Data Scientist

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.

Considering applying for this job Do not delay, scroll down and make your application as soon as possible to avoid missing out.

• 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 behaviors
• Understand business objectives and formulate problem into a data science problem, analyzing large amounts of information to find patterns and solutions
• Design, 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 audiences
• Analyze experimental results, and iterate and refine models to create significant business impact
• Data mine or extract usable data from valuable data sources
• Use machine learning tools to select features, and create and optimize classifiers
• Carry 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 domain
• Python Programming language for Data Scientist; expert skills in manipulating data frames using Pandas and arrays using Numpy
• Familiarity 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 pipelines
• In-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 Azure
• Experience deploying custom ML models on existing platforms like Salesforce
• Excellent verbal and written communication skills
• Demonstrate agility, flexibility, and show a willingness to learn new tools and technology

J-18808-Ljbffr