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Medical, Dental, Vision, Retirement, PTO
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Job description
WEBSITE: https://canoeintelligence.com/
TITLE: Data Analyst, Private Markets
LOCATION: New York City (hybrid) or Jacksonville, FL (hybrid)
SALARY: $70,000 - $110,000 + Bonus and Equity (based on New York, will be adjusted for geo)
The Role:
You are an emerging operations professional eager to grow your career at the intersection of private markets and cutting-edge AI. As a member of our Canoe Data Operations Team, you will apply your expertise in private market data to build, define, and execute on our product and service offering-while supporting day-to-day operations, ensuring data quality, and tackling the operational complexity of the private markets ecosystem.
You will work alongside senior team members to manage delivery through our onshore and offshore teams, contribute to the accuracy and efficiency of our platform, and partner closely with Product Managers to help shape the future product roadmap. This is an exciting opportunity to own core functionality and drive meaningful improvements across service delivery and ongoing operations.
What You'll Do:
Operational Support & Workflow Management:
- Support Document Processing Workflows: Assist in the intake, review, and processing of LP documents (Capital Account Statements, PCAPs, Call/Distribution Notices), ensuring they move through the pipeline accurately and on time.
- Monitor & Triage Exceptions: Review automated outputs, identify processing exceptions or anomalies, and escalate or resolve issues in coordination with senior operations staff.
- Deliver Quality: Reconcile extraction data against source documents, manage conflicting data points, and maintain high standards across all client deliverables.
- Be an SME: Become a go-to individual within Canoe for private market data points-including underlying asset data such as cost basis, valuations, and operating metrics-and support the manipulation and enrichment of such data.
- Advocate for Standards: Champion best practices, perform quality checks, and drive consistency across the team to foster a culture of excellence.
- Derive Insights: Perform analysis on data trends to inform our product and service offering, and flag patterns that can inform process improvements or automation opportunities.
- Continuous Improvement: Identify technology and process improvements to efficiently and effectively process data, and assist in refining operating procedures.
- Document Operational Logic: Help capture and organize process notes, workflow rules, and exception-handling procedures to be shared across operations and product teams.
- Cross-Functional Coordination: Work closely with Data, Product, and Engineering teams to communicate operational needs, contribute to product roadmap discussions, and flag issues that require systemic fixes.
- Manage Offshore Coordination: Support delivery through onshore and offshore team structures, ensuring work is executed accurately and on schedule.
- Client-Adjacent Support: Assist client-facing team members by preparing operational summaries and data quality reports that support client communications and onboarding.
- Experience: 1+ years of experience in fund operations, fund administration, private market data, or a related financial services role. Internship experience in relevant fields will be considered.
- Domain Knowledge: Familiarity with private market data points including asset-level data (cost basis, valuations, operating metrics), capital calls, distributions, and fund financial statements.
- Operational Mindset: Process-oriented and organized, with a proven ability to self-manage in a remote or hybrid work setting and balance individual focus with team collaboration.
- Attention to Detail: You take accuracy seriously and understand that clean, reliable data is the foundation of everything we do.
- Communication Skills: Strong communication, presentation, and interpersonal skills with the ability to work effectively across teams and time zones.
- Comfort with Ambiguity: Comfortable navigating complex, fast-paced environments and uncovering answers to open-ended product and operational questions.
- Technical Comfort: Comfortable working with structured data in Excel or similar tools. Exposure to SQL or data platforms is a bonus, but not required.
- Medical, dental, vision benefits
- Flexible PTO
- 401(k)
- Flexible work from home policy
- Home office stipend + wifi reimbursement
- Employee Assistance Program
- Gym reimbursement
- Education assistance
- Parental Leave
- Commuter benefits
Our Values:
Client First -> Listen, and deliver client-centric solutions
Be An Owner -> Take initiative, improve situations, drive positive outcomes
Excellence -> Always set the highest standard for yourself and others
Win Together -> 1 + 1 = 3
Who We Are:
Canoe is reimagining alternative investment data processes for hundreds of leading institutional investors, capital allocators, asset servicing firms and wealth managers. By combining industry expertise with the most sophisticated data capture technologies, Canoe's technology automates the highly-frustrating, time-consuming, and costly manual workflows related to alternative investment document and data management, extraction and delivery. With Canoe, clients can refocus capital and human resources on business performance and growth, increase efficiency, and gain deeper access to their data. Canoe's AI-driven platform was developed in 2013 for Portage Partners LLC, a private investment firm.
Canoe is an equal opportunity employer. All aspects of employment including the decision to hire, promote, discipline, or discharge, will be based on merit, competence, performance, and business needs. We do not discriminate on the basis of race, color, religion, marital status, age, national origin, ancestry, physical or mental disability, medical condition, pregnancy, genetic information, gender, sexual orientation, gender identity or expression, veteran status, or any other status protected under federal, state, or local law.
Department Data Operations Locations Jacksonville, New York City Remote status Hybrid
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Frequently asked questions
Q: What skills or qualities help someone succeed as a Data Analyst?
A: To succeed as a Data Analyst, key technical skills include proficiency in programming languages such as Python or R, expertise in data visualization tools like Tableau or Power BI, and knowledge of statistical analysis and machine learning concepts. Additionally, strong soft skills like effective communication, problem-solving, and collaboration are crucial for presenting insights to stakeholders and working with cross-functional teams. By combining these technical and soft skills, Data Analysts can drive business decisions, identify areas for improvement, and contribute to the growth and success of their organization.
Q: What is the career path for a Data Analyst?
A: A Data Analyst's typical career progression involves starting as an Entry-Level Data Analyst, where they collect, analyze, and interpret data to inform business decisions. As they gain experience, they can move into Mid-Level roles such as Senior Data Analyst or Business Analyst, where they take on more complex projects and lead smaller teams. Ultimately, they can advance to Senior Leadership positions like Data Scientist, Data Manager, or even Director of Analytics, where they oversee large-scale data initiatives and drive strategic business growth.\n\nKey opportunities for skill development and professional growth in this role include learning programming languages like Python or R, mastering data visualization tools like Tableau or Power BI, and staying up-to-date with emerging trends in machine learning and artificial intelligence. Additionally, Data Analysts can develop soft skills like communication, project management, and leadership to excel in their roles.\n\nLong-term career prospects for Data Analysts are diverse, with potential directions including transitioning into related fields like Business Intelligence, Data Engineering, or even becoming a Product Manager, or pursuing advanced degrees in Data Science or related fields to further specialize in areas like machine learning or data engineering.