KnowBe4, the provider of the world’s largest security awareness training and simulated phishing platform, is used by tens of thousands of organizations around the globe. KnowBe4 enables organizations to manage the ongoing problem of social engineering by helping them train employees to make smarter security decisions, every day.
Fortune has ranked us as a best place to work for women, for millennials, and in technology for four years in a row! We have been certified as a "Great Place To Work" in 8 countries, plus we’ve earned numerous other prestigious awards, including Glassdoor’s Best Places To Work.
Our team values radical transparency, extreme ownership, and continuous professional development in a welcoming workplace that encourages all employees to be themselves. Whether working remotely or in-person, we strive to make every day fun and engaging; from team lunches to trivia competitions to local outings, there is always something exciting happening at KnowBe4.
Remote positions open to the US only.
The Senior Data Scientist will work closely with the VP of Data & Analytics to implement advanced analytical models and other data-driven solutions.
- Work with stakeholders in marketing to identify opportunities to use available data to develop business solutions
- Enhance existing data collection procedures to ensure that all data relevant for analyses is captured
- Cleanse, consolidate, and verify the integrity of data used in analyses
- Build and validate predictive models to increase customer retention, revenue generation, and other business outcomes
- Assist in the design and data modeling of the data warehouse
- Visualize data, especially in reports and dashboards, to communicate analysis results to stakeholders
- Extend data collection to unstructured data within the company and external sources
- Develop machine learning driven products for internal use
- Perform ad-hoc analysis, presentations and other projects as required
- Master’s degree in Statistics, Computer Science, Mathematics or other quantitative discipline.
- Master’s degree – 3+ yrs in similar role: PhD – 2+ yrs
- Experience with statistical computer languages (Python, R etc.) to manipulate and analyze large datasets.
- Experience with databases, query languages, and associated data architecture.
- Experience with data visualization tools like Looker, Tableau, PowerBI, or Plotly
- Experience in professional application of machine learning algorithms such as Random Forest, SVM, k-NN, Naïve Bayes, Gradient Boosting. Deep learning frameworks (Keras/Tensorflow, PyTorch, etc.) is a plus
- Experience applying data science to marketing including attribution modeling, media mix modeling, and ROI analysis.
- Ability to communicate effectively with both technical and non-technical colleagues
- Experience with marketing automation platforms and/or CRM software is a plus (Hubspot, Salesforce, Marketo, etc.)
- Experience with AWS is a plus
- Professional experience with Python, including Python data libraries (numpy, pandas, matplotlib, scikit-learn, etc)
- Build machine learning models (training, validation, and testing) with appropriate solutions for data reduction, sampling, feature selection, and feature engineering
- Design and evaluate experiments (including hypothesis testing) by creating key data sets
- Help grow the Data Science function by defining and socializing best practices, particularly within a DataOps and MLOps data ecosystem
- Document every action in either issue/MR templates or READMEs so your learnings turn into repeatable actions and then into automation
- Familiarity with the CRISP-DM analytics development model
- Experience working with a variety of statistical and machine learning methods (time series analysis, regression, classification, clustering, survival analysis, etc)
- Deep understanding of SQL in data warehouses (Snowflake and dbt) and in business intelligence tools (Looker)
- Extensive knowledge, application, and experience in creating and implementing recommendation systems, machine learning, NLP, statistics, and deep learning
- Ability to quantify improvements from business efficiency or customer experience based on research outcomes
- Expert understanding of statistics and the math behind data science algorithms
- Identify and spearhead new data science initiatives, projects, and collaborations that improve results
- Willingness to experiment and confront the hardest or most complex problems
The base pay for this position ranges from $135,000 - $150,000, which will vary depending on how well an applicant’s skills and experience align with the job description listed above.