Senior Data Analyst -SQL/Machine Learning /AI/PowerBI

The Senior Data Analyst role in New York City offers a hybrid work arrangement and centers on SQL, PySpark, Python with Pandas, and machine learning initiatives. This position is open to local candidates, with a two-hour onsite interview in NYC. Compensation is USD 65 per hour.

Responsibilities

• Perform SQL-based data extraction and analysis
• Process data with PySpark to support large-scale workflows
• Carry out analyses using Python and Pandas
• Derive actionable insights from sizable datasets
• Develop and evaluate machine learning models
• Deliver analytics and reporting to inform decisions

Requirements

• Strong SQL query writing and optimization
• Proficiency in PySpark
• Python programming skills
• Experience with Pandas for data manipulation
• Background in machine learning applications
• Ability to write, execute, and troubleshoot SQL queries
• Data extraction and integration capabilities
• Experience creating joins, aggregations, and filters
• Basic to intermediate data transformations
• Building and maintaining data pipelines
• Large-scale data processing and optimization
• Data cleansing and preparation
• Data transformation in distributed environments
• Exploratory data analysis and data manipulation with Pandas
• Exposure to classification, regression, and clustering models
• Model evaluation and performance measurement

Technologies

• SQL
• PySpark
• Python
• Pandas
• PowerBI
• Databricks
• Google Cloud Platform (GCP)

Benefits

• 401(k)
• Dental insurance
• Health insurance
• Vision insurance

Interview Details

• In-person interview only, no video interviews
• Candidate must be local to attend a two-hour onsite session in NYC
• Live SQL and PySpark coding exercises will be conducted
• Candidates should have thoroughly validated hands-on coding skills prior to submission

Team Structure

• 10 Data Engineers
• 6 Data Scientists

Certifications

• Highly Preferred: Databricks Data Engineer Certification
• Acceptable Post-Hire: Databricks Certification
• Acceptable Post-Hire: Google Cloud (GCP) Certification

Priority Technical Skill: PySpark

• Building and maintaining data pipelines
• Large-scale data processing
• Data transformation and optimization
• Distributed data environments

Python and Pandas

• Data cleansing and preparation
• Data transformation
• Exploratory data analysis
• Data manipulation with Pandas

Machine Learning Focus

• Classification models
• Regression models
• Clustering techniques
• Model evaluation and performance measurement