Basic Qualifications
- Educational Background: Possess a graduate degree in Data Science, Computer Science, Business Analytics, Statistics, Economics, Applied Mathematics, or a related quantitative field from a prestigious institution.
- Professional Experience: Minimum of six months of industry or internship experience in a data science or machine learning engineering role, demonstrating strong proficiency in Python, SQL, and version control using Git.
- Technical Skills: Tried ability to independently fit, evaluate, and interpret statistical and machine learning models within a business context.
- Communication Skills: Excellent verbal and written communication skills, crucial for documenting findings and fostering effective daily collaborations.
- Project Management: Ability to prioritize and meet deadlines in a dynamic environment.
- Attention to Detail: Prodigious attention to detail, ensuring precision in data analysis, model development, and reporting.
Additional Qualifications
- Data orchestration tools such as Airflow.
- Data warehousing solutions like Snowflake.
- Cloud services, including Amazon Web Services (AWS) and Google Cloud Platform (Google Cloud Platform).
- Development environments like Visual Studio Code.
- Programming skills in HTML, C, or Java.
- Web application development.
- Data pipeline ingestion processes.
- A high degree of curiosity and motivation to learn new technologies and methodologies.
- Stellar problem-solving skills and logical thinking.
- A strong interest in AI and enthusiasm for AI product development.
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