Hamilton Porter is proud to support the hiring needs, of one of the leaders in small business refinancing. Our long time client, is looking for a Data Scientist.

Location: Hybrid - Arlington, VA

Will develop models to support programs for the organization. Will classify or categorize data to make predictions related to the models.

What You Will Do:

Model Development:

Design, develop, and deploy machine learning models and algorithms to solve business problems or improve processes for Legal/Collections and Sales
Build models to classify account transaction data to benefit underwriting process and merchant insights
Build models including but not limited to credit risk, fraud, and offer acceptance propensity
Perform through testing and validation of models and support various aspects of the business with data analytics, i.e., experience with data and model governance
Research, design, implement and validate cutting-edge algorithms/models to analyze diverse sources of data to achieve targeted outcomes, i.e., be up to date on data science research (papers and libraries); be able to build and evaluate models yourself

Advanced Data Analysis:

Conduct sophisticated analysis on top of models to derive meaningful insights and actionable strategy recommendations.
Identify new data sources and patterns that add lift to predictive modeling capabilities; come in with existing knowledge about relevant datasets and services to leverage
Conduct analysis and turn insights into actionable changes for predictive models or policies; have experience identifying and prioritizing the business impact

Statistical Analysis:

Apply statistical techniques to interpret data, validate models, and ensure robustness of analytical solutions.
Deliver informative and effective findings, results and recommendations from statistical analysis to stakeholders, both technical and non-technical audiences
Recommend ongoing improvements to methods and algorithms currently in production

Collaboration:

Work closely with cross-functional teams such as engineering, product management, and business stakeholders to understand requirements and deliver solutions.

What We’re Looking For:

MS in Statistics, Economics, Finance, or other related quantitative field
Strong understanding of Computer Science fundamentals
3-5 years of relevant experience in applying data science techniques to real-world problems
Strong proficiency Python and SQL for data manipulation, analysis, and modeling
Econometric modeling, traditional modeling techniques (regression, tree-based models), deep learning, Natural Language Processing (NLP)
Agile, Scrum experience
Strong SQL
Big data; experience with Databricks or Snowflake, Linux, AWS
Strong understanding of Software Development Lifecycle (SDLC)
Experience with exploratory data analysis and visualization
Solid understanding of statistical methods and their application in data analysis and modeling
Experience with machine learning techniques and libraries/frameworks (e.g., scikit-learn)
Ability to work with large, complex datasets using tools like Pandas, Spark, or similar
Strong analytical and problem-solving skills to translate business requirements into technical solutions
Able to share a portfolio (e.g., website, github, paper references, etc.) of papers, visualizations, or software
Excellent communication skills to articulate findings and insights to both technical and non-technical stakeholders.

Compensation:

Competitive base salary ($110K - $124K - DOE) + potential for 10% performance bonus
Outstanding company covered Health Coverage - tons of options across Health, Dental, Vision options + Flexible PTO
401K through Fidelity with 25% match
Tons of other company wide perks...

Apply today we are quick to interview.

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