“An educated person in the millennial era is one who can continuously learn, unlearn and relearn”. The problems today and in the future are too complex for the experts to solve, as they are reluctant to change. One needs to understand the interconnections between the problems and apply an interdisciplinary approach to make better business decisions.I am a self-motivated, purpose-driven problem solver and a decision-maker. To master the idea of an inter-disciplinary approach towards problem-solving, I aim to bring together the field of finance along with technology and mathematics. Using statistical modeling and data science/ machine learning, I seek to explore the inefficiencies of the financial markets. I have experience in analytics where I enabled the South Australian government pension funds department and a Fortune 30 client in the CPG (FMCG) domain to make data-driven decisions using advanced analytics like time series forecasting and machine learning. As a student consultant, I have assisted a top Investment Management firm with competitor analysis and understanding what tools and strategies are commodities in the market, and what are the differentiators. The goal was to enable the firm to position itself in the Systematic or Quantitative investment space.I define myself as an Investment Decision Catalyst, who is a blend of Quantitative Financial Analyst, Data Scientist, Machine Learning Engineer, and Management Consultant. Depending on the problem and its need, I have developed an ability to effectively use my skills to funnel into the problem-solving journey.Contact Details: rjindal@gatech.edu | rjindal.thapar@gmail.com | +1 404 736-4447Expertise:Programming Languages: R, Python, Java, SQL, MATLAB, StataFunctional: Problem Solving, Management Consulting, Data Science, Data Analytics, Machine Learning, Statistical Modeling, Time Series Analysis, Market Research, Quantitative Research, Financial Analysis, Financial Modeling, Investment Analysis, Spends OptimizationCourse Work (Carnegie Mellon University):Technical: Machine Learning, Data Mining, Database Management, Unstructured Data Analytics, Applied Econometrics, Statistics, Data Warehousing, Java, Python, Big DataBusiness: Financial Management, Principles of Finance, Economic Analysis, Financial Accounting, Consulting Labs, Project Management, Design Thinking, Decision making under uncertainty