Analytics Engineer

Position Summary

Role and Responsibilities

Samsung Ads, the advertising monetization arm of Samsung Electronics, leverages proprietary real-time TV viewing behavior and insights to promote relevant brands and content experiences to consumers. We partner with brands, agencies and content owners to deliver unique advertising opportunities on native placements within our Smart TV platform and programmatically with a cross device solution.

Samsung’s unique first party data help brands connect to their audience as they explore content across desktop, mobile, tablets and our Smart TVs. The Samsung Ad platform delivers high-quality audience targeting powered by three key components: first-party audience data at scale, world-class data science, and brand-safe cross-device ad inventory.

We’re looking for an innovative individual to support the Samsung Ads Client Analytics team. This position will create innovate data models, reporting solutions, and tools from one of the richest TV viewership/media consumption databases in the industry today.

The candidate will build data infrastructure and customized reporting solutions to guide strategy and ad sales leveraging Snowflake data warehouse and using SQL, Python, AWS S3, Tableau, and DOMO for our top enterprise clients.
The candidate will explore data to report on ad campaign performance, find trends and identify new client growth opportunities. Also, the candidate will help tune and improve current code base.
Candidate must be organized, detailed oriented, flexible and possess ability to establish priorities with minimal guidance in a fast paced environment – must be proactive, analytical problem solver and strategic thinker who is able to draw conclusions - not just report numbers.
Candidates must have prior data engineering experience and strong SQL and Python skills.

Responsibilities
Working closely with internal stakeholders, translate business requirements into technical architecture for reporting solutions in a scalable, automated way.

Transform and cleanse outputs into meaningful analysis for business/sales teams using SQL and Python.

Explore data to identify client ad performance opportunities, trends and anomalies, contribute to new reporting capabilities/solutions.

Architect data pipelines to connect different data sources and automate reporting flows.

Develop and maintain complex data warehousing, modeling, and attribution systems for use by internal stakeholders customized to unique business requirements.

Tune and optimize current reporting solutions to meet updated client needs, new measurement methodologies, or improve query performance.

Perform advanced analytics including measuring AB Test and Incrementality testing, evaluating statistical significance, and providing power analyses for research designs.

Qualifications

• Bachelors and 6+ years in a related engineering/analytics work OR Masters and 4+ years.
• Advanced SQL skills – 4+ years using SQL.
• Proficient in 1 or more programming languages (Python, R, etc).
• 4+ years of Python experience.
• Expertise with Snowflake and AWS for automation and data modeling.
• Experience building, maintaining, and optimizing complex data pipelines with business outcome applications for advertisers.
• Jira, Confluence, GitHub and other agile development tool experience.
• Experience with Data Visualization tools such as DOMO, Tableau.
• Experience with automation, and ability to build custom solutions for unique client needs across various software tools.
• Ability to communicate technical roadblocks to non-technical stakeholders.
• Advanced Analytics experience and Measurement experience.
• Bachelors degree in related major (computer science/engineering or quantitative discipline (Economics, Statistics, Engineering, Analytics, Physics, Mathematics)) required; Masters a plus.

Bonus:

• Familiarity with media, TV measurement.
• Experience designing AB tests.
• Exposure to Data Cleanrooms.

Skills and Qualifications

The salary range for this role is expected to be between $135,000 and $170,000.  Actual pay will be determined considering factors such as relevant skills and experience, and comparison to other employees in the role.

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