Senior Data Analyst

About the Team:

The Data & Analytics team works across AlphaSense to make data an asset for growth. We do that through infrastructure, process, well-modeled and documented data, analysis, and deep partnership with the business. We own and manage the data stack, consisting of Fivetran, Stitch, dbt, BigQuery and Tableau. In addition to technical leadership, we partner across departments to raise the analytics bar, drive operational improvement, and support growth. Our work spans BI dashboards for business and executive users, ML models for critical business challenges, and data & infrastructure to support our AI engineers. 

About the Role: 

This Data Analyst will be a critical member of the team as we build data models, reporting and dashboards, and deliver deep insights aimed at accelerating the growth of the company on our way toward a successful IPO. This role will partner with people across the company (Product Engineering, AI Research, Content, Sales, Revenue Operations, Marketing, Finance, etc.) to tackle key strategic, operational, and technical initiatives while building systems that will help us scale.

If you excel at anticipating and keenly understanding the needs of your stakeholders, delivering tailored, impactful solutions, transforming complex data into meaningful insights, and have strong expertise in SQL and data visualization, we'd love to talk to you! This role is ideal for someone who thrives in environments that require critical thinking and proactive problem-solving, enjoys collaborating across teams, has a knack for simplifying complex concepts, and is eager to take ownership in driving impactful data-driven decisions within a dynamic and evolving business landscape.

The minimum qualifications for this role include: 

• 8+ years of experience in data analytics, which may include formal education.
• 3+ years of demonstrated experience developing and validating SQL queries to support analyses, reporting, and dashboards, with the ability to derive insights and craft strategies or narratives from large and complex data sets.
• 2+ years of applied experience in data visualization software such as Tableau, Looker, PowerBl, or another data visualization tool, with demonstrated proficiency creating compelling narratives and presentations that convey complex data insights to a non-technical audience (i.e., storytelling with data).
• Experience collaborating closely with data engineering teams, ensuring seamless data integration, pipeline development, and maintaining data quality for analytical purposes.
• Experience collaborating deeply across an organization to understand department process, needs, and goals, and building custom analysis/reporting to match.
• Capable of seamlessly switching “altitude” between specific technical questions and broad org-level KPIs/strategies.
• Possesses a growth mindset, with the passion to be challenged, learn from setbacks, and apply those lessons to drive business impact.

Preferred qualifications for this role include:

• Experience in the SaaS industry or working with subscription revenue business models.
• Knowledge of version control systems, such as GitHub, for managing and collaborating on data projects.
• Experience with Python for programmatic data analysis.
• Experience with data modeling tools (LookML, dbt, Dataform). 

What You’ll Do: 

• Analyze business performance and develop metrics, reports, and dashboards that inform our business strategy and drive action. 
• Exercise your creativity by finding hidden patterns in our data and relaying those discoveries to stakeholders with stunning dashboards.
• Conduct data deep-diving to understand the underlying drivers of key trends and outcomes. 
• Collaborate closely with cross-functional teams across AlphaSense to understand their analytical needs and deliver data-driven insights and recommendations.
• Assess needs and resources to build deliverables that address the needs of a variety of analytics personas. 
• Support the “single source of truth” for the organization through creating and maintaining data models for use by other teams and by identifying and correcting data gaps, inconsistencies, etc.
• Conduct open-ended exploratory data analysis to uncover actionable insights, validate hypotheses, and significantly guide the prioritization of business initiatives.
• Provide peer review and mentorship of colleagues and their work to maintain a high standard of quality, accuracy, and knowledge across the team.
• Onboard new technical and business users onto our data systems, tools, and business intelligence approaches.
• Roll out analytics systems and processes throughout the organization.
• Identify opportunities for better tooling, data systems, and processes to help improve operations and drive growth.