Data Scientist

• Analyze quality data from multiple enterprise systems to identify patterns, gaps, and opportunities for data-driven improvements.
• Work with program managers and operations leaders to define relevant data assets and specify data access and usage.
• Transform structured and unstructured datasets into actionable insights.
• Conduct data quality checks and resolve data defects across enterprise platforms.
• Develop and validate machine learning models supporting demand forecasting, scenario modeling, and predictive use cases.
• Document analytical findings, model performance, and data definitions to ensure transparency and reproducibility.
• Collaborate with data engineers to build and maintain Python-based data pipelines for ETL, model training, and automated workflows.
• Translate business problems into data science and AI/ML solution frameworks, bridging engineering/operations with digital teams.
• Design and execute scenario planning models; evaluate “what-if” outcomes for strategic decisions.
• Track project execution data, link planning assumptions to actual performance, and support variance analysis.
• Review and analyze existing dashboards, models, and data pipelines to understand design patterns and business requirements.
• Interpret SQL queries and business logic embedded in current reports and analytical systems.
• Provide actionable insights and resolve queries related to model outputs or data defects for various stakeholders.
• Collaborate on continuous improvement initiatives, optimize existing reporting assets, and stay updated with AI/ML advancements.

• Bachelor’s degree in a related field (e.g., Data Science, Computer Science, Statistics).
• 3+ years of experience in data analysis, machine learning, or data science roles.
• Proficiency in Python with experience in pandas, numpy, scikit-learn, scipy, and object-oriented programming.
• Experience building scenario models, performing what-if analysis, and developing predictive analytics.
• Strong SQL skills for querying and interpreting complex data sources.
• Understanding of statistical modeling, hypothesis testing, and experimental design.
• Experience with enterprise data management, data exploration, cleaning, and integration from various sources (SAP, Salesforce, Databricks, ERP/CRM).
• Knowledge of anomaly detection, data lineage, and data governance principles.
• Excellent communication skills, with the ability to translate technical findings into business insights.
• Proactive and collaborative mindset with a strong problem-solving attitude.
• Fluent in English; additional languages are a plus.
• Demonstrated ability to perform the duties of this position through relevant experience, training, or education.

Pay range is not a guarantee of compensation or salary, as final offer amount may vary based on factors including but not limited to experience and geographic location. Talascend also offers a variety of benefits including: health and disability insurance, 401(k), EAP, paid time off, and company-paid holidays. The specific programs and options available to an employee may vary depending on date of hire, plan requirements, schedule type, and client work site mandates.