What you will do:

• Derive actionable insights using rich historical and ongoing corporate actions information within MCA and other complimentary financial services products
• Address day-to-day operations data sourcing needs
• Develop insights, methods or tools using various analytic methods such as text analytics, predictive modeling, regressions, machine learning, , simulations, etc.
• Handle large amounts of data from multiple and disparate sources
• Analyze the data and the results to ensure data quality, statistical relevance, etc. with a critical mindset
• Work closely with stakeholders to solve challenging business problems with technical expertise, curiosity and creativity
• Establish necessary business and domain knowledge to correctly interpret data and results
• Bring analytical rigor and statistical methods to the challenges of measuring data quality, product performance, anticipating and interpreting the behavior of end-users
• Automate workflows and apply scientific methods to solve business and engineering problems

Who you are:

• Hands on project lifecycle experience, from business analysis to productization
• Strong critical thinking and problem-solving skills
• Ability to work independently and execute projects end-to-end
• Experience working with SQL, Python, R, AWS
• Experience in NLP/text analytics
• Experience of web-scraping, REST-based APIs (json/yaml/OpenAPI) using Python.
• Ability to quickly acquire new technical skills
• Able to translate business problems into problems that can be solved with Data Science
• Ability to work in a team
• Ability to communicate ideas and analysis results effectively both verbally and in writing to a non-technical audience
• Bachelor of Science or certified in a quantitative discipline (e.g., statistics, operations research, computer science, mathematics, physics, electrical engineering, industrial engineering)
• 4-5 years of professional experience in Advanced Analytics / Data Science / Machine Learning in Finance and/or Reference Data space