Data Analyst - AI-Powered Financial Research Platform

Company: Finstock, Inc.

Location: Remote - United States preferred

Workplace type: Remote

Job type: Full-time

Compensation: USD $55,000 - $80,000 annual base salary, depending on experience, technical depth, location, and role fit

Reporting line: Analytics Lead

Collaboration tools: Microsoft Teams, Outlook, Microsoft 365, GitHub, BI tools, cloud data platforms, and company-approved productivity tools

About Finstock, Inc.

Finstock, Inc. builds AI-powered financial research, trading analytics, quantitative research, and market intelligence tools for experienced market users, analysts, research teams, and institutions.

Our products rely on accurate financial data, clear analytics, reliable dashboards, thoughtful reporting, and strong collaboration across product, engineering, data, AI, and analyst teams.

About the Role

We are hiring a Data Analyst to help turn financial, product, market, and operational data into clear insights that support Finstock’s research workflows, product decisions, and market intelligence platform.

In this role, you will work with datasets related to market data, company fundamentals, user workflows, product usage, research outputs, financial analytics, and internal operations. You will build dashboards, prepare reports, validate data quality, investigate trends, and help teams make better data-informed decisions.

This is a remote role with a preference for candidates based in the United States. Candidates in other countries may be considered where Finstock, Inc. is able to engage them in compliance with applicable employment, tax, data protection, and operational requirements.

Key Responsibilities

• Analyze financial market data, product usage data, research workflow data, and internal operational datasets.
• Build and maintain dashboards, reports, tables, and recurring analytics views for product, research, AI, engineering, and leadership teams.
• Write SQL queries to extract, clean, join, validate, and analyze structured datasets.
• Monitor data quality, investigate anomalies, reconcile discrepancies, and document known limitations.
• Support financial research workflows involving equities, ETFs, indices, FX, crypto assets, commodities, macro indicators, financial statements, and company disclosures.
• Prepare clear analytical summaries, charts, and written insights for internal stakeholders.
• Analyze user behavior, feature usage, funnel performance, retention patterns, and product engagement trends.
• Collaborate with Data Engineers to improve source data quality, data models, metric definitions, and reporting reliability.
• Collaborate with Software Engineers and Product Managers to define analytics requirements for new product features.
• Collaborate with Regional Analysts to support market intelligence, company research, and cross-asset data review.
• Create and maintain documentation for metrics, dashboards, data definitions, business logic, and assumptions.
• Help identify opportunities to improve internal reporting, product analytics, research automation, and data-driven decision-making.
• Ensure analysis and reporting follow internal security, confidentiality, privacy, data licensing, and compliance requirements.

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Required Qualifications

• 2+ years of professional experience in data analysis, business intelligence, product analytics, financial analysis, analytics engineering, or a related analytical role.
• Strong proficiency in SQL.
• Strong proficiency with Excel or Google Sheets for analysis, modeling, validation, and reporting.
• Experience with BI or dashboarding tools such as Power BI, Tableau, Looker, Metabase, Mode, Superset, or similar platforms.
• Ability to analyze structured datasets and communicate findings clearly to technical and non-technical stakeholders.
• Strong understanding of data quality, metric definitions, joins, aggregations, filters, cohort analysis, and reporting logic.
• Strong attention to detail and ability to identify data inconsistencies, outliers, and misleading conclusions.
• Strong written communication skills and ability to produce clear analytical summaries.
• Ability to work independently in a remote environment and collaborate effectively across product, engineering, data, AI, and analyst teams.
• Professional commitment to data security, confidentiality, and responsible handling of financial and user-related data.
• Ability to work remotely in compliance with applicable laws and eligibility requirements.

Preferred Qualifications

• Experience working with financial market data, fintech products, investment research platforms, trading analytics, or capital markets data.
• Familiarity with equities, ETFs, indices, FX, crypto assets, commodities, financial statements, corporate actions, and macroeconomic datasets.
• Experience with Python or R for data cleaning, analysis, automation, or statistical work.
• Familiarity with dbt, data warehouses, cloud databases, analytics engineering workflows, or modern data stacks.
• Experience analyzing SaaS product metrics, user behavior, retention, activation, engagement, conversion, or feature adoption.
• Experience with A/B testing, statistical analysis, time-series analysis, forecasting, or anomaly detection.
• Experience creating executive-ready dashboards, research reports, data memos, or analytical briefs.
• Familiarity with data governance, access control, privacy controls, audit trails, or vendor data licensing requirements.
• Interest in financial research, market intelligence, AI-assisted workflows, and quantitative analytics.

What You Will Work On

You may work on projects such as:

• Building dashboards for product usage, research workflow performance, data quality, and market intelligence coverage.

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• Creating clean reporting layers for financial analytics, charts, company data, and internal research tools.
• Analyzing user behavior to identify friction points, feature adoption patterns, and product improvement opportunities.
• Validating financial datasets before they are used in dashboards, research workflows, or product features.
• Supporting Regional Analysts with curated datasets, market summaries, company screens, and cross-market research views.
• Creating metric definitions and documentation so teams can make consistent data-driven decisions.
• Partnering with Data Engineers to improve reporting tables, data models, and analytical reliability.

What You Will Gain

• Opportunity to work on analytics for an AI-powered financial research and market intelligence platform.
• Direct collaboration with product, engineering, AI, data, and regional analyst teams.
• Exposure to financial market data, product analytics, research workflows, and AI-assisted product development.
• Remote work with a distributed international team.
• A company email account and access to approved work tools, including Microsoft 365, Outlook, Teams, BI tools, and company-approved productivity tools, subject to internal security and usage policies.
• Opportunity to participate in company offsite activities, including possible Hong Kong offsites, subject to business schedule, travel eligibility, visa/documentation requirements, and company approval. Approved business-related travel, accommodation, and reasonable expenses will be covered by the company.

Important Role Boundaries

This is a data analytics role supporting financial research workflows, product analytics, and internal reporting.

The role does not require or permit the employee to:

• Provide personalized investment, legal, tax, accounting, or financial advice to users or clients.
• Recommend that any individual buy, sell, or hold a security based on personal circumstances.
• Execute trades or manage client funds.
• Handle client assets, deposits, or payments.
• Promise or imply investment returns, trading profits, or risk-free outcomes.
• Use unauthorized data sources, violate third-party data terms, or bypass licensing restrictions.
• Request applicants to pay any application fee, training fee, software fee, equipment fee, or onboarding fee.

Equal Opportunity Statement

Finstock, Inc. considers qualified applicants based on role-related skills, experience, analytical ability, technical ability, work quality, availability, and applicable engagement requirements. We do not make hiring decisions based on age, gender, gender identity, religion, ethnicity, race, national origin, disability, sexual orientation, marital status, family status, veteran status, or any other status protected by applicable law.