Data Scientist

We are seeking a driven and creative Data Scientist with a minimum of 3 years of experience in a data science or machine learning role who will be instrumental in building predictive models testing hypotheses and providing statistically sound insights that enhance our lead generation capabilities. The Data Scientist will be part of our analytics team working closely with IT marketing media buying and CRO teams to transform raw data into actionable insights whether that means building real-time scoring models investigating campaign performance or helping the business distinguish signal from noise when making decisions.

The ideal candidate is 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. Theyre as comfortable building production ML pipelines as they are answering a media buyers question about whether a source is actually underperforming or just experiencing variance. Experience in digital marketing lead generation or ad-tech is highly desirable.

Primary Responsibilities

• Leverage agentic AI-assisted development tools throughout the workflow from exploratory analysis and feature engineering to model development and pipeline building to accelerate iteration speed while maintaining rigor and code quality
• Design develop and deploy machine learning models to segment and score landing page visitors based on intent and lead quality using behavioral signals such as scroll depth click patterns session duration and form engagement.
• 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 doesnt support them.
• Identify and quantify relationships between behavioral signals traffic sources campaign attributes and lead quality outcomes; distinguish meaningful correlations from spurious ones.
• Serve as an analytical partner to media buyers and marketing teams: investigate campaign and source performance validate hypotheses about lead quality and provide statistically rigorous answers to business questions.

Requirements:

• 3 years of experience in data science machine learning or a related quantitative role.
• Comfortable working in agentic AI-assisted development environments (e.g. Cursor ClaudeCode Antigravity) to accelerate model development data exploration and pipeline building including the judgment to know when AI-generated outputs need manual verification or refinement.
• 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: can distinguish signal from noise assess significance and communicate uncertainty clearly.
• Proficiency in SQL and experience working with large-scale datasets.
• Understanding of classification regression and clustering techniques; experience with user segmentation or propensity modeling preferred.
• Exposure to digital marketing concepts and KPIs (CPL CVR ROAS etc.) is highly desirable.
• Ability to translate vague business questions into testable hypotheses and structured analyses.
• Excellent problem-solving skills with the ability to work through ambiguity and define structure where none exists.
• Strong communication skills with the ability to explain technical concepts to non-technical stakeholders.
• Team-oriented mindset with a collaborative and proactive approach.
• Upper-Intermediate or higher level of English.

Nice to Have

• Experience building or using custom skills prompt workflows or tool-use patterns within agentic coding environments.
• Experience in lead generation ad-tech or performance marketing environments.
• Familiarity with ad network optimization postback mechanisms or conversion APIs.
• Experience with cloud platforms and MLOps tools.
• Background in time-series forecasting or demand modeling.