Data Scientist

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 -

• 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…