Suggested rewrite: Led a cross-functional initiative that improved [business outcome] by [measurable result], demonstrating experience relevant to this role...
Associate Director, Content Business Analysis
- Remote from
- USA
- Salary
- USD 172,994–233k / yr
- Department
- Data Science & Analytics
- Employment
- Full Time
- Experience
- Director
- Published
- Apply before
- 9 Dec 2026
- Listing views
- 16
- Application actions
- 1
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About this role.
About AlphaSense:
AlphaSense is the AI platform redefining market intelligence and workflow orchestration, trusted by thousands of leading organizations to drive faster, more confident decisions in business and finance. The platform combines domain-specific AI with a vast content universe of over 500 million premium business documents — including equity research, earnings calls, expert interviews, filings, news, and internal proprietary content. Purpose-built for speed, accuracy, and enterprise-grade security, AlphaSense helps teams extract critical insights, uncover market-moving trends, and automate complex workflows with high-quality outputs. With AI solutions like Generative Search, Generative Grid, and Deep Research, AlphaSense delivers the clarity and depth professionals need to navigate complexity and obtain accurate, real-time information quickly. For more information, visit www.alpha-sense.com. Come join us.
AlphaSense Inc seeks Assoc. Director, Content Business Analysis in New York, NY.
Duties:
- Analytics (15%): Execute complex strategic analytics and business intelligence projects that provide growth opportunities and data driven insights to support content leadership decisions. Collect, analyze, and interpret large datasets related to product usage, customer behavior, revenue performance, and market trends to identify opportunities for growth, operational efficiency, and product innovation.
- Product Performance (15%): Provide strategic guidance on performance measurement frameworks and establish product performance metrics, user engagement, adoption, retention, and revenue performance, customer engagement, and key performance indicators (KPIs) including annual R&D spend, gross margin by product line, customer acquisition cost payback, and content cost ratios.
- Robust Data Infrastructure (15%): Design and implement scalable data infrastructure and analytics processes to improve data accessibility, reporting accuracy, and decision-making capabilities across business functions. Establish data governance standards and ensure data quality across internal systems and third-party data sources.
- Data Analysis (15%): Analyze platform usage patterns and customer segmentation data to recommend strategies for optimizing feature access and usage-based provisioning models. Work with Product, RevOps, and Finance teams to improve cost efficiency by aligning feature availability and infrastructure utilization with customer usage patterns and revenue contribution.
- Royalty Reporting (10%): Collaborate with Finance and Business intelligence teams to build a robust royalty reporting framework, ensuring consistent, compliant and true reporting and payouts to vendor partners.
- Democratize Data (15%): Partner with Product Management, Engineering, Revenue Operations, and Finance teams to define analytics requirements and ensure alignment between business objectives and product development priorities. Collaborate cross-functionally to monitor the provisioning and rollout of platform features and data products, ensuring efficient resource allocation and alignment with customer demand.
- Dashboarding (15%): Develop and maintain advanced analytical models, executive-level dashboards, and reporting frameworks to monitor key business metrics and present actionable insights and strategic recommendations to senior leadership to inform business planning, resource allocation, and performance optimization.
Requires a Bachelor’s or foreign equivalent degree in Business Analytics, Data Science, Economics, Finance, Statistics, or a related quantitative field, and 4 years of experience in the job offered or in a business analytics, strategic analysis, or data-driven business strategy-related role.
Position requires experience in each of the following skills:
- SQL and data analysis tools including Python and R
- Business intelligence dashboards and data visualization reports using Tableau, Looker, Power BI, Google Data Studio, or BigQuery
- Financial modeling and ROI analysis
- Customer usage analysis, segmentation, and behavioral analytics
- Collaborating with cross-functional teams including Product Management, Engineering, Revenue Operations, and Finance to translate data insights into strategic initiatives
- Designing data-driven performance metrics and KPIs used to monitor business performance and inform executive decision-making
- Jira or Linear for program and task tracking, including creating and managing issues, epics, workflows, and dependency tracking across multiple teams
- Confluence or Notion to create and maintain structured program documentation, governance materials, meeting records, and decision logs
- Google Sheets, Microsoft Excel, or Airtable – Performing quantitative analysis using formulas, pivot tables, data reconciliation, and operational reporting
- Application Programming Interface (API)–Based Data Workflows
- JavaScript Object Notation (JSON) and Extensible Markup Language (XML) – Reviewing and interpreting JSON and XML data structures used in financial content feeds or data delivery workflows.
Full-time Telecommuting permitted.
International travel required up to 5% to travel to any of our current office locations including Singapore, Bangalore, Pune, New Delhi, Finland, London, Waterford (Ireland), NYC, Chicago, and Vancouver for offsite strategy meetings, all-hands, and product or sales kickoffs 2-3 times per year abroad.
40 hours/week. $172,994/yr. – $233,000/yr. Must also have authority to work permanently in the U.S. Applicants who are interested in this position may apply at https://www.jobpostingtoday.com/ Ref #26920.
For base compensation, we set standard ranges for all roles based on function and level benchmarked against similar stage growth companies and internal comparables. In order to be compliant with local legislation, as well as to provide greater transparency to candidates, we share salary ranges on all job postings regardless of desired hiring location. Final offer amounts are determined by multiple factors including candidate experience/expertise and may vary from the amounts listed below.
You may also be offered a performance-based bonus, equity, and a generous benefits program.
Base Compensation Range
$275,000—$290,000 USD
AlphaSense is an equal-opportunity employer. We are committed to a work environment that supports, inspires, and respects all individuals. All employees share in the responsibility for fulfilling AlphaSense’s commitment to equal employment opportunity. AlphaSense does not discriminate against any employee or applicant on the basis of race, color, sex (including pregnancy), national origin, age, religion, marital status, sexual orientation, gender identity, gender expression, military or veteran status, disability, or any other non-merit factor. This policy applies to every aspect of employment at AlphaSense, including recruitment, hiring, training, advancement, and termination.
In addition, it is the policy of AlphaSense to provide reasonable accommodation to qualified employees who have protected disabilities to the extent required by applicable laws, regulations, and ordinances where a particular employee works.
Recruiting Scams and Fraud
We at AlphaSense have been made aware of fraudulent job postings and individuals impersonating AlphaSense recruiters. These scams may involve fake job offers, requests for sensitive personal information, or demands for payment. Please note:
- AlphaSense never asks candidates to pay for job applications, equipment, or training.
- All official communications will come from an @alpha-sense.com email address.
- If you’re unsure about a job posting or recruiter, verify it on our Careers page.
If you believe you’ve been targeted by a scam or have any doubts regarding the authenticity of any job listing purportedly from or on behalf of AlphaSense please contact us. Your security and trust matter to us.
This job listing has been manually reviewed by the Jobicy Trust & Safety Team for compliance with our posting guidelines, including verification of the company's legitimacy, accuracy of job details, clarity of remote work policy, and absence of misleading or fraudulent content.
Role DNA
A quick view of the complexity, pace, ownership and collaboration implied by the job description.
Pace & Pressure
4/5Autonomy Level
5/5Communication Load
5/5Core skills
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Sample interview questions
I would start by aligning business goals with a metric tree covering adoption, engagement, retention, monetization, content cost, and customer outcomes. I would define metric ownership, data sources, calculation logic, targets, and dashboard cadences, then validate the framework with Product, Finance, and Revenue Operations stakeholders.
I would segment customers by plan, usage intensity, feature adoption, revenue contribution, and retention risk. I would analyze feature utilization against infrastructure and content costs, identify underused or high-value features, and recommend entitlement, packaging, or enablement changes supported by controlled experiments.
I establish governed metric definitions, documented lineage, automated data-quality checks, reconciliation against financial systems, and clear ownership for each source. Before publishing, I validate material changes with functional stakeholders and provide concise annotations for assumptions, refresh timing, and known limitations.
I would map contractual reporting requirements, source systems, data transformations, calculation rules, approval controls, and payout timelines. I would implement auditable data pipelines and reconciliations, retain decision logs, and partner with Finance and Business Intelligence to address exceptions before payouts are finalized.
I begin with the decision required rather than the dataset, summarize the key finding and financial or operational impact, and present a limited set of practical options with trade-offs. I support the recommendation with transparent methodology, sensitivity analysis where relevant, and a clear owner and next step.
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