2025 Data Analytics Data Science Engineer

Data Science Engineer

Contribute to the build-out of the next stage of our data analytics program to deeply understand historical deal flow and develop modelling capabilities for decision support and predictive outcomes across finance, operations, collections, and other groups within the company. Will collaborate to build the foundation for AI-based decision support and business analytics. The position will be based out of our Reston, VA office, with some travel required to our Manhattan offices. Minimum of 4 days per week in the office required. Not a remote work position.

• Data Analysis and Management:
• Collect, analyze, and interpret complex data sets to identify trends, patterns, and insights.
• Help develop an AI-based natural language interface for ad hoc reporting.
• Contribute to creating and deploying AI and machine learning tools, where needed, to advance the competitive positioning of the company.
• Assist with developing in-house Python libraries to streamline and automate data analytics pipelines.  
• Develop KPIs and other key measures of business operations.
• Develop and maintain interactive dashboards to analyze and visualize key metrics, supporting data-driven decision making for cross-functional teams.
• Maintain and manage data pipelines to ensure seamless data flow and integration.
• Ensure data quality, integrity, and consistency across data warehouse; collaborate cross-functionally to address data quality issues. 

• Predictive Analytics / Model Development:
  • Contribute to developing and implementing predictive and machine learning models to address business challenges and inform strategic decisions.
  • Collaborate with cross-functional teams to apply predictive analytics across various business domains.
  • Optimize and refine models based on performance metrics and feedback.
• Stakeholder Collaboration:
  • Work closely with Data Analytics Team Lead to gather requirements and align analytics and AI/ML initiatives with business goals.
  • Present complex information in a clear and concise manner
  • Identify and propose new process improvement opportunities.
• Research and Innovation:
  • Stay updated with the latest trends and advancements in AI and ML technologies.
  • Conduct research to explore new methodologies and techniques that can be applied to current and future projects.
  • Collaborate with cross-functional teams to drive innovation and help implement cutting-edge solutions.
• Required Skills & Qualifications:
  • Bachelor's degree (Masters preferred) in Information Science, Computer Science, Econometrics, Statistics, or a related field.
  • 3 + years of professional experience in data science, (+ development desirable)
  • Proficiency in SQL and experience working with relational databases and data warehouses.  
  • Strong knowledge and experience of Python and its main data analytics and AI/ML libraries (e.g. Pandas, NumPy, Scikit-learn, Seaborn). Familiarity with object-oriented programming.
  • Experience with data visualization tools such as Tableau, Matplotlib, Seaborn.
  • Experience using version control and collaboration tools such as Git, GitHub/Bitbucket.  
  • Strong understanding of statistical methods, and machine learning algorithms. Previous experience developing ML/Predictive models preferred.
  • Exceptional communication skills to present findings and recommendations effectively.
  • Technical expertise regarding data models, database design development, data mining techniques.
  • Excellent problem-solving skills with the ability to think critically and provide innovative solutions.
  • Passion for learning and staying up to date with the latest industry developments.
• Preferred Skills & Qualification:
  • Previous experience with financial services such as banking, investing, insurance or lending
  • Previous experience with Snowflake is highly preferred  
  • Familiarity with GenAI/LLM frameworks and concepts, e.g. (LangChain, RAG, Vector Databases, Semantic model) highly preferred.
  • Knowledge of cloud-based services and platforms such as AWS (Lambda, S3, EC2s)  
  • Experience in data science + development
  • Prior experience using Jira and Agile methodologies in a team-based project environment.