Senior Data Scientist

NinjaOne

1d • Hybrid

About The Position

As a Senior Data Scientist at NinjaOne, you will play a critical role in accelerating business growth by applying advanced analytics and machine learning. You’ll work at the intersection of data, product, and go-to-market teams to build predictive models, experimentation frameworks, and actionable insights that directly influence revenue, customer acquisition, retention, and operational efficiency.
This role offers the opportunity to own high-impact initiatives end-to-end. Drive problem framing, model development, production deployment and business adoption while working on large-scale, real-world data in a fast-growing, product-led organization.
If you’re motivated by solving complex problems, shipping production ML, and seeing your work drive measurable business outcomes, this is a chance to make a massive impact at scale.
Location - We are flexible on remote working from home, if you are located in the USA and reside in one of the following states - CA, CO, CT, FL, GA, IL, KS, MA, MD, ME, NJ, NC, NY, OR, TN, TX, VA, and WA. We have physical offices in Austin, TX and Tampa, FL, if you prefer a hybrid option.
We hire the best software engineers, but experience in our stack can’t hurt: NinjaOne is built on Java, Kotlin, C++, Golang and Postgres; supporting millions of user endpoints and running as a scalable cloud service in AWS. Knowing large-scale datastore bottlenecks, asynchronous application design and client-server architecture will help you.

Requirements

• Bachelor’s or Master’s degree in Computer Science, Statistics, Engineering, or a related quantitative field.
• 10+ years of experience applying data science, machine learning, and advanced analytics to business and product problems.
• Expert proficiency in Python and SQL for data analysis, modeling, and production ML workflows.
• Strong foundation in statistical modeling, machine learning, experimentation, and causal inference.
• Hands-on experience deploying and operating production ML systems in cloud environments (AWS, Azure), including MLOps best practices.

Nice To Haves

• Previous experience working with large-scale data pipelines and machine learning models.
• Mastery of Generative AI and Deep Learning frameworks.

Responsibilities

• Design, build, and deploy advanced analytical models to drive insights and decision-making across sales, marketing, customer support, and product teams.
• Develop predictive models for forecasting, churn, lead scoring, pipeline health, customer lifetime value, and usage-based segmentation.
• Partner closely with stakeholders to translate business questions into data science problems, metrics, and experimentation strategies.
• Build scalable data pipelines and feature engineering workflows to support model training, inference, and real-time analytics.
• Create experimentation frameworks and run A/B tests to optimize marketing campaigns, product features, and support workflows.
• Implement causal inference and attribution models to measure campaign effectiveness and product adoption drivers.
• Lead data quality, validation, and governance efforts to ensure high trust in analytical outputs.
• Mentor junior data scientists and analysts, establishing best practices for modeling, experimentation, and documentation.
• Collaborate with engineering and operations teams to productionize models and embed intelligence into core business systems.
• Other duties as needed

Benefits

• We are a collaborative, kind, and curious community.
• We honor your flexibility needs with full-time work that is hybrid remote.
• We have you covered with our comprehensive benefits package, which includes medical, dental, and vision insurance.
• We help you prepare for your financial future with our 401(k) plan.
• We prioritize your work-life balance with our unlimited PTO.
• We reward your work with opportunity for growth and advancement.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level