Data Scientist

Summary

Join G2 as a Data Scientist and lead the development and refinement of machine learning models to solve complex business problems. You will conduct experiments, build data pipelines, analyze large datasets, and collaborate with cross-functional teams. This role also involves mentoring junior team members and ensuring model deployment and production workflows. G2 offers generous benefits, including flexible work, ample parental leave, and unlimited PTO. The company is committed to creating an inclusive and diverse work environment.

Requirements

• 4+ years experience as a data scientist involved in data extraction, analysis and modeling
• 4+ years of experience in Python and SQL
• Strong understanding of statistics
• Proficiency in machine learning algorithms and all stages of machine learning
• Familiarity with neural networks and deep learning
• Familiarity with AWS services and Snowflake (or similar SQL DB)
• Familiar with containerization (e.g., Docker) and API frameworks (e.g., Flask)
• Demonstrated ability to troubleshoot issues in production environments, including debugging data pipelines or model related errors

Responsibilities

• Lead the development and refinement of machine learning models, including feature engineering, algorithm selection, and model optimization
• Conduct experiments with advanced machine learning techniques to improve model performance and deliver impactful solutions
• Build, maintain, and optimize data pipelines to support end-to-end machine learning workflows
• Analyze large datasets to extract insights and provide actionable recommendations for business teams in conjunction with model development
• Collaborate with ML engineers to operationalize models, ensuring scalability and reliability
• Work closely with cross-functional teams, including product managers and engineers, to translate business requirements into machine learning solutions
• Document and present methodologies, findings, and results to both technical and non-technical audiences
• Act as an on-call resource to troubleshoot and resolve issues with deployed machine learning models
• Collaborate with ML engineers to monitor model performance and ensure operational stability
• Mentor junior team members, providing technical support, guidance on model development, and best practices implementation

Preferred Qualifications

• Successful end-to-end delivery of data science products
• Exposure to MLOps tools like MLFlow, KubeFlow, DVC,AWS Sagemaker, Seldon etc
• Experience deploying models in a AWS cloud environment - with specific experience with AWS tools such as Sagemaker and Step Functions
• Expertise with Natural Language Processing and Understanding
• Experience with libraries and frameworks for training ML and DL models (PySpark, Tensorflow)
• Experience with LLMs/Generative AI

Benefits

• Flexible work
• Ample parental leave
• Unlimited PTO