UNFCU
Data Scientist
UNFCU, New York, New York, United States,
This role is the first of its kind at UNFCU. We are looking for an experienced Data Scientist who will take us to the next level of machine learning, aiding the organization in achieving its unique objectives and goals. You will analyze and interpret complex datasets and use advanced analytics tools, algorithms, and machine learning techniques to make predictions and decisions from vast amounts of data.This position is expected to be hybrid.NYC Salary Range - $85,600 - $130,000 annually; compensation is commensurate to geographic location.
Regardless of seniority or role, uphold UNFCU’s mission, core values, and guiding principles by providing an exceptional service experience to colleagues and members alike through consistent demonstration of our service excellence behaviorsUnderstand business objectives and formulate problem into a data science problem, analyzing large amounts of information to find patterns and solutionsDesign, train, and deliver data science solutions using all modalities (tabular, text) and of all sizes (small or big data)Explore data and communicate insights clearly to non-technical as well as technical audiencesAnalyze experimental results, and iterate and refine models to create significant business impactData mine or extract usable data from valuable data sourcesUse machine learning tools to select features, and create and optimize classifiersCarry out preprocessing of structured and unstructured data
Bachelor’s degree in a quantitative discipline and at least 3 years of data science experience in the financial domainPython Programming language for Data Scientist; expert skills in manipulating data frames using Pandas and arrays using NumpyFamiliarity with Python standard machine learning and Deep Learning libraries (like scikit-learn, StatsModels, tensor flow, Keras and Pytorch)Solid applied statistical skills, including knowledge of statistical tests, distributions, regression, maximum likelihood estimators, etc.Ability to develop and maintain robust data processing pipelines and reproducible modelling pipelinesIn-depth understanding of classical statistical forecasting algorithms like ARIMA, Prophet, etc.Proven experience in handling Time Series Forecasting using standard Regression algorithms like Linear Regression, Gradient Boosted Decision Trees, Random forest, etc.Experience with any of the cloud platforms like GCP, AWS or AzureExperience deploying custom ML models on existing platforms like SalesforceExcellent verbal and written communication skillsDemonstrate agility, flexibility, and show a willingness to learn new tools and technology
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Regardless of seniority or role, uphold UNFCU’s mission, core values, and guiding principles by providing an exceptional service experience to colleagues and members alike through consistent demonstration of our service excellence behaviorsUnderstand business objectives and formulate problem into a data science problem, analyzing large amounts of information to find patterns and solutionsDesign, train, and deliver data science solutions using all modalities (tabular, text) and of all sizes (small or big data)Explore data and communicate insights clearly to non-technical as well as technical audiencesAnalyze experimental results, and iterate and refine models to create significant business impactData mine or extract usable data from valuable data sourcesUse machine learning tools to select features, and create and optimize classifiersCarry out preprocessing of structured and unstructured data
Bachelor’s degree in a quantitative discipline and at least 3 years of data science experience in the financial domainPython Programming language for Data Scientist; expert skills in manipulating data frames using Pandas and arrays using NumpyFamiliarity with Python standard machine learning and Deep Learning libraries (like scikit-learn, StatsModels, tensor flow, Keras and Pytorch)Solid applied statistical skills, including knowledge of statistical tests, distributions, regression, maximum likelihood estimators, etc.Ability to develop and maintain robust data processing pipelines and reproducible modelling pipelinesIn-depth understanding of classical statistical forecasting algorithms like ARIMA, Prophet, etc.Proven experience in handling Time Series Forecasting using standard Regression algorithms like Linear Regression, Gradient Boosted Decision Trees, Random forest, etc.Experience with any of the cloud platforms like GCP, AWS or AzureExperience deploying custom ML models on existing platforms like SalesforceExcellent verbal and written communication skillsDemonstrate agility, flexibility, and show a willingness to learn new tools and technology
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