Top Entry Level Data Science Jobs in Buffalo, NY

The Revenue Operations Analyst supports the full customer lifecycle in collaboration with Marketing, Customer Success, and Sales Leadership. This role focuses on optimizing revenue tools, maintaining data integrity, improving processes, managing leads, and supporting deal structures to drive business growth and enhance team productivity.

The Data Integration Specialist will work with clients to onboard their data to Enterra solutions, validate data processes, and communicate requirements. Responsibilities include mapping data, addressing gaps, conducting initial data wrangling, and testing solutions. The role emphasizes collaboration with data engineers and understanding client data needs.

The Research Associate role at Carbon Direct involves conducting research and analysis, creating deliverables, collaborating with teams, and managing projects focused on nature-based climate solutions. A strong candidate will engage in data analysis, foster communication, and ensure quality in outcomes while supporting carbon management advisory engagements.

The Data Scientist will collect data, apply analytical and statistical methods to extract insights, and create visualizations for stakeholders. The role requires working with various data tools and managing data warehouses to ensure effective data integration and analysis.

The Data Scientist will support data science needs by performing data mining, statistical analysis, and building predictive models for the Cybercrime and Analytics Group. Responsibilities include optimizing classifiers, data processing, anomaly detection, and assisting with IT support as needed.

Join Hims & Hers Analytics and Data Science team to engage in data-driven decision making, improve user experience, and contribute to product development. Collaborate with business leaders, marketers, and product teams to drive analytical insights, and leverage machine learning for innovative solutions across the organization.

The Data Scientist will develop and maintain ETL processes, generate insightful reports from financial data, analyze performance indicators, and collaborate with cross-functional teams to improve financial operations and data quality.