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Data Scientist for Indexing (for CCPI)

Job Title: Data Scientist for Indexing

Strong command of the English language in reading, speaking, and writing
Fluent in R/Python with over 2 years of proven experience.

Job Description:

As a Data Scientist for Indexing, you will play a crucial role in designing, developing, and optimizing financial indexes used in investment products and services.

Your expertise in data analysis, statistical modeling, and programming will be essential in creating accurate and reliable benchmarks for evaluating investment performance and guiding portfolio management decisions.

Key Responsibilities:

  1. Index Design and Development: Collaborate with the research and investment teams to understand the objectives and requirements for creating new financial indexes. Design innovative index methodologies that accurately represent the underlying market or asset class.

  2. Data Collection and Preprocessing: Source and collect financial data from various internal and external sources. Cleanse and preprocess the data to ensure its quality and suitability for index calculations.

  3. Statistical Modeling: Apply advanced statistical techniques and quantitative methods to analyze financial data and identify patterns and trends relevant to index construction. Develop mathematical models for index calculation, considering factors such as weighting schemes and rebalancing procedures.

  4. Index Optimization: Continuously explore ways to improve index performance and efficiency. Utilize statistical analysis and optimization techniques to enhance the risk-return profile and representativeness of the indexes.

  5. Backtesting and Validation: Conduct rigorous backtesting and validation of index methodologies using historical data to ensure their robustness and accuracy. Analyze the performance of the indexes and compare them against relevant benchmarks.

  6. Data Visualization: Create clear and insightful data visualizations to communicate index characteristics, historical performance, and other relevant information to internal stakeholders and clients.

  7. Automation and Efficiency: Develop tools and scripts to automate data processing, index calculations, and reporting tasks. Enhance the efficiency of index development and maintenance processes.

  8. Collaboration and Communication: Work closely with cross-functional teams, including portfolio managers, research analysts, and IT professionals, to ensure seamless integration of indexes into investment strategies and products. Communicate complex technical concepts in a clear and understandable manner.

  9. Regulatory Compliance: Stay updated with industry regulations and best practices related to index construction and maintenance. Ensure that the indexes meet all necessary regulatory requirements.

  10. Research and Innovation: Stay abreast of the latest developments in data science, machine learning, and financial markets. Identify and implement innovative approaches to improve index construction and analysis.

Requirements:

  1. Master’s or Ph.D. in Data Science, Statistics, Computer Science, Mathematics, Finance, or a related field.
  2. Strong background in statistical analysis, quantitative research, and data modeling.
  3. Proficiency in programming languages such as Python, R, or similar, and experience with data manipulation libraries and tools.
  4. Familiarity with financial markets, investment products, and asset classes.
  5. Experience working with financial data sets and understanding of data challenges specific to financial markets.
  6. Knowledge of index methodologies, including market-cap weighting, price return, total return, and rebalancing.
  7. Ability to develop and implement complex mathematical models for index calculation and optimization.
  8. Excellent analytical and problem-solving skills, with a keen eye for detail.
  9. Strong communication and collaboration skills to work effectively within a team environment.
  10. Experience with data visualization tools and techniques.
  11. Knowledge of regulatory requirements related to financial indexes is a plus.

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