Senior Data Scientist

F5 Networks•Seattle, WA

7d•Remote

About The Position

At F5, we strive to bring a better digital world to life. Our teams empower organizations across the globe to create, secure, and run applications that enhance how we experience our evolving digital world. We are passionate about cybersecurity, from protecting consumers from fraud to enabling companies to focus on innovation. Everything we do centers around people. That means we obsess over how to make the lives of our customers, and their customers, better. And it means we prioritize a diverse F5 community where each individual can thrive. Join F5’s Data & Insights team as a Senior Data Scientist and make a measurable impact on teams making decisions with data. You’ll use statistical, causal, machine learning, and LLM modeling to create and scale use, understanding and leverage of data-enabled decision-making. Succes criteria will include enabling effective actions, boosting revenue, and streamlining operations. Your work will influence strategic initiatives, customer interactions, sales strategy, and forecasting across F5 Inc.

Requirements

Master’s or Ph.D. in Data Science, Statistics, Computer Science, or a related field.
5+ years in data science, with a proven track record of delivering impactful insights and models.
Experience with large-scale datasets and distributed computing tools e.g. Snowflake, Azure Data Warehouse, Databricks, and Spark.
Have successfully delivered complex projects sustaining ongoing use as part of a business team
Strong knowledge of SQL and relational databases.
Proficient in programming languages such as Python, including use of notebooks, tabular data (Pandas, Spark) and integration with LLMs (Langchain, MCPs).
Expertise in machine learning frameworks (e.g., TensorFlow, PyTorch) and libraries (e.g., scikit-learn, PyMC, Stan).
Model development and maintenance (MLFlow), and data lifecycle management.
Experience with source control (git) and AI copilots (Claude Code)
Proven ability to optimize model performance for business outcomes.
Proficiency in LLM prompt engineering.
Drive and ability to create reliable, working data deliverables (MVP) and iterate to required quality.
Enthusiastic about collaborating with stakeholders to build business solutions.
Demonstrates ownership and a proactive attitude to “make it happen.”
Strong communicator, discern what users need to understand and use data; able to explain complex technical concepts to non-technical stakeholders when necessary.
Capable of working independently and as part of a team.

Responsibilities

Data Analysis and Modeling: Develop and deploy advanced statistical models and machine learning algorithms to tackle complex business problems, including RCTs and causality modeling.
Perform exploratory data analysis to uncover trends, patterns, and anomalies in large datasets.
Build predictive models to forecast key metrics, guide business strategy, and tune performance to business needs and constraints.
Design and maintain scalable data and model pipelines
Reusable model feature development
Continuously refine models and processes to improve accuracy and efficiency.
Collaboration and Communication: Work closely with data science team, as well as business analysts, data analysts, data engineering, and functional teams from customer success, renewals, sales, and marketing teams to understand data needs and deliver actionable insights.
Present your findings and recommendations to senior leadership in a focused, clear and engaging way.
Work with delivery teams to land insights and forecasts in business applications and processes.
Stay current with the advancements in AI engineering, causal modeling, forecasting, propensity modeling, EDA, machine learning, and NLP.