Senior Portfolio Manager - Freelance AI Trainer at Mindrift

New York, New York, United States -

Full Time

Start Date

Immediate

Expiry Date

18 Sep, 26

Salary

60.0

Posted On

20 Jun, 26

Experience

2 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Portfolio Management, Investment Research, Tax-Loss Harvesting, Performance Attribution, Excel Modeling, Investment Policy Statement Analysis, ESG Analysis, Fee-Stack Analysis, Tax-Lot Accounting, Financial Calculation, Fiduciary Compliance, English Proficiency

Industry

technology;Information and Internet

Description

Please submit your CV in English and indicate your level of English proficiency. Mindrift connects specialists with project-based AI opportunities for leading tech companies, focused on testing, evaluating, and improving AI systems. Participation is project-based, not permanent employment. What this opportunity involves While each project involves unique tasks, contributors may: Design and evaluate Quarterly Business Review scenarios — performance vs. benchmark, allocation drift against IPS tolerance bands, and material fund document changes; Write and grade underperformance explanation tasks where the correct answer is grounded strictly in fund documents, with no projections beyond what the manager's commentary actually states; Create rebalancing test cases with full tax-impact math: cost basis, short-term vs. long-term capital gains, and alternatives to selling (redirecting contributions); Build tax-loss harvesting scenarios that test the wash-sale rule in both directions — including the 30-day backward window and substantially identical securities across different fund families and tickers; Develop suitability check cases probing risk tolerance, time horizon, prohibited holdings, and concentration limits against a client's Investment Policy Statement; Design ESG look-through scenarios where the fund label diverges from actual holdings due to subsidiary relationships or narrow exclusion methodologies; Construct fee-stack analysis cases: portfolio-weighted expense ratios, advisory fees, all-in cost comparisons against category benchmarks; Author goal-projection scenarios that test whether the agent uses assumption-based language and never slips into commitment language when prompted to be reassuring; Document test cases clearly with verified calculations, policy citations, and correct answers. What we look for This opportunity is a good fit for mortgage underwriters and loan origination professionals open to part-time, non-permanent projects. Ideally, contributors will have: Degree in Finance, Economics, Business Administration, Accounting, or related field — or equivalent professional experience; no specific degree is required if CFA charterholder status or comparable credentials are present; 3+ years of experience managing portfolios or writing investment research in a fiduciary context (RIA, private wealth, asset management, family office, or bank trust); Ability to compute time-weighted returns, attribution effects (Brinson framework), and portfolio-weighted expense ratios without assistance; Practical knowledge of the wash-sale rule applied in both directions, tax-lot accounting methods (FIFO, specific identification, HIFO), and short- vs. long-term gain treatment; Investment Policy Statement literacy — able to identify every constraint and flag conflicts between a proposed recommendation and the IPS; Prospectus and fact-sheet reading discipline — able to distinguish what the marketing summary says from what the legal language actually says; Excel modeling competence: assumptions in named cells, performance attribution models, tax-impact worksheets that update correctly; CFA charterholder, CFP, CPWA, CIMA, or CIPM credential is a strong positive signal — for this agent, credentials matter more than in other projects due to the precision the work requires; FINRA Series 7, 65, or 66 license is a baseline positive signal; its absence on someone claiming significant advisory experience is a red flag; Strong written English (C1+). How it works Apply → Pass qualification(s) → Join a project → Complete tasks → Get paid Project time expectations For this project, tasks are estimated to require around 10–20 hours per week during active phases, based on project requirements. This is an estimate, not a guaranteed workload, and applies only while the project is active. Compensation On this project, contributors can earn up to $60 per hour equivalent, depending on their level and pace of contribution. Compensation varies across projects depending on scope, complexity, and required expertise. Please note that other projects on the platform may offer different earning levels based on their requirements.

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Responsibilities

Design and evaluate complex financial scenarios for AI training, including portfolio rebalancing, tax-impact math, and suitability checks. Document test cases with verified calculations and policy citations to improve AI system accuracy.