About Our Client:
This innovative Global technology-based company is looking for a Data Scientist for a full-time/permanent position that is fully remote.
Responsibilities:
● Develop and refine advanced machine learning models and algorithms to optimize
bidding strategies
● Analyze data from Google Ad Manager and other SSPs to understand the market
dynamics and identify revenue maximization opportunities
● Design and evaluate different pricing rules and their impact on network yield
● Work on predictive models to forecast user engagement and other relevant metrics
● Collaborate with the ad engineering team to integrate data science insights into
existing platforms
● Continuously monitor model performance and fine-tune as needed
● Stay updated with the latest trends and technologies in the AdTech space
● Ensure data integrity and compliance with federal, state-level, sector-specific and
GDPR data protection regulations.
Requirements:
● Bachelor’s or Master’s degree in Data Science, Software Engineering, Computer
Science, Statistics, or other scientific or quantitative fields
● 3+ years of experience in a data science role within the AdTech domain. The ideal
candidate should have a proven track record of analyzing complex and diverse
datasets, particularly those derived from header bidding processes, Google Ad
Manager, and comparable ad-serving platforms. This experience should include a
deep understanding of the nuances and dynamics of online advertising data, as well
as a demonstrated ability to extract actionable insights from these datasets to drive
revenue optimization
● Experience in A/B testing for pricing optimization
● Strong knowledge of data science frameworks, machine learning, statistical
modeling and data mining techniques
● Proven experience with SQL in any flavor (MySQL, PostgreSQL, Microsoft SQL
Server, SnowSQL, etc.) with proficiency in writing complex queries for data
manipulation and analysis
● Proven technical knowledge in a data-focused programming language, such as R,
Python or Julia
● Expertise in AWS cloud services specific to Storage (S3, EFS, etc.), Databases
(RDS, Redshift, etc.), Analytics (Athena, AWS Glue, etc.), Machine Learning
(Sagemaker, Forecast, etc.), and Compute (EC2, Lambda, etc.) or equivalent
services on other cloud platforms such as Azure or GCP
● Deep experience with supervised and unsupervised machine learning frameworks
and statistical modeling techniques
● Experience with big data technologies and tools such as Apache Hadoop, Apache
Spark, Apache Hive, Rapidminer, or Elasticsearch
● Familiar with software engineering best practices such as unit testing, code reviews,
design, and documentation
● Ability to present data and analytical findings effectively to both technical and
non-technical audiences