Data Scientist

Role: Data Scientist Location: Reston, VA (Hybrid – 3 days onsite, 2 days remote) Type: Contract with possible conversion to full-time Interview Process Round 1: Video interview Round 2: In-person interview Experience Requirements • 1–5 years of experience • Strong Python experience • Strong proficiency in Python, R, SQL, and experience with data manipulation libraries such as Pandas and NumPy • Ability to work independently • Fannie Mae / Freddie Mac experience is a plus, not required • Good verbal and written communication skills Nice to Have • Experience with Amazon Bedrock for Data Science / ML work Open to more junior-mid level candidates with 1-5 years of experience, bill rates should reflect the amount of experience. Job Title: Data Scientist Key Responsibilities • Collect, clean, and preprocess large datasets from multiple sources. • Apply statistical analysis and machine learning techniques to solve business problems. • Build predictive models and algorithms to optimize processes and improve outcomes. • Develop dashboards and visualizations to communicate insights effectively. • Collaborate with cross-functional teams (Product, Engineering, Risk, Marketing) to identify opportunities for leveraging data. • Ensure data integrity, security, and compliance with organizational standards. • Stay current with emerging technologies and best practices in data science and AI. \_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_ Required Qualifications • Bachelor’s or Master’s degree in Data Science, Computer Science, Statistics, Mathematics, or related field. • Strong proficiency in Python, R, SQL, and experience with data manipulation libraries (e.g., Pandas, NumPy). • Hands-on experience with machine learning frameworks (e.g., scikit-learn, TensorFlow, PyTorch). • Solid understanding of statistical modeling, hypothesis testing, and data visualization. • Experience with big data platforms (e.g., Spark, Hadoop) and cloud environments (AWS, Azure, GCP). • Excellent problem-solving skills and ability to communicate complex concepts clearly. \_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_ Preferred Qualifications • Experience in risk modeling, financial services, or product analytics. • Knowledge of MLOps and deploying models in production. • Familiarity with data governance and compliance frameworks. \_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_ Soft Skills • Strong analytical thinking and attention to detail. • Ability to work independently and in a team environment. • Effective communication and stakeholder management skills.