Data Scientist, Sales & CS (SF)

The Data Science and Engineering team works closely with our product, customer success, marketing, and sales teams; we help them ask questions the right way — and then find the answers. Our data informs us of the impact we are having on the world, and the Data team is crucial to architecting and building our data infrastructure. We design and use data analysis tools that increase our data’s scalability, accuracy, and accessibility. We proactively inform our company's goals and direction with data so that our product can help more teams do great things. With more than 1 billion tasks and 50,000+ paying organizations, we have an incredibly rich data set for understanding how teams work together using Asana and how we can make them even more effective.

We are looking for a data scientist to partner with our Sales and Customer Success team. You will design and build data products to increase the productivity of Asana’s global sales engine. In this role, you will also be the voice of data in strategic discussions with business leadership that are relevant to your area.

What you’ll achieve

• Build models and conduct analyses to proactively identify opportunities and risks for the Sales team in their book of business. 
• Construct frameworks and build metrics to evaluate the performance and impact of various sales teams.
• Investigate high-level questions like “What’s the next best team/company that Sales should reach out to?” or “What sales activities help reduce the length of a sales cycle?”
• Collaborate with Sales and Customer Success stakeholders, Revenue Operations, Sales Insights, and other cross-functional partners to identify impactful business questions. 
• Conduct deep-dive analysis, and communicate actionable recommendations to drive decisions. 
• Explore and identify opportunities to develop data science products that can uplevel Asana’s Sales effectiveness and efficiency.

About you

• 2+ years of experience in applying data science techniques to drive business decisions
  Strong technical background in computer science, statistics, math, information science, or another quantitative field
• Fluency in at least one modern language useful for statistics and/or data processing (e.g. Python, R, Scala)
• Proficiency with relational data modeling and SQL
• Expertise in statistical methods including experimental design, regression, causal inference with observational data, time series modeling.
• Familiarity with one or more of the machine learning approaches in classification, ranking, or clustering.
• Strong ability in managing stakeholders, communicating complex concepts to diverse audiences, and crafting compelling stories.
  

It's great, but not required if you have:

• Familiarity with SaaS business model, sales-assisted growth, or SFDC data model
• Experience in working on ambiguous projects with multiple cross-functional stakeholders
• Experience in writing production-quality code in Python/Scala and productionizing machine learning applications with tools such as Git, Sagemaker, Airflow.
• Graduate degree in Computer Science, Math, Statistics, Economics, Marketing Science, Engineering, or a related quantitative field.