Remote Data Scientist – Finance (PST Hours)

Eliassen Group; Cheyenne (WY); Remote; USD 103,000 - 116,000; Part time

Benefits offered by this job

Medical, Dental, Vision benefits

401k with company matching

Life insurance

Job summary

Eliassen Group is seeking a Data Scientist for a remote, contract role working on PST hours. The candidate will design, develop, and deploy analytical, statistical, and machine learning solutions to drive customer growth, portfolio performance, profitability, and strategic decision-making.

The role requires collaboration with Marketing, Product, Finance, Treasury, Risk, Technology, and Data Engineering to solve complex business problems.

Qualifications

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

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, O/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.

Job description

Eliassen Group is seeking a Data Scientist for a remote, contract role working on PST hours. The candidate will design, develop, and deploy analytical, statistical, and machine learning solutions to drive customer growth, portfolio performance, profitability, and strategic decision-making.

The role requires collaboration with Marketing, Product, Finance, Treasury, Risk, Technology, and Data Engineering to solve complex business problems.