Data Scientist

Role:
Data Scientist

Location:
Reston, VA (Hybrid — 3 days onsite, 2 days remote)

Type:
Contract with possible conversion to full-time

• Round 1:
  Video interview
• Round 2:
  In-person interview

• 1–5 years of experience
• Strong Python experience
• Strong proficiency in Python, R, SQL, and experience with data manipulation libraries such as Pandas and Num Py
• Ability to work independently
• Fannie Mae / Freddie Mac experience is a plus, not required
• Good verbal and written communication skills

• 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

• 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.

• 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, Num Py).
• Hands‑on experience with machine learning frameworks (e.g., scikit‑learn, Tensor Flow, 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.

• Experience in risk modeling, financial services, or product analytics.
• Knowledge of MLOps and deploying models in production.
• Familiarity with data governance and compliance frameworks.

• Strong analytical thinking and attention to detail.
• Ability to work independently and in a team environment.
• Effective communication and stakeholder management skills.