Title: Jr. Data Scientist
Duration: long term contract
Location: Hybrid (Vienna, VA)
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.
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