Associate Alts Data Operation Analyst

About the role

This role reviews Alternatives data and supports machine learning operations within a data and AI platform. You will own the validation and correction of extracted data points to ensure the integrity of Alternatives datasets used by clients and internal models. A core part of your work involves close collaboration with the Machine Learning Operations team to relabel documents and prepare data for future model retraining. You will act as a human-in-the-loop reviewer for Private Funds statements, identifying discrepancies and ensuring accurate processing for Addepar clients. This position requires a strong sense of ownership over repetitive detail-oriented tasks, as your work directly feeds into model accuracy. You will translate raw financial documents into clean, structured data that supports downstream analytics and decision-making. Success in this role depends on your ability to communicate findings clearly and work effectively with cross-functional partners in a data-driven environment. Your contributions will help maintain the reliability of financial data that influences investment decisions and platform insights.

Key facts

What you'll do

Private Fund statements are reviewed to ensure accurate Alternatives data processing for Addepar clients, involving line-level validation and discrepancy logging.

Extracted data from machine learning models is identified and corrected to reflect precise financial valuations, improving model output accuracy and client trust.

Documents are relabeled and prepared alongside the Machine Learning Operations team to support future model retraining and iteration, enhancing long-term system performance.

Flexible working hours are accommodated, and office presence occurs three days per week from the Pune location to align with team coordination and real-time discussions.

Data quality checks are performed using structured review processes, focusing on completeness, accuracy, and consistency of Alternatives holdings information.

Financial data is reconciled against source documents to confirm that figures such as cost basis, valuation dates, and share classes are correctly captured in the system.

Collaboration with analysts and engineers ensures that data corrections are integrated into workflows, supporting continuous improvement in data pipelines.

Templates and documentation related to Alternatives data are maintained and updated to reflect changes in data requirements or regulatory standards.

Process efficiency is improved by identifying repetitive tasks and suggesting refinements that reduce manual effort and error rates over time.

Communication with internal stakeholders ensures that data issues are resolved promptly and that reporting timelines are consistently met.

Requirements

The posting states a bachelor's degree requirement, and candidates must hold a degree to be considered for this entry-level data operations role.

Experience ranges from 0 to 1 year, with fresh graduates welcomed for entry-level contributions, provided they demonstrate strong analytical aptitude.

An academic background in finance, commerce, or economics demonstrates foundational capital markets knowledge and business awareness relevant to financial data review.

Detail orientation is shown through exceptional attention to detail and effective problem-solving abilities in repetitive tasks that require accuracy and consistency.

Technology comfort is required, with foundational skills in Microsoft Excel and Google Suite for data manipulation, analysis, and professional communication.

Team collaboration reflects self-motivation, eagerness to learn, and a forward-thinking mentality when working with cross-functional partners in data and finance.

Flexible working hours and regular Pune office presence for three days weekly are committed to for consistent team alignment and operational coordination.

A strong command of written and verbal English is necessary to accurately interpret documentation and communicate findings within the team.

Candidates must be legally authorized to work in India without the need for visa sponsorship, as the role does not include visa support.

Practical notes

This role involves human review of financial documents and collaboration with machine learning workflows, requiring reliability and accuracy in a structured environment. No visa sponsorship is available for this position, and candidates must be authorized to work in India. Typical interview steps include data interviews that may feature a SQL or coding exercise, a statistics question, and a case study where candidates design a metric or interpret an experiment. Some employers may provide a take-home analysis to assess practical data skills. Expect behavioral questions about past projects and the business impact of your work, with emphasis on how you communicate uncertainty and decision relevance. Bringing a clean write-up of a past analysis to the interview is well received and can highlight your attention to detail and communication abilities.

Hours, travel, visa, or deadlines are specified as needed to ensure clarity around work arrangements and expectations for this data operations position.