Associate Data Developer
Team: BHG
Location: Maryland, United States, Remote USA
Commitment: Full time
Workplace Type: remote
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.
Qualifications
- 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.
Nice to Have
- Exposure to deploying or productionizing machine learning models in any capacity.
- Familiarity with MLOps concepts such as model versioning, monitoring, or retraining.
- Background in digital marketing analytics, attribution, or performance optimization.
- Experience working with third-party analytics or attribution APIs (e.g., AppsFlyer or similar).
- Games industry experience and a passion for games.
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