Data Engineer (Decision Science)

Paramount Pictures; New York (NY); Remote; USD 80,000 - 120,000; Full time

Job summary

An established industry player is seeking a Data Engineer to join their Applied Intelligence Personalization Team. This exciting role involves analyzing engagement metrics and optimizing recommendation strategies through advanced data analytics. The ideal candidate will leverage their expertise in SQL, Python/R, and visualization tools to design data pipelines and enhance decision-making processes. With a focus on collaboration and innovation, this position offers a remote-friendly work environment where your contributions will shape the future of personalization and engagement analytics. Join a team that values learning and creativity in a dynamic field.

Benefits

Remote-friendly work setup

Collaborative team environment

Culture of learning and innovation

Qualifications

• 2+ years in Analytics Engineering or Decision Science with expert SQL and Python/R skills.
• Experience in A/B testing frameworks and optimization of large-scale data queries.

Responsibilities

• Design and maintain data pipelines for engagement metrics and A/B test results.
• Communicate insights and recommendations to stakeholders effectively.
• Monitor A/B testing results to optimize personalization models.

Skills

SQL

Python/R

Statistical Analysis

A/B Testing

Data Visualization

Data Analytics

Problem-Solving

Education

Bachelor's Degree in a relevant field

Tools

Apache Superset

BigQuery

Google Cloud Platform (GCP)

dbt (Data Build Tool)

Looker

Job description

The Applied Intelligence Personalization Team at Paramount is looking for a Data Engineer - Engagement & Experimentation to join our team. This role will focus on analyzing engagement metrics, evaluating experiment results, and optimizing our recommendation and personalization strategies. The ideal candidate will be an expert in SQL, Python/R, streaming data processing, and visualization tools like Apache Superset, ensuring that insights drive impactful decision-making.

Responsibilities Include:

1. Design and maintain data pipelines and analytics frameworks to track engagement metrics and A/B test results.
2. Assist in data validation, feature engineering, and exploratory data analysis.
3. Query, clean and analyze large datasets with an emphasis on statistical analysis.
4. Develop and optimize Superset dashboards and reports for experimentation insights and KPI tracking.
5. Communicate results and recommendations to technical and non-technical stakeholders.
6. Work with large-scale structured and semi-structured datasets, designing appropriate decision science tests for analytics and reporting.
7. Monitor and analyze A/B testing results to optimize personalization models and content recommendations.
8. Implement standard processes for statistical testing, quality, and documentation.

Key Projects:

1. Develop real-time engagement tracking and experimentation analysis pipelines.
2. Optimize streaming data workflows for user behavior analysis.
3. Enhance Python scripting to support data-driven decision-making.

Basic Qualifications:

1. 2+ years of experience in Analytics Engineering or Decision Science in a high-scale environment, along with expert-level SQL skills, experience in BigQuery or other cloud-based data warehouses, and proficiency in Python/R or other scripting languages for data manipulation and statistical modeling.
2. Strong experience optimizing large-scale data queries and pipelines for performance and efficiency, along with experience building Decision Science testing or statistical modeling for A/B testing.
3. Strong analytical mindset with experience in A/B testing frameworks and experimentation methodologies, along with the ability to optimize large-scale data queries and pipelines.

Additional Qualifications:

1. Strong communication skills to collaborate with ML engineers, data scientists, and product teams.
2. Hands-on experience with dbt (Data Build Tool) for transformation workflows.
3. Knowledge of data governance and quality best practices.
4. Familiarity with Google Cloud Platform (GCP), BigQuery, and Looker.
5. Experience working with personalization and recommendation systems.
6. Strong problem-solving skills and a passion for Decision Science methodologies.
7. Interest in open-source contributions and industry standard processes for analytics engineering.

What We Offer:

1. A culture of learning focused on innovation in data analytics and personalization.
2. A collaborative team environment where data drives decision-making.
3. A remote-friendly work setup with the opportunity to work on innovative engagement analytics and experimentation frameworks.

This role is a great opportunity to shape the future of personalization through advanced data analytics, experimentation, and real-time engagement tracking.