Data Scientist
Asana
Use the employer link to read the full source listing and submit your application.
Listing data may include public employer ATS feeds and Jobs by Adzuna.
Before you apply
The decision-making details job seekers want first
We pulled the strongest signals from the listing so you can quickly judge fit, compensation, and what the company expects before opening the full source post.
Compensation
Salary & market context
189% above the BLS national median
BLS national median: $74,680
- To ensure pay is fair and not impacted by biases, we're committed to looking at market value which is why we check ourselves and conduct a yearly pay equity audit.
- In addition to base salary, your compensation package may include additional components such as equity, sales incentive pay (for most sales roles), and benefits.
- We strive to provide equitable and competitive benefits packages that support our employees worldwide and include: Mental health, wellness & fitness benefits Career coaching & support Inclusive family building benefits Long-term savings or retirement plans In-office culinary options to cater to your dietary preferences These are just some of the benefits we offer, and benefits may vary based on role, country, and local regulations.
Requirements
Top requirements
- Bachelor Degree in Math, Statistics, Computer Science, Engineering a related quantitative field, or equivalent experience
- 4+ years of experience in a data science role, successfully driving the architecture and execution of large-scale production data science projects
- 3+ years of experience collaborating with Marketing functions on deep technical projects, with extensive experience designing, implementing, and deploying marketing models (e.g. MMM, LTV, MTA, Uplift)
- Expert-level knowledge in advanced statistical modeling, causal inference, experimental design and analysis, and machine learning techniques relevant to marketing effectiveness
Perks & setup
Benefits candidates care about
- Research, prototype, and advocate for emerging capabilities and state-of-the-art models in the marketing data science space, demonstrating their potential benefits and leading their implementation.
- To ensure pay is fair and not impacted by biases, we're committed to looking at market value which is why we check ourselves and conduct a yearly pay equity audit.
- In addition to base salary, your compensation package may include additional components such as equity, sales incentive pay (for most sales roles), and benefits.
- If you're interviewing for this role, speak with your Talent Acquisition Partner to learn more about the total compensation and benefits for this role.
Why candidates care
Benefits & perks
- Research, prototype, and advocate for emerging capabilities and state-of-the-art models in the marketing data science space, demonstrating their potential benefits and leading their implementation.
- To ensure pay is fair and not impacted by biases, we're committed to looking at market value which is why we check ourselves and conduct a yearly pay equity audit.
- In addition to base salary, your compensation package may include additional components such as equity, sales incentive pay (for most sales roles), and benefits.
- If you're interviewing for this role, speak with your Talent Acquisition Partner to learn more about the total compensation and benefits for this role.
- We strive to provide equitable and competitive benefits packages that support our employees worldwide and include: Mental health, wellness & fitness benefits Career coaching & support Inclusive family building benefits Long-term savings or retirement plans In-office culinary options to cater to your dietary preferences These are just some of the benefits we offer, and benefits may vary based on role, country, and local regulations.
- If you're interviewing for this role, speak with your Talent Acquisition Partner to learn more about the total compensation and benefits for this role. #LI-Hybrid #LI-SA About us Asana is a leading platform for human + AI collaboration.
Start here
Requirements
- Bachelor Degree in Math, Statistics, Computer Science, Engineering a related quantitative field, or equivalent experience
- 4+ years of experience in a data science role, successfully driving the architecture and execution of large-scale production data science projects
- 3+ years of experience collaborating with Marketing functions on deep technical projects, with extensive experience designing, implementing, and deploying marketing models (e.g. MMM, LTV, MTA, Uplift)
- Expert-level knowledge in advanced statistical modeling, causal inference, experimental design and analysis, and machine learning techniques relevant to marketing effectiveness
- Proven track record developing, deploying, and maintaining scalable production ML solutions and data products
- Technical Stack: Expert proficiency in SQL and Python. Experience with MLOps tools (e.g., MLFlow), statistical languages (e.g., R), and distributed data processing systems (e.g., Spark, Redshift) is a plus
- Demonstrates curiosity about AI tools and emerging technologies, with a willingness to learn and leverage them to enhance productivity, collaboration, or decision-making.
- What we’ll offer:
Responsibilities
What you'll do
- In your role on the Marketing Data Science team, you will be the deepest technical expert responsible for using data and scientific techniques to design and build scalable, state-of-the-art solutions to enhance Asana’s marketing effectiveness.
- You will drive the technical roadmap for data science, collaborating with marketing leadership and the broader Asana data community to uncover new opportunities.
- You will provide technical leadership and hands-on mentorship, elevating the team's technical bar and influencing overall business strategy through best-in-class modeling and experimental design.
- What you’ll achieve: Architect, design, and lead the technical execution for the Marketing Data Science roadmap, serving as the Solution Architect for all core projects including Media Mix Modeling (MMM), User Lifetime Value, Causal Inferences, Multi-touch Attribution, and Spend Optimization engines.
- MMM, LTV, MTA, Uplift) Expert-level knowledge in advanced statistical modeling, causal inference, experimental design and analysis, and machine learning techniques relevant to marketing effectiveness Proven track record developing, deploying, and maintaining scalable production ML solutions and data products Technical Stack: Expert proficiency in SQL and Python.
Role snapshot
About the role
The Data Science team at Asana is pivotal in fulfilling our mission by fostering a data-driven approach in shaping both our product and business strategies. In your role on the Marketing Data Science team, you will be the deepest technical expert responsible for using data and scientific techniques to design and build scalable, state-of-the-art solutions to enhance Asana’s marketing effectiveness. You will drive the technical roadmap for data science, collaborating with marketing leadership and the broader Asana data community to uncover new opportunities. You will provide technical leadership and hands-on mentorship, elevating the team's technical bar and influencing overall business strategy through best-in-class modeling and experimental design.
This role is based in our San Francisco office with an office-centric hybrid schedule. The standard in-office days are Monday, Tuesday, and Thursday. Most Asanas have the option to work from home on Wednesdays. Working from home on Fridays depends on the type of work you do and the teams with which you partner. If you're interviewing for this role, your recruiter will share more about the in-office requirements.
What you’ll achieve:
Architect, design, and lead the technical execution for the Marketing Data Science roadmap, serving as the Solution Architect for all core projects including Media Mix Modeling (MMM), User Lifetime Value, Causal Inferences, Multi-touch Attribution, and Spend Optimization engines.
Source text