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Staff Data Scientist
2 weeks ago
**About the Team**
Data is at the core of Outreach's strategy. It drives ourselves and our customers to the highest levels of success. We use it for everything from customer health scores and revenue dashboards to operational metrics of our AWS infrastructure, to helping increase product engagement and user productivity through natural language understanding, to predictive analytics and causal inference via experimentation. As our customer base continues to grow, we are looking towards new ways of leveraging our data to deeper understand our customers’ needs and deliver new products and features to help continuously improve their customer engagement workflows.
The mission of the Data Science team is to enable such continuous optimization by reconstructing customer engagement workflows from data, developing metrics to measure the success and efficiency of these workflows, and providing tools to support the optimization of these workflows. At the Process Intelligence squad, our key goal is to transform how sales reps operate by enabling a personalized guided selling process. One example is predicting the likelihood of a deal to win so sales reps can shift their focus strategically toward deals that need attention. In addition to just producing a score as our prediction, we put emphasis on analyzing which factors during the sales process contributed more to the prediction. This allows us to give recommendations to the sales rep on what to do next.
**The Role**
**Your Daily Adventures Will Include**:
- Working with internal and external customers to understand their pain points and brainstorm solutions
- Ensuring the data that feed into our machine learning models are reliable, accurate, and punctual
- Working alongside experienced engineers, designers, and product managers to help deliver new customer-facing features and products
**Our Vision of You**:
- A hybrid data scientist/engineer who can navigate both sides with little help from others
- You have experience working with distributed data processing frameworks such as Spark. Experience with Spark's MLlib, AWS, Databricks, MLFlow are a plus
- You understand the typical life-cycle of machine learning product development, from inception to production
- You have experience with deploying and running ML models in real products
- You are pragmatic, not stubborn with your solutions, and have the mindset of “get the job done”
- You are hands-on, able to quickly pick up new tools and languages, and excited about building things and experimenting
- You go above and beyond to help your team
- You are honest, admit mistakes, and own fixing them
- You are a motivated and talented crafts-person, always looking to sharpen and adapt your skills
- You have an MS or PhD degree in Computer Science, Data Science, or a related field, and 5+ years of industry or equivalent experience
