
Data Scientist
4 weeks ago
Key Responsibilities:
1. Data Exploration and Insights
- Continuously explore and analyze datasets to identify opportunities to improve data matching logic, including fuzzy logic implementations.
- Work with data from diverse sources such as Excel files and relational databases.
2. Data Quality Improvement
- Analyze and identify data quality issues within the SCI system.
- Propose and implement effective solutions to enhance the integrity, consistency, and completeness of data.
3. Weekly Playback and Collaboration
- Participate in weekly playback sessions with stakeholders.
- Use Jupyter Notebook to present insights and incorporate feedback into ongoing analyses and solutions.
4. Project Scaling and Support
- Support the expansion of the SCI project by assisting with data acquisition, cleansing, and validation across new markets.
- Manage batch ingestion processes and validate SCI records post-ingestion.
5. Data Analysis and Validation
- Perform detailed analysis of SCI records to identify inconsistencies or issues after data ingestion.
- Implement improvements to enhance data processing and record matching accuracy.
6. Stakeholder Collaboration
- Work closely with business stakeholders for manual validation of flagged records.
- Clearly communicate data insights, findings, and improvement recommendations.
Technical Requirements:
- 5+ years of experience as a Data Scientist or in a similar analytical role.
- Strong proficiency in Python and SQL.
- Advanced experience using Jupyter Notebook for data exploration and reporting.
- Hands-on experience with fuzzy logic or similar data-matching techniques.
- Proven experience handling large datasets from varied sources.
- Deep understanding of data quality principles, processes, and standards.
Key Skills:
- Python
- SQL
- Jupyter Notebook
- Fuzzy Logic and Data Matching Techniques
- Data Analysis & Cleansing
- Data Validation & Quality Improvement
- Data Acquisition & Preprocessing
- Communication and Stakeholder Collaboration
- Analytical Thinking and Problem Solving
- Machine Learning (Preferred for advanced insights and modeling)
Preferred Qualifications:
- Familiarity with data quality tools and frameworks.
- Experience with cloud platforms such as AWS, Azure, or GCP.
- Exposure to data visualization tools like Tableau or Power BI.
- Understanding of machine learning algorithms and statistical modeling.
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