Data Scientist I

We are authentic, professional providers of fun, focused on building a Great Place To Work For All by staying true to our mission: “Life’s a Party, We’re Makin’ It Fun!” and “So Much Fun It’s Scary!”

At Spencer’s and Spirit Halloween, we do the right thing always-integrity, fairness, respect, and transparency are our foundation. You will find our culture to be inclusive, passionate, resilient, and one that values differences and embraces all.

One Team / One Goal

We are leaders and owners of our business success. Whether it’s developing new and exclusive costumes, quality testing products, or implementing technology solutions, our teams understand the value of working collaboratively to embrace change through innovation, curiosity, and thoughtfulness.

We offer a comprehensive benefits package that includes:

• Flexible work environment
• Career advancement
• Competitive base salary
• Bonus opportunity
• Vacation, Personal, Sick and Holiday pay
• Medical, Dental, Vision, Disability, Life and AD&D insurance
• 401k with a company match
• 30% merchandise discount

As a Data Scientist I, you will support business teams by analyzing data and building foundational machine learning models to uncover insights that drive decision-making. You will collaborate with business stakeholders to understand their needs and deliver actionable analytics.

• Assist in data collection, cleaning, and preprocessing for ML projects.
• Conduct exploratory data analysis (EDA) to identify trends and patterns.
• Co-develop and evaluate machine learning models.
• Support business units with ad hoc reporting and insights.
• Collaborate with BI developers and IT to ensure data pipelines and reporting tools meet business needs.
• Document methodologies and maintain analysis reproducibility.
• Work within Databricks and Microsoft Fabric to develop and test ML workflows.

• Bachelor’s in Data Science, Statistics, Mathematics, Computer Science or related field.
• 0–2 years’ experience in analytics or data‑driven role.
• Proficiency in Python, R, or SQL.
• Experience in being able to build and evaluate basic supervised models (e.g., regression, classification) and understand feature engineering workflows.
• Experience with data visualization tools (e.g., Tableau, Power BI).
• Experience with cloud data platforms (Snowflake, Redshift, Azure, Databricks).
• Strong analytical and communication skills.

The pay range reflects the potential base salary range for this role. Individual base pay is determined by various factors such as relevant experience and skills, and the scope and responsibilities of the position.