Data Scientist
WFA Digital Insight
Demand for data scientists with expertise in machine learning and statistical analysis has skyrocketed, with a 25% increase in job openings over the past year. CapsLock's Data Scientist role stands out in the current remote job market, offering a unique opportunity to drive business growth through data-driven decision making. With the rise of digital marketing, companies are looking for professionals who can turn complex data into actionable insights. As a candidate, you should be prepared to showcase your skills in Python, machine learning libraries, and experience working with agentic AI-assisted development tools. Before applying, consider how your skills align with CapsLock's goals and be ready to demonstrate your ability to communicate complex data insights to non-technical stakeholders.
Job Description
About the Role
The Data Scientist role at CapsLock is a critical part of the analytics team, responsible for developing and deploying machine learning models to drive business growth. As a Data Scientist, you will work closely with IT, marketing, media buying, and CRO teams to transform raw data into actionable insights. Your day-to-day tasks will involve building predictive models, testing hypotheses, and providing statistically sound insights to enhance lead generation capabilities. You will be part of a dynamic team that values creativity, statistical intuition, and strong communication skills.The ideal candidate will be someone who thrives on solving ambiguous problems, brings strong statistical intuition alongside machine learning skills, and can serve as a trusted analytical partner to stakeholders across the business. You will be working in an agentic AI-assisted development environment, leveraging tools such as Cursor, ClaudeCode, or Antigravity to accelerate model development, data exploration, and pipeline building.
What You Will Do
- Design, develop, and deploy machine learning models to segment and score landing page visitors based on intent and lead quality
- Engineer predictive features from raw user behavior data to improve model accuracy and business relevance
- Build and maintain real-time scoring pipelines that enable dynamic postback signals to ad networks, improving campaign optimization speed and efficiency
- Collaborate with marketing and analytics teams to define quality/intent tiers and translate business logic into quantifiable model outputs
- Conduct exploratory data analysis and experimentation to uncover patterns in user behavior that correlate with downstream lead quality and conversion outcomes
- Continuously monitor, evaluate, and iterate on model performance, ensuring alignment with evolving business goals and traffic patterns
- Contribute to forecasting and budget projection initiatives as needed, supporting strategic planning with data-driven modeling
- Clearly communicate, document, and present findings, methodologies, and model specifications for cross-functional, non-technical stakeholders
- Support data-driven decision-making by quantifying uncertainty, assessing statistical significance, and challenging assumptions when the data doesn't support them
- Identify and quantify relationships between behavioral signals, traffic sources, campaign attributes, and lead quality outcomes
- Serve as an analytical partner to media buyers and marketing teams, investigating campaign and source performance, validating hypotheses about lead quality, and providing statistically rigorous answers to business questions
What We Are Looking For
- 3+ years of experience in data science, machine learning, or a related quantitative role
- Strong proficiency in Python, including ML libraries such as scikit-learn, XGBoost, LightGBM, or similar
- Solid experience with feature engineering, particularly from behavioral, clickstream, or event-based data
- Familiarity with deploying models in production environments; experience with real-time or near-real-time inference is a strong plus
- Strong foundation in statistical inference, hypothesis testing, and root-cause analysis
- Comfortable working in agentic AI-assisted development environments
- Experience in digital marketing, lead generation, or ad-tech is highly desirable
- Excellent communication and collaboration skills
Nice to Have
- Experience with Excel and data visualization tools
- Knowledge of cloud-based data platforms such as AWS or Google Cloud
- Certification in data science or a related field
Benefits and Perks
- Opportunity to work with a dynamic and growing company
- Collaborative and supportive team environment
- Professional development opportunities, including training and conference sponsorships
- Flexible working hours and remote work options
- Access to cutting-edge technologies and tools
- Competitive salary and benefits package
How to Stand Out
- Make sure to highlight your experience with machine learning libraries such as scikit-learn and XGBoost in your resume and cover letter
- Be prepared to provide examples of how you've applied statistical inference and hypothesis testing in previous roles
- Develop a strong understanding of agentic AI-assisted development tools and be ready to discuss their applications in data science
- Showcase your ability to communicate complex data insights to non-technical stakeholders through clear and concise writing samples
- Prepare to discuss your experience with real-time or near-real-time inference and how you've handled related challenges in previous roles
- Research CapsLock's business goals and be ready to discuss how your skills and experience align with their objectives
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