Data Scientist | Data & Engineering Team

WHY DEPT®?

We are pioneers at heart. What this means, is that we are always leaning forward, thinking of what we can create tomorrow that does not exist today. We were born digital and we are a new model of agency, with a deep skillset in tech and marketing. That’s why we hire curious, self-driven, talented people who never stop innovating.

Our culture is big enough to cope and small enough to care. Meaning, that with people across 20+ countries, we’re big enough to provide you with the best tools, global opportunities, and benefits that help you thrive. While acting small by investing in you, your growth, your team, and giving you the autonomy to solve our clients' problems, no matter where you are in the world. 

This is remote role, however you must be located within 50 miles of San Diego, CA to be considered.

What do we do?

The Data & Engineering team provides technology solutions by architecting and developing enterprise systems using a variety of programming languages, tools, and platforms. This can range from building data warehouses and web applications, to implementing reporting platforms. We work in small teams, own the projects that we work on, and have direct input into the business decisions of our clients.

The Role:

We are looking for a well-rounded, flexible Data Scientist with an interest in translating business goals into concrete solutions. You’ve been part of more than one team, you’ve demonstrated initiative on most of your projects, and you can tell us in technical detail what you did to help. Ideally, you’ve worked with at least one DevOps team, and in at least one flavor of agile.  If you haven't, we won’t hold that against you. At DEPT®, we pride ourselves on our pragmatic, engineering approach to making data work for the business.

What you’ll bring:

• Self-Starter: Must be proactive and able to work independently, taking ownership of projects and driving them forward with minimal supervision.
• Collaborative: Will work closely with cross-functional teams, particularly Data Operations, while being responsible for leading and managing the overall project.
• Full Life Cycle Accountability: Responsible for end-to-end project management, including:
• Development: Designing and building solutions.
• Testing: Ensuring quality through comprehensive testing.
• Deployment: Overseeing the deployment process.
• Optimization: Continuously improving performance and efficiency.
• Support: Providing ongoing maintenance and support to ensure long-term success.
• Experience across multiple technical and functional domains in order to identify and execute optimal technical solutions in a variety of internal/client situations.
• You understand design decisions and can articulate the tradeoffs made.
• You are aware of industry trends and how they affect our work and introduce new ideas into our current workflow.
• You offer advice and opinions for technical decisions that affect multiple clients/projects or the entire company.
• You can communicate context, recommendations, and rationale to relevant internal and/or external stakeholders to drive towards buy-in
• You demonstrate the ability to take a step back and question/ensure that work proposed/being done is maximizing client value delivery.
• You can synthesize input from various team members to drive to a solution.

Minimum requirements:

• Experience with experimental design, execution and data-driven measurement solutions
• Experience with (traditional) Natural Language Processing, Forecasting, Supervised and Unsupervised learning
• Excellent statistical programming skills (R, Python, etc)
• Advanced knowledge of SQL and how to utilize it for machine learning purposes
• 3+ years of experience/background in Data Science (degree in statistics, data science computer science, etc)
• You have experience with the implementation/execution, prototyping and productionalization of data science solutions
• You are good with data visualization, and data storytelling
• You are able to translate complex data science concepts into easy to understand language.

Preferred requirements:

• Experience with cloud environments (such as but not limited to Databricks, AWS)

• Experience with building and training Neural Networks from scratch
• Experience with fine-tuning (transfer-learning) pre-trained models
• Experience with frameworks like Tensorflow, JAX & Pytorch
• Experience with MLOps (MLFlow, Kubeflow, Sagemaker, Tfx, etc)
• Experience with Hugging Face, Spacy, NLTK, Elastic Search

WHAT DO WE OFFER?