DATA SCIENTIST II

Job Overview

• Engage with internal stakeholders to ensure analytic solutions align with their needs and deliver tangible results.
• Translate real-world business challenges into analytical frameworks.
• Utilize a diverse skill set, including data mining, machine learning, statistics, visualization, and more.
• Collaborate with teams to gather, refine, and harmonize data, ensuring its readiness for analysis.
• Simplify complex results, avoiding excessive technical jargon, and employ tools and cloud services like Python, R, SQL, and AWS.
• Data Analysis & Model Development: Craft machine learning models and products, ensuring their technical robustness and relevance to business users.
• Solution Deployment: Design, develop, and roll out end-to-end machine learning solutions to address multifaceted business issues.
• Tool & Framework Selection: Choose the right tools (AWS Sagemaker preferred), techniques and frameworks for data science projects, particularly those related to demand forecasting.
• Quality Assurance: Guarantee the precision and reliability of data science outputs through meticulous validation, testing, and performance tracking.
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What your background should look like:

• At least 3-5 years of experience in data science, machine learning, or related fields.
• Proficiency in programming (Python or R) and familiarity with essential data analysis tools and libraries.
• Demonstrated expertise in machine learning and AI techniques.
• Exceptional problem-solving abilities and a knack for innovative solutions.
• Stellar communication skills, with a history of conveying complex ideas effectively.
• A proven record of delivering data science projects efficiently.

Competencies