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Mid LevelFull-timePythonMachine LearningData ScienceGit
Salary Range
$75,000 - $80,000 /year
About the Role
We are looking for a Data Developer to join our team at Big Huge Games. This role focuses on developing data-driven insights, models, and analytical systems that inform game development, player experience, and marketing performance.
Key Responsibilities
- →Contribute to the design, build, and maintenance of data pipelines that ingest player, game, and marketing data from databases, event streams, and external APIs.
- →Assist in developing, evaluating, and iterating on machine learning models for use cases such as LTV prediction, churn forecasting, player segmentation, and marketing optimization.
- →Build and optimize analytical datasets and feature pipelines that support modeling, experimentation, and reporting.
- →Partner with Product, Game Design, Marketing, and Analytics teams to help frame business questions, define success metrics, and surface actionable insights.
- →Support data quality, reliability, and reproducibility through testing, documentation, and version control.
- →Help integrate model outputs into dashboards, reporting tools, or downstream systems to support operational decision-making.
- →Continuously learn and improve your own analytical workflows, modeling approaches, and data tooling under the guidance of senior team members.
Requirements
- ✓Bachelor's degree in Data Science, Computer Science, Statistics, Mathematics, or a related quantitative field, or equivalent professional experience.
- ✓1–3 years of professional (non-academic) experience in a data, analytics, or engineering role.
- ✓Proficiency in Python for data analysis and modeling, with some exposure to working with RESTful APIs.
- ✓Working knowledge of statistical methods and machine learning techniques applied to real-world datasets.
- ✓Solid SQL skills and experience querying large datasets; familiarity with cloud data warehouses (e.g., Snowflake, BigQuery, or Redshift) is a plus.
- ✓Some exposure to data transformation or orchestration tools (e.g., dbt, Airflow) is a plus but not required.
- ✓Willingness to independently own tasks and work through ambiguous problems, with support from the broader team.
- ✓Clear communication skills with the ability to explain analytical findings to both technical and non-technical stakeholders.
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