Data Scientist, Anaplan

• Strong hands-on professional experience in Data Science, successfully building and deploying systems from prototype to production in a fast-paced environment
• Strong predictive modeling foundation: Extensive experience with traditional ML algorithms, Deep Learning frameworks, and complex time-series forecasting
• Experience developing production-grade Python code: High proficiency in Python, Pandas, and modern software practices (testing, clean code, code review, CI/CD)
• Data & Pipeline Expertise: Hands-on experience optimizing data models and access patterns for modern data warehouses (Snowflake, Databricks) utilizing SQL and transformation tools like dbt
• Cloud & Data Infrastructure: Experience working with scalable cloud infrastructure (AWS, GCP, or Azure), and handling columnar data formats like Parquet
• MLOps Exposure: Experience with tools and frameworks for training, tracking, deploying, and monitoring models in production (e.g., MLflow, Optuna, Prefect, or Airflow)

Desirable

• We are seeking a versatile Data Scientist to join the Functional Analytics team
• The core mission of our team is to design and develop new functional analytic capabilities or “engines” that integrate directly into Anaplan Applications to solve complex enterprise business problems
• In this role, you will develop best-in-class ML models and pipelines to drive automated, actionable insights at scale
• Beyond core development, you will act as a key technical partner for our customers
• You will play a highly visible role in driving customer onboardings, getting hands-on with client data to customize and fine-tune our ML engines so they seamlessly adapt to complex business realities and specific customer needs
• Customer Onboarding & Engine Customization: Lead the technical deployment of our engines for new clients. Partner closely with customers, Customer Success, Product, and Engineering to adapt and customize ML models, ensuring they accurately reflect client-specific business logic, operational guardrails, and unique data nuances
• Analytic Engine Development: Design and develop scalable functional analytic capabilities that seamlessly integrate into Anaplan Applications, translating raw customer data into automated, high-value business insights
• Advanced Modeling & Timeseries Forecasting: Design, train, and implement robust Machine Learning (LightGBM, XGBoost) and Deep Learning (PyTorch) models specifically focused on complex demand sensing and resolving cold-start forecasting problems
• Feature Engineering Pipelines: Build and optimize scalable data pipelines leveraging a hybrid SQL/Python architecture (dbt, Snowflake) to extract rich, localized temporal signals from high-volume transactional retail data
• End-to-End Deployment (MLOps): Partner with our engineers to transition your models from prototype into scalable, monitored, and reliable production pipelines using tools like MLflow and Optuna