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Greetings!

Our client Navy Federal Credit Union is the world's largest credit union with over 10 million members, over $149 billion in assets, and over 23,000 employees.

Our client is seeking an Associate Data Scientist-15721-Hybrid in Vienna, VA OR San Diego CA OR Pensacola, FL OR Winchester, VA. You seem to have a rock-solid profile and your overall background seems to be a great match for the position.

Please review the below information for clarity on the position description.

Description

Our Digital data science department is dedicated to building predictive solutions for our mobile application and online business operations. We develop predictive tools to assist business and app developers in enhancing user experience and optimizing operational performance.

We are seeking a motivated and talented entry-level data scientist to join our growing department. This role involves collaborating with senior team members, leaders, and business units to create custom solutions and data science models that provide insights into customer digital behavior, forecast mobile app and website usage trends, assess customer app store sentiment, and analyze data for actionable insights. Knowledge or insights into financial services and banking products will also be helpful in designing solutions and predictive tools to help customers improve financial management and financial health/well-being.

Responsibilities

+ Collaborate with senior data scientists and leaders to design and implement predictive models and custom solutions that enhance our digital offerings.

+ Partner with business units to gather requirements, understand customer needs, and develop data science solutions that address specific business challenges.

+ Write efficient code in Python and SQL to manipulate and analyze data.

+ Design, develop, and evaluate basic/routine predictive models and algorithms with some complexity

+ Utilize traditional and machine learning techniques and tools to build a variety of models, including but not limited to logistic regression, random forest, XGBoost, neural networks, NLP, k-means clustering, ARIMA, and prophet forecasting.

+ Analyze and interpret results with some complexity

+ Exercise limited judgment and discretion within defined procedures and practices

+ Develop and code basic modeling programs, algorithms, and automated processes

+ Use modeling and trend analysis to analyze data

+ Collaborate with team members and participate in team projects and initiatives

+ Utilize effective written and verbal communication to document and present findings

Qualifications

+ 0-2 years of experience in data science, statistics, and data analytics

+ Strong programming abilities in SQL, Python, R, or similar languages in data exploration, data preparation, modeling, prediction, simulation, and statistical analysis

+ Ability to use data and cloud environments such as Azure, Databricks, AWS, or Hadoop

+ Experience with machine learning techniques and tools to build a variety of models, including logistic regression, XGBoost, neural networks, NLP, and clustering

+ Technical writing skills

+ Strong communication and data storytelling presentation skills of technical material

+ Ability to collaborate and build relationships

+ Desired: Bachelor's degree in data science, statistics, mathematics, computers science, engineering, or degrees in similar quantitative fields