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.

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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.

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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.

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Soft Skills

• Strong analytical thinking and attention to detail.

• Ability to work independently and in a team environment.

• Effective communication and stakeholder management skills.