Data Scientist - W2 ONLY - REMOTE - Time Series Forecasting & Causal Inference

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• NOTE: W2 only - REMOTE
• NOTE: W2 only - REMOTE
• NOTE: W2 only - REMOTE

Job Title: Data Scientist Time Series Forecasting & Causal Inference

Location: Remote

Job Type: 3-Month Contract (High Potential to Extend)

Job Summary

This role will support teams focused on immunization insights and labor forecasting by building time series forecasting and causal inference models. The ideal candidate brings a proven track record of selecting and justifying appropriate modeling techniques, paired with strong data preparation and integration skills.

This position requires someone who is not only technically proficient in model building but also meticulous in data sourcing, merging, and cleansing. Candidates who overlook critical integration steps or struggle with filtering and preparing real-world datasets will not be a good fit.

Key Responsibilities

• Run advanced time series forecasting and causal inference models to support immunization and labor planning efforts.
• Take full ownership of the end-to-end modeling pipeline from data acquisition and integration (including multiple formats like Excel, Snowflake, and Teradata) to final model output.
• Demonstrate sound judgment in model selection (e.g., linear regression vs. XGBoost vs. time series), and articulate the rationale behind these choices.
• Collaborate with cross-functional teams to understand data sources and business context.
• Prepare accurate and clean datasets by properly merging data from multiple sources, applying relevant filters, and identifying any gaps in data (e.g., missing files or sheets).
• Avoid common modeling pitfalls (e.g., incorrect variable encoding) and ensure statistical integrity throughout the modeling process.

Required Skills & Experience

• 5+ years of data science experience in applied settings, ideally in healthcare, retail, or labor forecasting domains.
• Proven experience in time series forecasting and causal inference modeling.
• Expertise in Python, with hands-on experience using Snowflake, Teradata, and Databricks.
• Demonstrated ability to work across functions and with a variety of stakeholders to deliver high-impact insights.
• Strong foundational skills in data integration, including merging datasets, handling structured data (e.g., Excel sheets), and applying accurate data filtering techniques.
• Comfortable working in fast-paced environments with tight deadlines and evolving priorities.

Nice to Have

• Experience with XGBoost and other advanced machine learning models.
• Familiarity with immunization data or labor scheduling datasets.
• Previous consulting or contract work within a large, matrixed organization.

What We Re Not Looking For

• Candidates with primarily data engineering
• Individuals who rely solely on pre-prepared datasets without verifying data completeness or quality.
• Modelers who cannot justify their algorithm selection or overlook basic data preparation steps.