Zorba AI - Data Scientist - SQL/Python (5-10 yrs)

Data Scientist

Responsibilities :

Data Exploration and Insights :

- Conduct continuous data exploration and analysis to identify opportunities for enhancing data matching logic, including fuzzy logic, and improving overall data quality within the SCI solution.

- This includes working with large datasets from various sources, including Excel files and databases.

Data Quality Improvement :

- Perform various analyses specifically aimed at improving data quality within the SCI system.

- This will involve identifying data quality issues, proposing solutions, and implementing improvements.

Weekly Playback and Collaboration :

- Participate in weekly playback sessions, using Jupyter Notebook to demonstrate data insights and analysis.

- Incorporate new explorations and analyses based on feedback from the working group and prioritized tasks.

Project Scaling and Support :

- Contribute to the scaling of the SCI project by supporting data acquisition, cleansing, and validation processes for new markets.

- This includes pre-requisites for batch ingestion and post-batch ingestion analysis and validation of SCI records.

Data Analysis and Validation :

- Perform thorough data analysis and validation of SCI records after batch ingestion.

- Proactively identify insights and implement solutions to improve data quality.

Stakeholder Collaboration :

- Coordinate with business stakeholders to facilitate the manual validation of records flagged for manual intervention.

- Communicate findings and recommendations clearly and effectively.

Technical Requirements :

- 5+ years of experience as a Data Scientist.

- Strong proficiency in Python and SQL.

- Extensive experience using Jupyter Notebook for data analysis and visualization.

- Working knowledge of data matching techniques, including fuzzy logic.

- Experience working with large datasets from various sources (Excel, databases, etc.

- Solid understanding of data quality principles and methodologies.

Skills :

- SQL

- Machine Learning (While not explicitly required in the initial description, it's a valuable skill for a Data Scientist and should be included)

- Data Analysis

- Jupyter Notebook

- Data Cleansing

- Fuzzy Logic

- Python

- Data Quality Improvement

- Data Validation

- Data Acquisition

- Communication and Collaboration

- Problem-solving and Analytical skills

Preferred Qualifications (Optional, but can help attract stronger candidates) :

- Experience with specific data quality tools and techniques.

- Familiarity with cloud computing platforms (e.g., AWS, Azure, GCP).

- Experience with data visualization tools (e.g., Tableau, Power BI).

- Knowledge of statistical modeling and machine learning algorithms