Description:

We are looking for a talented and motivated Senior Applied Scientist to help improve the performance of our targeting and optimization products.
The Applied Science team at Sojern develops services and pipelines to optimize advertising campaign performance and applies machine learning at scale for thousands of customers.
We utilize a range of algorithms and methods including Bayesian statistics and supervised learning to model conversion rates and revenue, linear programming to balance campaign objectives, and scaled AI/ML with Tensorflow/Vertex AI to model a traveler’s propensity to book.
As part of the Science and Optimization team, we deliver through the full data product life-cycle: from prototyping to production development to A/B testing and measurement.
Team members have the opportunity to gain experience with technologies such as Tensorflow, Vertex AI, Docker, and the Google Cloud Platform.
Responsibilities include designing and maintaining machine learning models to optimize campaign targeting, modeling key performance advertising metrics, improving systems that optimize campaign performance, implementing machine learning pipelines on Google Cloud Platform, writing and shipping production-level Python code, executing complex SQL queries, collaborating with other team members, documenting code and processes, and participating in the Agile development lifecycle.

Requirements:

You must have hands-on experience building production-level ML and data products.
An expert-level understanding of data science topics is required.
At least two years of experience as an applied scientist, data scientist, or ML engineer is necessary.
A Master's or PhD in computer science or a quantitative discipline, or equivalent experience, is required.
You should have experience writing and putting Python code into production and reasoning about algorithmic efficiency.
Strong knowledge of cloud computing platforms such as AWS, Azure, or Google Cloud is essential.
You must be able to design and apply machine learning models to solve business problems.
Effective communication skills with applied scientists, data scientists, engineers, and product managers are necessary.
You should be able to evaluate, analyze, and interpret model results to improve existing statistical model performance.
Experience performing complex data analysis using SQL/Jupyter notebook is required to find underlying issues and propose solutions.
You should demonstrate grit and initiative to fill in gaps and drive projects to completion.
Nice to have: experience with Google Cloud Platform, knowledge of another programming language (Go, C++, etc.), experience with Docker, and at least one year of experience within the Ad Tech ecosystem.

Competitive compensation packages, stock options for every employee, and a Bonusly program to reward team wins and performance are offered.
Employees can take up to 40 hours of paid time per year to volunteer and give back to the community.
Flexibility is provided through a Flexi-Friday benefit, hybrid or remote work options, and time-zone friendly work hours.
Team offsites, employee resource groups, and regular team-building events foster connection among employees.
A comprehensive PTO allowance, healthcare options, paid parental leave, retirement contributions, travel benefits, and mental health resources are included for wellbeing.
Learning and development stipends, mentorship programs, and career development opportunities support growth.
Home office tech setup, monthly internet and phone allowances, and modern collaboration tools enhance productivity.