely on AlphaSense to remove uncertainty from decision-making. With market intelligence and search built on proven AI, AlphaSense delivers insights that matter from content you can trust. Our universe of public and private content includes equity research, company filings, event transcripts, expert calls, news, trade journals, and clients’ own research content. Our platform is trusted by over 4,000 enterprise customers, including a majority of the S&P 500.

Founded in 2011, AlphaSense is headquartered in New York City with over 1,500 people across the globe and offices in the U.S., U.K., Finland, India, and Singapore. Come Join Us!

About the Role: 

As the Vice President of Business Intelligence/Data & Analytics at AlphaSense, you will be pivotal in shaping and executing AlphaSense’s data strategy to drive business growth and innovation.

Who You Are:

• Qualifications:
  • Bachelor's degree in Computer Science, Information Systems, Statistics, Mathematics, Data Science, or a related field. A Master's degree or MBA is often preferred.
  • 10+ years of experience in data and analytics, with a proven track record of leadership in a similar role, preferably within the SaaS or technology industry.
  • Experience managing and leading a high-performing data and analytics team.
  Technical Skills:
  • Proficiency in data warehousing, ETL processes, and BI tools
  • Strong understanding of data modeling, data architecture, and database design principles.
  • Knowledge of advanced analytics techniques, machine learning, and AI/ML concepts.
  Strategic Thinking and Business Acumen:
  • Strong strategic thinking and business acumen with the ability to align data initiatives with organizational goals and drive business value.
  • Experience in budget management, resource allocation, and ROI analysis.
  • Strong analytical and problem-solving skills with the ability to translate complex data into actionable insights and recommendations.
  Leadership and Team Management:
  • Exceptional leadership and interpersonal skills with a track record of building, leading, and mentoring high-performing teams.
  • Ability to inspire and motivate team members, foster a collaborative culture, and drive excellence in performance.
  Communication Skills:
  • Excellent verbal and written communication skills with the ability to effectively communicate complex data concepts and insights to non-technical stakeholders.
  • Strong presentation skills with experience presenting to senior leadership and external stakeholders.
  Cross-functional Collaboration:
  • Proven ability to collaborate and partner effectively with other departments (e.g., product, marketing, sales, finance) to understand their data and analytics needs and deliver tailored solutions.
  Innovation and Continuous Learning:
  • Passion for innovation and staying abreast of the latest trends, technologies, and best practices in business intelligence, data analytics, and AI/ML.
  • Commitment to continuous learning and professional development to enhance skills and capabilities.
  Ethical and Compliance Orientation:
  • Strong commitment to data governance, data privacy, and compliance with relevant regulations (e.g., GDPR, CCPA).
  • Experience implementing and maintaining data governance policies and procedures.

What You’ll Do: 

• Enhance Data Strategy: Evaluate and refine the existing data strategy to ensure alignment with the company’s evolving business objectives and growth plans. Strengthen data governance, architecture, and quality standards. 
• Optimize Analytics and Insights: Enhance the existing analytics and data visualization capabilities by identifying opportunities for improvement. Develop and deploy advanced analytics tools, dashboards, and reports to provide deeper, actionable insights to stakeholders. 
• Optimize Data Infrastructure and Technologies: Assess and optimize the current data infrastructure and technologies (e.g., data warehouses, ETL processes, BI tools) to ensure scalability, reliability, and security. Implement enhancements as needed to meet the organization's growing data and analytics demands. BI stack includes (but not limited to) Stitch, GCP, BigQuery, dbt, Tableau.