Job description

Why join this team

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 - $90,820 - $130,000 annually; compensation is commensurate to geographic location.

What You'll Do

  • 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

What we're seeking

  • 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

What makes you stand out

  • Working experience in predictive, recommendation, time series models and market segmentation
  • Working experience in anomaly detection and multi label classification
  • Working knowledge of SQL, MLOps, Generative AI Models
  • Exposure to Deep Learning, Text Analytics, Natural Language Processing and Natural Language Generation
  • Working experience in business intelligence, business analysis and advanced analytics

Who we are

UNFCU is a global not-for-profit financial institution that serves the UN community. We are committed to providing peace of mind to our members and colleagues and strive to achieve service excellence in all that we do. The best part of UNFCU is the people. Those that choose to work with us often find personal fulfillment, professional growth and a purposeful culture.

UNFCU is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees. UNFCU prohibits discrimination and harassment of any type. All applicants will be considered for employment without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by country, federal, state or local laws.

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