Data Scientist, Data & AI Team, Global eCommerce Platform. Total Annual Compensation: $70,000-$90,000

At Crossian, data science is not just analytics, it's a strategic lever powering our global eCommerce engine. As we grow from a $200M valuation toward $1B, the Data & AI Team plays a central role in designing models and optimization engines that fuel revenue, efficiency, and growth at scale.

As a Data Scientist, you will translate real business challenges into elegant analytical frameworks and machine learning solutions. From rigorous A/B testing to predictive modeling, from optimization algorithms to supply chain forecasting, your insights and models will directly influence how we acquire customers, plan inventory, price products, and build smarter features.

You'll work cross-functionally with product, marketing, operations, and engineering teams to ensure your models are not only technically excellent but also business-relevant and production-ready.

If you're passionate about solving high-impact business problems with data, Crossian is the place to make it happen.

💸 Competitive Compensation: Base salary plus performance bonuses up to 30 months total per year.

🌐 Global Data Playground: Billions of daily events across operations, storefronts, ads, and supply chain.

📈 Career Acceleration: L&D budget, mentorship, and a clear growth path into Staff or Principal roles.

🚢 Real-World Impact: Your models influence $MM decisions and live KPIs across teams.

🧭 Ownership Culture: You define the problem, design the solution, and deliver the outcome end to end.

Business-Framed Statistical Modeling

• Collaborate with stakeholders to translate open-ended business problems into testable hypotheses and ML formulations.
• Develop statistical models (e.g., linear regression, logistic regression, hierarchical models) to understand and predict business dynamics.
• Drive experimentation strategy and analyze A/B tests with proper statistical rigor.

ML Model Development

• Build and validate supervised and unsupervised ML models (e.g., regression, classification, clustering, ensemble methods).
• Apply modeling techniques to problems like customer segmentation, fraud detection, demand prediction, and marketing efficiency.
• Fine-tune models using performance metrics such as AUC, RMSE, lift, and precision/recall.

Optimization & Forecasting

• Apply operations research techniques to build optimization solutions for pricing, inventory, and logistics.
• Contribute to planning tools via time-series forecasting, resource allocation models, or heuristics.
• (Nice to have) Experience applying ML to supply chain use cases (demand forecasting, inventory management, routing).

Cross-Functional Execution

• Work closely with MLEs and Data Engineers to productionize models and integrate into APIs or dashboards.
• Communicate clearly with non-technical partners (Marketing, Product, Finance) to ensure insight adoption.
• Mentor junior team members and contribute to analytics best practices and experimentation frameworks.

Education & Experience

• Bachelor’s or Master’s degree in Computer Science, Data Science, Statistics, Mathematics, or a related quantitative field.
• Senior level: 5+ years of hands-on experience in data science or applied ML roles, preferably in eCommerce, adtech, fintech, or supply chain.
• Intermediate level: 3+ years of relevant experience with at least one deployed solution or experimentation framework.

Technical Proficiency

• Strong Python or R skills (e.g., scikit-learn, NumPy, pandas, statsmodels, TensorFlow, PyTorch).
• Advanced SQL for data extraction, joining, and preprocessing.
• Deep understanding of statistical inference, hypothesis testing, experimental design, and optimization.
• Familiarity with cloud-based platforms (AWS/GCP) and version control (Git).

Soft Skills & Mindset

• Clear, structured communication with both technical and non-technical audiences.
• Curiosity to dig into ambiguous problems and turn them into measurable, data-driven solutions.
• Collaborative spirit; ability to work in Agile squads with product managers, engineers, and analysts.

Preferred (Not Required)

• Prior experience in eCommerce, logistics, or pricing optimization.
• Familiarity with tools like MLflow, SageMaker, Vertex AI, Airflow.
• Publications, open-source contributions, or ML competition experience (e.g., Kaggle, NeurIPS).