Data Scientist

Eliassen Group; Richmond (VA); A distancia; USD 103.000 - 116.000; Jornada completa

Descripción de la vacante

Eliassen Group is seeking a Data Scientist for a remote contract role operating on PST hours in the banking and financial services sector. You will design, develop, and implement analytical, statistical, and machine learning solutions to drive customer growth, portfolio performance, profitability, and strategic decision-making.

The role collaborates with Marketing, Product, Finance, Treasury, Risk, Technology, and Data Engineering to solve complex business problems using data.

Formación

• 3+ years in Data Science, Machine Learning, or related field.
• Experience delivering end-to-end analytical solutions from requirements through implementation.
• Experience with large-scale structured and unstructured datasets.
• Experience partnering with stakeholders to solve business problems with data-driven solutions.
• Advanced SQL for large-scale data extraction, transformation, and analysis.
• Python for analytics, automation, ML, and model development.
• Statistical modeling, forecasting, and ML techniques.
• Experimental design, hypothesis testing, and causal inference.
• Data visualization and data storytelling.
• Data quality validation and root-cause analysis.

Responsabilidades

• Design, develop, validate, and maintain predictive and forecasting models.
• Apply ML and advanced analytics to support customer growth and portfolio performance.
• Execute end-to-end analytical workflows from data extraction to deployment and monitoring.
• Develop scalable analytical datasets, workflows, and data pipelines.
• Evaluate emerging analytical methodologies to improve outcomes.
• Analyze customer acquisition, onboarding, engagement, retention, and product performance.
• Develop customer segmentation methodologies and behavioral models.
• Identify key drivers of value, retention, profitability, and portfolio performance.
• Conduct deep-dive analyses to uncover actionable insights and opportunities.
• Quantify impact of business initiatives using statistical methods.
• Develop forecasting models for growth, balances, deposits, and funding activity.
• Build optimization frameworks for planning and pricing decisions.
• Evaluate scenarios and quantify risks and opportunities.
• Partner with stakeholders to define metrics and measure results.
• Design and evaluate controlled experiments and A/B tests.
• Establish measurement methodologies and success metrics.

Conocimientos

Data Science

Machine Learning

SQL

Python

Statistical Modeling

Experimentation

Causal Inference

Data Visualization

Analytical Thinking

Communication

Stakeholder Engagement

End-to-End Analytics

Educación

Bachelor's degree in Data Science/Statistics/CS/Mathematics

Master's degree preferred

Herramientas

SQL

Python

Descripción del empleo

Data Scientist

Anywhere

Type: Contract

Category: Data

Industry: Financial Services

Workplace Type: Remote

Standard Hours: Open

Reference ID: JN -102026-109220

Date Posted: 10/26/2026

Shortcut: http://careers.eliassen.com/1vCyha

Description:

Remote (west coast hours)

Our client, an industry leader in banking and financial services, has an excellent contract opportunity for a Data Scientist working remote on PST. The role designs, develops, and implements analytical, statistical, and machine learning solutions that drive customer growth, portfolio performance, profitability, and strategic decision-making. The position serves as a key technical contributor within the Data Science & Analytics team, partnering with Marketing, Product, Finance, Treasury, Risk, Technology, and Data Engineering to solve complex business problems using data. The role requires expertise in large-scale data processing, predictive modeling, experimentation, forecasting, and customer analytics, along with the ability to translate business needs into scalable analytical solutions and communicate findings to stakeholders.

We can facilitate w2 and corp-to-corp consultants. For our w2 consultants, we offer a great benefits package that includes Medical, Dental, and Vision benefits, 401k with company matching, and life insurance.

Rate: $74.46 to $84.46/hr. w2

JN -102026-109220

Responsibilities:

• Design, develop, validate, and maintain predictive, forecasting, classification, segmentation, and optimization models.

• Apply machine learning, statistical modeling, and advanced analytical techniques to support customer acquisition, retention, portfolio growth, pricing, profitability, and operational efficiency.

• Execute end-to-end analytical workflows including data extraction, feature engineering, model development, validation, deployment, monitoring, and performance measurement.

• Develop scalable and reusable analytical solutions, model frameworks, and code libraries.

• Evaluate and implement emerging analytical methodologies and technologies to improve business outcomes.

• Analyze customer acquisition, onboarding, engagement, retention, funding behavior, and product performance.

• Develop customer segmentation methodologies and behavioral models to support growth initiatives and customer experience improvements.

• Identify key drivers of customer value, retention, attrition, profitability, and portfolio performance.

• Conduct deep-dive analyses to uncover actionable insights and business opportunities.

• Quantify the impact of business initiatives using statistical and analytical methodologies.

• Develop forecasting models for customer growth, balances, deposits, funding activity, and other key business metrics.

• Build optimization frameworks to support business planning, customer strategies, portfolio management, and pricing decisions.

• Evaluate scenarios and quantify business risks, opportunities, and expected outcomes.

• Partner with stakeholders to define performance metrics and measure business results.

• Design, execute, and evaluate controlled experiments, A/B tests, and pilot programs.

• Establish measurement methodologies and success metrics for strategic initiatives.

• Apply causal inference and statistical techniques to measure incremental business impact.

• Provide recommendations based on quantitative evaluation of business strategies and initiatives.

• Develop and optimize SQL and Python solutions for data extraction, transformation, analysis, and automation.

• Build scalable analytical datasets, automated workflows, and data pipelines.

• Develop reusable tools and frameworks to improve efficiency and consistency across analytical projects.

• Partner with Technology and Data Engineering teams to improve data accessibility, reliability, and scalability.

• Investigate data anomalies, reporting discrepancies, and model performance issues.

• Perform root-cause analysis and recommend corrective actions.

• Develop automated data quality controls, validation processes, and monitoring frameworks.

• Ensure analytical solutions adhere to governance, documentation, and reproducibility standards.

• Partner with business leaders and cross-functional teams to define analytical requirements and prioritize opportunities.

• Translate business challenges into analytical approaches and technical solutions.

• Present analytical findings, model results, assumptions, risks, and recommendations to technical and non-technical audiences.

• Serve as a trusted advisor on advanced analytics, machine learning, and measurement methodologies.

Experience Requirements:

• 3+ years in Data Science, Machine Learning, Advanced Analytics, Quantitative Modeling, or a related field.

• Experience delivering end-to-end analytical solutions from requirements through implementation and production support.

• Experience with large-scale structured and unstructured datasets.

• Experience partnering with stakeholders to solve business problems with data-driven solutions.

• Advanced SQL for large-scale data extraction, transformation, and analysis.

• Python for analytics, automation, machine learning, and model development.

• Statistical modeling and machine learning techniques, predictive analytics, and forecasting.

• Experimental design, hypothesis testing, and causal inference.

• Data visualization and data storytelling.

• Data quality validation and root-cause analysis.

• Large-scale data processing and analytics.

• Strong verbal and written communication with the ability to translate analytical findings into actionable recommendations.

Education Requirements:

• Bachelor's degree in Data Science, Statistics, Computer Science, Mathematics, Economics, Engineering, Operations Research, Physics, or a related quantitative field required.

• Master's degree or higher in a related quantitative discipline preferred.