Data Scientist (Bachelor’s degree from a U.S.-accredited university is required.)

Job Description

We are seeking a Data Scientist to join a data science team and collaborate with senior data scientists, business leaders, and cross-functional teams to develop predictive models and data-driven solutions that enhance digital products and customer experiences.

The ideal candidate will have strong hands-on experience with Python, SQL, PySpark, machine learning, predictive modeling, and cloud data platforms such as Azure and Databricks. Experience in banking or financial services, customer analytics, digital analytics, and advanced machine learning techniques is highly preferred.

Responsibilities

• Collaborate with senior data scientists and business leaders to design and implement predictive models and custom data science solutions.
• Partner with business units to gather requirements, understand customer needs, and translate business challenges into data-driven solutions.
• Write efficient and scalable code using Python, SQL, and PySpark to manipulate, explore, and analyze large datasets.
• Design, develop, test, and evaluate predictive models and algorithms ranging from moderate to high complexity.
• Apply traditional statistical and machine learning techniques to solve business problems.
• Develop models using techniques including Logistic Regression, Random Forest, XGBoost, Neural Networks, NLP, K-Means Clustering, ARIMA, and Prophet Forecasting.
• Perform data exploration, preparation, feature engineering, modeling, prediction, simulation, and statistical analysis.
• Analyze model outputs and translate complex analytical results into meaningful business insights.
• Apply modeling and trend analysis techniques to identify patterns, opportunities, and potential risks.
• Develop modeling programs, algorithms, and automated analytical processes.
• Work with cloud-based data environments including Azure, Databricks, AWS, or Hadoop.
• Support customer analytics and digital analytics initiatives to improve customer experience and digital offerings.
• Document methodologies, analytical findings, and technical processes.
• Present analytical results and recommendations to technical and non-technical stakeholders.
• Collaborate with team members on data science projects, initiatives, and continuous improvement efforts.
• Work independently with moderate to minimal supervision while following established procedures and practices.

Required Qualifications

• 3–7 years of experience in data science, statistics, data analytics, or a related quantitative field.
• Strong programming skills in Python and SQL.
• Hands-on experience with PySpark / Apache Spark or similar distributed data processing technologies.
• Strong knowledge of machine learning and predictive modeling techniques.
• Experience developing and evaluating models such as Logistic Regression, Random Forest, XGBoost, Neural Networks, NLP, and Clustering.
• Experience working with cloud or big-data environments such as Azure, Databricks, AWS, or Hadoop.
• Experience with data exploration, data preparation, statistical analysis, prediction, simulation, and modeling.
• Strong analytical and problem-solving skills.
• Ability to work independently with moderate to minimal supervision.
• Strong written and verbal communication skills.
• Ability to communicate complex technical concepts and analytical findings through effective data storytelling and presentations.
• Strong collaboration and relationship-building skills.
• Bachelor's degree in Data Science, Statistics, Economics, Mathematics, Computer Science, Engineering, or another quantitative discipline.

Preferred Qualifications

• Experience in banking, financial services, fintech, or credit union environments.
• Experience with customer analytics or digital analytics.
• Advanced experience with NLP and machine learning techniques.
• Hands-on experience with Azure and Databricks.
• Experience with Azure DevOps (ADO) or Jira.
• Master's degree in Data Science, Statistics, Mathematics, or a related quantitative field.
• Experience presenting data science findings to business and executive stakeholders.
• Strong technical writing and documentation skills.

Required Technical Skills

Python | SQL | PySpark | Machine Learning | Predictive Modeling | Azure | Databricks | NLP | XGBoost | Neural Networks | Customer Analytics | Digital Analytics

Work Arrangement

• Hybrid – 3 days/week onsite
• Location: Vienna, VA
• Candidates should be comfortable working onsite at the headquarters three days per week.