Used Tools & Technologies
Not specified
Required Skills & Competences
Tag name is followed by "@" symbol and proficiency level value.
About proficiency levels:
- 1-2 — basic awareness. Minimal hands-on experience, and a rudimentary understanding of the technology's purpose;
- 3-6 — daily use. Comfortable and regular usage, capable of handling common tasks and challenges related to the technology;
- 7-9 — you are an expert, you can teach others, you know all the pitfalls and tricks;
- 10 — exceptional knowledge, comprehensive understanding, and adeptness in all aspects of the technology, including advanced problem-solving. Think twice before claiming or demanding such level.
Python @ 3
SQL @ 3
Statistics @ 3
Data Science @ 3
Prioritization @ 3
Data Analysis @ 3
FinTech @ 3
Data Visualization @ 3
- 1-2 — basic awareness. Minimal hands-on experience, and a rudimentary understanding of the technology's purpose;
- 3-6 — daily use. Comfortable and regular usage, capable of handling common tasks and challenges related to the technology;
- 7-9 — you are an expert, you can teach others, you know all the pitfalls and tricks;
- 10 — exceptional knowledge, comprehensive understanding, and adeptness in all aspects of the technology, including advanced problem-solving. Think twice before claiming or demanding such level.
Details
Bloomberg Enterprise Data is fast paced, innovative and expanding. The team partners closely with clients to understand their data and FinTech needs and delivers datasets across asset types with multiple delivery technologies and flexible scheduling. You will work as a Product Analyst in Enterprise Data to act as a gatekeeper for data quality during product development, launch and enhancement. The role involves quantitative analysis, anomaly detection, and close collaboration with product, engineering and client teams across reference & pricing, company fundamentals, sustainable finance, Risk & Investment analytics and other Bloomberg Data License products.
Responsibilities
- Conduct time series data anomaly detection to identify abnormal patterns (e.g., coverage drops, missing values, unexpected data changes) and backtest model performance.
- Prepare exploratory data analysis including statistical and visual summaries to assess data and product quality, identify weaknesses, and propose enhancements.
- Communicate analysis results to product managers and software developers.
- Collaborate with product, engineering and sales teams on product delivery, task prioritization and product roadmap.
- Answer client questions and address client feedback related to product enhancements and bug fixes.
- Conduct product usage analysis to improve data product offerings.
- Contribute to scaling team activities through automation such as monitoring daily production data generation.
Requirements
- 1–3 years of experience working with model development for time series anomaly detection.
- Bachelor's or Master’s degree in a quantitative discipline (financial engineering, statistics, computer science, finance, engineering, etc.).
- Hands-on experience in analytical fields such as data science, quantitative analysis, data visualization, data mining, anomaly detection and data validation.
- Financial knowledge across asset classes (equity, fixed income, mortgages, municipal bonds, futures, options).
- Strong attention to data integrity.
- Programming skills in Python and SQL.
- Solid statistics and mathematical knowledge to perform quantitative analysis.
- Experience gathering, matching, and pre-processing large datasets from varied sources and of different characteristics.
- Experience working with clients, business managers or product managers to identify needs and communicate project processes.
Compensation & Benefits
Salary Range: 110000 - 225000 USD annually + benefits + bonus.
Bloomberg offers a comprehensive benefits plan that may include merit increases, incentive compensation (exempt roles), paid holidays, paid time off, medical, dental, vision, short and long term disability, 401(k) with match, life insurance, and wellness programs. The Company does not provide benefits directly to contingent workers/contractors and interns.
Additional Information
The referenced salary range is based on the Company's good faith belief at the time of posting. Actual compensation may vary based on geographic location, experience, market conditions, education/training and skill level.
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