
Senior Data Scientist
Posted 4 hours ago

Posted 4 hours ago
This is a fully remote position, open to applicants in Serbia, +2 more states.
• Transform business challenges into analytical solutions and pinpoint opportunities for predictive modeling, optimization, and data-informed decision-making.
• Create, develop, and implement machine learning models utilizing classification, regression, clustering, and forecasting techniques.
• Construct prompts for securely hosted AI models and harness the analytical capabilities of LLM.
• Utilize statistical methods and experimental techniques, such as hypothesis testing and A/B testing.
• Perform exploratory data analysis on extensive datasets to uncover patterns, trends, and key factors.
• Engineer features and prepare datasets to enhance model performance and reliability.
• Assess and optimize models using metrics, cross-validation, and tuning strategies.
• Ensure model explainability and interpretability, effectively communicating results to both technical and non-technical audiences.
• Design and implement MLOps practices, including model versioning, monitoring, and retraining.
• Collaborate with data engineers to access, prepare, and scale datasets from cloud platforms.
• Present insights and recommendations through data visualization and business intelligence.
• Contribute to the design of analytics and AI solutions with a focus on delivering business value.
• Engage with stakeholders and clients throughout the discovery, experimentation, and solution design phases.
• 5 years of experience as a senior data scientist or engineer delivering data science, machine learning, or advanced analytics solutions.
• 2 years of experience working with GCP data technologies.
• Practical experience with machine learning techniques, including regression, classification, clustering, and time series analysis.
• Proficient in statistical analysis and modeling with production deployments.
• Comprehensive understanding of the end-to-end machine learning lifecycle: data preparation, modeling, evaluation, deployment, and monitoring.
• Expertise in model performance tuning and validation techniques.
• Strong SQL skills and experience handling large datasets.
• Proven ability to elicit, analyze, and document requirements and processes effectively.
• Demonstrated proficiency in applied data techniques, including identification, pipelining/ETL, curation, chunking, modeling, data quality, cataloging, lineage, and package deployment.
• Hands-on experience with Agile methodologies and active participation in Agile ceremonies.
• Ability to work independently and take ownership of tasks within a multidisciplinary team.
• Excellent problem-solving skills and a keen eye for detail.
• Capability to convey complex analytical concepts clearly to business stakeholders.
• Comfortable operating in a fast-paced, dynamic environment.
• Bachelor’s or Master’s degree in Data Science, Computer Science, Mathematics, Statistics, or a related field.
• Commitment to learning and fostering long-term career growth.
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