Databricks Data Scientist

Databricks Data Scientist

Washington D.C. (hybrid onsite)

165 - 185K + benefits

Overview

As a Databricks Data Scientist, you will leverage the Databricks platform to analyze large-scale, complex datasets for a highly visible consumer-facing product. This role focuses on transforming data into actionable insights that drive product strategy, customer experience improvements, and business outcomes. You will work cross-functionally to uncover trends, validate hypotheses, and deliver scalable analytical solutions.

Responsibilities

• Analyze complex, high-volume datasets using the Databricks platform to identify trends, patterns, and actionable insights
• Perform data collection, cleansing, and exploratory data analysis (EDA) to ensure data quality and usability
• Apply statistical methods and hypothesis testing to validate assumptions and identify significant trends
• Develop and implement predictive models and machine learning solutions to support business objectives
• Analyze customer behavior data, with a focus on retention, churn, and engagement metrics
• Create data visualizations and dashboards to effectively communicate insights to stakeholders
• Collaborate with product, engineering, and business teams to translate analytical findings into strategic recommendations
• Utilize Python and SQL to manipulate data, build models, and implement scalable analytical workflows
• Identify anomalies, correlations, and opportunities within large datasets to inform decision-making
• Contribute to the design and optimization of data pipelines and analytics processes within the Databricks ecosystem

Requirements

• Ability to pass a Public Trust Background Investigation
• Bachelor’s degree or four years of experience in lieu of degree
• 8+ years of relevant experience delivering data engineering solutions that drive measurable customer or user value
• Advanced experience in predictive modeling and analytics, including regression, classification, clustering, and time-series analysis
• Expert-level proficiency in data science methodologies, including statistical analysis, hypothesis testing, and machine learning model development
• Strong expertise in Databricks platform, including building, deploying, and optimizing data pipelines and analytical workflows
• Experience in data visualization tools and techniques to effectively communicate insights to technical and non-technical audiences
• Experience with big data engineering concepts, including working with distributed data systems and large-scale data processing
• Advanced proficiency in Python and SQL for data manipulation, feature engineering, and model implementation
• Proven ability to analyze customer behavior data, with a focus on retention, churn analysis, and user engagement
• Experience working with large, complex data sets, including data wrangling, cleaning, and exploratory data analysis (EDA)
• Strong problem-solving skills with the ability to translate business questions into analytical frameworks and actionable insights
• Excellent written and verbal communication skills with the ability to explain technical decisions in terms of customer impact