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 additional 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 (supervised, unsupervised, reinforcement learning, etc.) 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 to find underlying issues and propose solutions is required.
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 at least one other 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 offered to every employee, and a Bonusly program to reward and recognize team wins and performance are included.
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 for most roles, and time-zone friendly work hours with async collaboration.
Team offsites are planned annually, and there are six employee resource groups, regular virtual and in-office team building events, and monthly company All Hands & leadership Q&As.
A PTO allowance to recharge, comprehensive healthcare options, paid parental leave (16 weeks for birthing parents; 12 weeks for non-birthing parents), retirement contributions, travel benefits, and mental health resources are offered.
A learning & development stipend, mentorship program, career development programs, and leadership training are available for growth.
Home office tech setup (laptop, monitor, keyboard, mouse), monthly internet and phone allowance, and modern tools for communication and collaboration (Slack, Google Suite) are provided for productivity.