Data Analyst - Financial Domain

A data analyst / scientist with experience in financial data and Investment technology solutions who can develop insights from data and impact strategy and direction of high value business solutions. Require critical thinking and hands on approach using latest AI models and methodologies to analyze business problems and develop solutions from underlying data, and discover new ways/patterns to address critical questions that could not be addressed before.

Well, organized to execute data analysis and solutioning initiatives as an individual contributor and as part of the team. Provide analytical insights to business leaders, users, developers, and other stakeholders, and evolve data discoveries and processes into operational capabilities. Develop working solutions applying platforms and methodologies of data science and AI, and provide bottom-up insights to articulate findings of critical problems.

Provide subject matter expertise in the wide range of Investment data domains to direct solutioning effort in the most efficient manner. This is not a top-down consulting role, but a hands-on data-science role with deep experience in coding/AI technologies where applicable.

Requirements

5+ years of experience as Data Scientist, Business Analyst or related role in Investment & Risk technology domain Bachelors or Master’s degree in Finance, Statistics, Economics, Mathematics or related field of study Application of AI tools and platforms where necessary to connect unstructured financial data Experience in Investment Management, Portfolio modeling, Trade/Order Management Systems, Compliance, Enterprise Data Management platforms and solutions Experience in Fixed Income and OTC instruments, including trade/order modeling, reference data, valuation, analytics and portfolio risk analytics etc.

Expertise in querying and analyzing large quantities of data using SQL, PL/SQL, Python, Java, Hive, Spark etc. Business intelligence tools such as Tableau/Splunk etc. for data visualizations and dashboards ETL tools such as Informatica, Alteryx, Pentaho etc. Problem solving for data science projects: Define the analytical target, frame business questions, develop hypothesis, create analysis plans and review/refine, present findings for decision making Use pivot tables, plotting graphs, visualizations, numeric models, programming and other advanced features in Excel Design experiments using different data science methodologies, data sources, or elements to gauge the proxy solution of unstructured business problems Running statistical and hypothesis testing, building regression and classification models including logistics, decision tree, conducting principal component analysis.

Benefits

Across USA. Hybrid with some onsite travel when needed Benefits: Base, Bonus, Medical/Dental/Vision Insurance, 401K. Opportunity to work on leading industry solutions (first of its kind) with emerging data science/AI models and methodologies, that will be in top demand for decades forward. Projects with globally recognized largest financial institutions.