Apolis
Data Scientist
Work Location: Bellevue, US (onsite)
Role and responsibilities: 5+ years of experience in data analysis, machine learning, or data science roles. • Experience with end-to-end data projects and collaborating with cross-functional teams. • Proficiency in Python, R, or similar programming languages. • Strong knowledge of statistics, machine learning, and data modeling. • Experience with SQL and database management. • Familiarity with data visualization tools (Tableau, Power BI, Matplotlib, Seaborn). • Experience in cloud platforms (AWS, Azure, GCP) and big data tools is a plus. • Strong analytical, problem-solving, and communication skills. • Collect, clean, and preprocess data from multiple sources. • Analyze data to identify trends, patterns, and correlations. • Build and validate predictive and classification models using machine learning techniques. • Create dashboards and visualizations to communicate findings effectively. • Present insights to stakeholders to influence business decisions. • Work with business teams, data engineers, and product managers to understand requirements. • Translate business problems into technical solutions and analytical approaches. • Collaborate with engineering teams to deploy models into production. • Monitor model performance and retrain as necessary. • Ensure data privacy, security, and compliance with regulatory requirements. • Follow best practices for documentation and reproducibility of analyses.
Role and responsibilities: 5+ years of experience in data analysis, machine learning, or data science roles. • Experience with end-to-end data projects and collaborating with cross-functional teams. • Proficiency in Python, R, or similar programming languages. • Strong knowledge of statistics, machine learning, and data modeling. • Experience with SQL and database management. • Familiarity with data visualization tools (Tableau, Power BI, Matplotlib, Seaborn). • Experience in cloud platforms (AWS, Azure, GCP) and big data tools is a plus. • Strong analytical, problem-solving, and communication skills. • Collect, clean, and preprocess data from multiple sources. • Analyze data to identify trends, patterns, and correlations. • Build and validate predictive and classification models using machine learning techniques. • Create dashboards and visualizations to communicate findings effectively. • Present insights to stakeholders to influence business decisions. • Work with business teams, data engineers, and product managers to understand requirements. • Translate business problems into technical solutions and analytical approaches. • Collaborate with engineering teams to deploy models into production. • Monitor model performance and retrain as necessary. • Ensure data privacy, security, and compliance with regulatory requirements. • Follow best practices for documentation and reproducibility of analyses.