Senior Analytics Engineer / Data Scientist

Responsibilities Turn product and business data into clear, trustworthy insights leaders can act on. Own the analytics lifecycle—from ingestion and modeling to BI visualization and decision enablement. Deliver self-serve insights using SQL/Python and embedded BI (e.g., ThoughtSpot). Define the design patterns and data infrastructure to scale. Partner closely with the CX team to quantify and communicate Laurel’s ROI, and join customer-facing presentations. Apply machine learning to real-world product and business problems. Comfortable prototyping AI/ML models in notebooks, experimenting with approaches (classification, clustering, regression, NLP, etc.), and translating findings into actionable insights. Requirements Bachelor's degree in Computer Science, Engineering, or a related field, or equivalent practical experience. 3+ years of professional experience as a Data Scientist. Advanced SQL and Python Experience with data orchestration tools (e.g., Airflow, Prefect, Dagster). Proficiency in modern data warehouses (e.g., Snowflake, BigQuery, Redshift). Familiarity with data modeling, warehousing principles, and BI tools (e.g., ThoughtSpot, PowerBI, Tableau). Ability to build ML models and quickly prototype solutions (classification, clustering, regression, NLP) that inform product direction. Cloud platform expertise (AWS, GCP, Azure). Knowledge of dbt, Kubernetes, and Terraform. Exposure to CI/CD pipelines and DevOps practices. Strong problem-solving and communication skills. Ability to work in a fast-paced startup environment and manage multiple priorities. Core Competencies Demonstrates expertise in data analysis and machine learning, with a strong ability to deliver actionable insights through SQL and Python. Proficient in data orchestration, modern data warehousing, and BI tools, while effectively communicating findings to stakeholders. Hard Skills Data Modeling BI Visualization Classification Clustering Regression Natural Language Processing Data Warehousing Principles Prototyping Solutions Analytics Lifecycle Management Decision Enablement Soft Skills Strong Problem-Solving Skills Effective Communication Skills Ability to Manage Multiple Priorities Industry Keywords Data Science CI/CD Pipelines DevOps Practices Fast-Paced Startup Environment Tools & Technologies ThoughtSpot PowerBI Tableau Airflow Prefect Dagster Snowflake BigQuery Redshift AWS #J-18808-Ljbffr