Position summary: 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 to do this including:
Bayesian statistics and supervised learning to model conversion rates and revenueLinear programming to balance campaign objectivesScaled AI/ML with Tensorflow/Vertex AI to model a traveler's propensity to bookAs a 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.
This provides each team member the opportunity to gain additional experience with a range of technologies such as Tensorflow, Vertex AI, Docker and the Google Cloud Platform.
What you will do: Design and maintain machine learning models to optimize campaign targetingModel key performance advertising metrics like conversion rates and click-through rates, and use those metrics to automate estimation of campaign bids and budgetsImprove systems that optimize campaign performance and pacingImplement machine learning pipelines on Google Cloud PlatformWrite and ship production-level python codeWrite and execute complex SQL queries to extract and transform data from various sourcesCollaborate with other applied scientists, software engineers and product managers to design and implement solutions based on business requirementsDocument code and processes for future reference and maintainability.Participate in the entire Agile development lifecycle, including sprint planning, stand-ups, and retrospectivesWhat you bring to the table:Essentials You have hands-on experience building production-level ML and data products.You have expert-level understanding of data science topics.You have at least two years of experience as an applied scientist / data scientist / ML engineer.You have an MS or PhD in computer science or a quantitative discipline, or equivalent experience.You have written and put Python code into production and can reason about algorithmic efficiency.You have strong knowledge of cloud computing platforms, such as AWS, Azure, or Google Cloud.You can design and apply machine learning models (supervised, unsupervised, reinforcement learning etc.)
to solve business problems.You can effectively communicate with applied scientists, data scientists, engineers and product managers.You can evaluate, analyze and interpret model results resulting in further improvement of existing statistical model performanceYou can perform complex data analysis using SQL/Jupyter notebook to find underlying issues and propose a solution to stakeholders explaining the various trade-offs associated with the solution.You can use your grit and initiative to fill in gaps and drive projects to completionNice to haveYou have experience with Google Cloud PlatformYou have good knowledge of at least one other programming language in addition to Python (Go, C++, etc.
)You have experience with DockerYou have at least one year of experience within the Ad Tech ecosystemWhat we have for you: We take a whole-person approach to create a Sojernista Experience that allows our people to thrive, not just as employees, but as humans.
As an employee of Sojern, you would benefit from this in the following ways:
Rewards & Recognition: Competitive compensation packages, stock options offered to every employee, Bonusly program to reward and recognize team wins and performance, plus employees can take up to 40 hours of paid time per year to volunteer and give back to the communityFlexibility: Flexi-Friday benefit, hybrid or remote work options for most roles, time-zone friendly work hours with async collaborationConnection: Team offsites planned annually, six employee resources groups, regular virtual and in-office team building events, monthly company All Hands & leadership Q&AsWellbeing: PTO allowance to recharge, comprehensive healthcare options, paid parental leave (16 weeks for birthing parents; 12 weeks for non-birthing parents), retirement contributions and investment options (for applicable locations), travel benefits (hotel stay benefit & IATA membership), plus mental health, wellness & financial health resourcesGrowth: Learning & development stipend, mentorship program, career development programs, leadership trainingProductivity: Home office tech set up (laptop, monitor, keyboard, mouse), monthly internet and phone allowance, modern tools to communicate and collaborate (Slack, Google Suite)Our Sojernista First workplace philosophy is designed to take a flexible approach, recognizing that the needs of our employees may differ depending on their role, team, or location.
What does not differ is our focus on building genuine connections, increasing global collaboration, and providing programs, tools and resources centered around the needs and wellbeing of our employees, regardless if you are working in an office, hybrid, or fully remote.
About Sojern: At Sojern, we believe in the power of travel as a way to bring the world together.
It is that passion that drives Sojern to build smart digital solutions that help travel marketers reach travelers efficiently, and increase long-term growth, customer loyalty and profitability.
Our customers include hotels, attractions and tourism boards, and they use the power of machine learning, data science and real-time traveler data in Sojern's products to build direct relationships with travelers across social, mobile and the web.
Now, more than ever, our thousands of customers rely on Sojern to drive visits, bookings, and ticket sales by engaging with travelers as they plan their travel.
As a globally distributed company, we are headquartered in San Francisco with employees based in 14 countries and counting.
Our team is passionate about travel and the core values that define our culture: Win as a Team, Embrace Inclusion, Be Genuine, Deliver Wow, and Center Around the Customer.
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