Data Scientist

Key Responsibilities

• Support the development and maintenance of analytical datasets and data pipelines in Snowflake
• Analyze structured and semi-structured data to identify trends, patterns, and actionable business insights
• Contribute to statistical, machine learning, and forecasting models under the guidance of senior team members
• Develop reports, dashboards, and visualizations that communicate findings clearly to business stakeholders
• Perform data preparation, feature engineering, validation, and documentation to support analytics initiatives
• Contribute to exploratory work related to natural language processing, document analytics, and LLM-enabled use cases, where appropriate
• Write SQL and Python code to support data analysis, modeling, and reporting needs
• Partner with cross-functional teams to translate business needs into analytical approaches and scalable solutions
• Support data quality, governance, and compliance practices aligned with enterprise standards
• Prepare clear documentation, summaries, and presentations for technical and non-technical audiences

Required Qualifications

• Bachelor’s degree in Data Science, Statistics, Mathematics, Computer Science, Engineering, or a related quantitative field
• 3-5 years of relevant experience in data science, analytics, business intelligence, or a related field, including internship or academic project experience
• Experience using Python and SQL for data analysis and problem-solving
• Foundational knowledge of statistical analysis, data exploration, and machine learning techniques
• Experience with data visualization tools such as Tableau or Power BI
• Strong analytical, problem-solving, and critical-thinking skills
• Strong written and verbal communication skills
• Demonstrated ability to work effectively in a collaborative team environment

Preferred Qualifications

• Exposure to Snowflake or other cloud-based data platforms, including Microsoft Azure and Google Cloud Platform
• Familiarity with machine learning libraries such as pandas, scikit-learn, or similar tools
• Experience working with semi-structured or unstructured data, including JSON or text-based data
• Exposure to natural language processing or LLM-related use cases through coursework, internships, or project work