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3-6 Years
SGD 3,500 - 5,000 per month
  • Posted an hour ago
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Job Description

Role overview

We are hiring a full-time Data Analyst to turn our clients portfolio and risk data into automated pipelines, analytics, dashboards andAI-assisted research. We are a software consultancy serving portfolio management and risk teams, and this role sits between our clients and our engineering work.

This is a career-conversion role. You do not need prior experience as a data analyst. You will learn the job through a structured 6-month on-the-job training programme under the Career Conversion Programme(CCP), working on real client deliverables from the first month.

Key responsibilities

Client needs and business analysis

. Map client workflows for data intake, reconciliation, risk reporting and research, and document them as process maps.

. Analyse client needs for portfolio and risk analytics, and turn them into written requirements: inputs, outputs, edge cases, business rules and acceptance criteria.

. Run discovery sessions with clients and write dashboard specifications and wireframes.

Data engineering and automation

. Build connectors to broker, custodian and market datasources using REST APIs (authentication, JSON, paging, rate limits).

. Clean, map and load data into database, keeping field mapping documents and instrument mapping tables up to date.

. Build and run a daily reconciliation of internal positions against broker and custodian statements, with tolerance rules.

. Schedule data jobs, automate recurring client reports, and maintain runbooks for re-running jobs and fixing common failures.

Portfolio and risk analytics

. Calculate portfolio metrics: market value, weights, gross/net and long/short exposure, delta-adjusted exposure, concentration, and daily, cumulative and time-weighted returns.

. Calculate risk metrics: rolling volatility, correlation, beta, maximum drawdown, Value-at-Risk and Expected Shortfall, documenting each method's assumptions.

. Build stress scenarios (historical and hypothetical)and PnL attribution by asset, strategy and driver (price, carry/funding, FX, fees).

. Validate every metric against independent reference calculations and automate tests.

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