Excellent skills in machine learning/deep learning-based algorithms with structured/ unstructured data; developing analytical insights and statistical models that optimize business.
Strong mathematical-statistical understanding behind the algorithms.
Proficient in time series forecasting, predictive analytics, propensity modeling.
Industry experience in predictive modeling, data science, and analysis.
Good in the evaluation of the performance of various classification, forecasting, and regression models.
Experience in conceptualizing and developing machine learning solutions in an ML engineer or data scientist role, building, and deploying ML models, or hands-on experience developing deep learning models.
Experience in process knowledge and analysis, proficient at detecting patterns or problems that could affect overall data integrity/ solution.
Ability to think through alternatives, coming to decisions quickly, and following through with execution to resolve issues at the source.
Experience writing and speaking about technical concepts to business and giving data-driven presentations.
Proficient in programming languages either R or Python
Statistics, Linear Algebra, Machine Learning, Natural Language Processing, Deep Learning, Computer Vision, Data Structure, R, Python
Bachelor’s/ Master’s/Ph.D. degree in a highly quantitative field (Computer Science, Machine Learning, Operational Research, Statistics, Mathematics, etc.) or equivalent field.