Applied Data Analyst - Data Quality Analytics

About the Role

Bloomberg's Enterprise Data division is a dynamic and rapidly growing part of the company, specializing in delivering a vast array of financial datasets across multiple asset types and formats tailored to client needs. The role of Product Analyst involves partnering with diverse stakeholders to safeguard data quality throughout the product lifecycle — from development and launch to ongoing enhancement. This position blends finance expertise, quantitative skills, and technical aptitude to analyze data and detect anomalies in innovative products, including reference and pricing data, company fundamentals, sustainable finance, risk and investment analytics, and Bloomberg Data License offerings.

Key Responsibilities

• Perform anomaly detection on time series data to identify patterns such as coverage decline, missing values, or unexpected changes, and validate model performance through back testing.
• Conduct exploratory data analysis with statistical and visual summaries to evaluate data and product quality, pinpoint weaknesses, and suggest improvements.
• Effectively communicate analytical outcomes to product managers and software developers.
• Collaborate closely with product, engineering, and sales teams in delivering products, managing task priorities, and shaping the product roadmap.
• Respond to client inquiries and incorporate client feedback into product fixes and feature enhancements.
• Analyze product usage trends to refine and augment data product offerings.
• Drive automation initiatives to scale team efforts, such as implementing monitoring systems for daily production data workflows.

Qualifications

• A minimum of 3 years of experience developing models specifically for time series anomaly detection.
• Bachelor's or Master’s degree in a quantitative field such as financial engineering, statistics, computer science, finance, or engineering.
• Practical experience in areas like data science, quantitative analytics, data visualization, data mining, anomaly detection, and data validation.
• Solid financial knowledge across various asset classes including equities, fixed income, mortgages, municipal bonds, futures, and options.
• Strong focus on maintaining data integrity.
• Proficiency in programming languages including Python and SQL.
• Sound understanding of statistics and mathematics to support quantitative analysis.
• Experience handling, integrating, and preprocessing substantial datasets from diverse sources with distinct characteristics.

Additional Preferred Qualifications

• Experience collaborating with clients, business managers, or product managers to identify requirements and communicate project progress proactively.

Compensation and Benefits

The role offers an annual salary ranging from $110,000 to $225,000, complemented by benefits and bonus opportunities. Compensation is calibrated based on location, experience, education, skills, and market factors. Benefits include extensive plans such as paid leave, health coverage (medical, dental, vision), disability benefits, 401(k) with matching, life insurance, and wellness programs. Note that contingent workers and interns are not covered by these benefits.