We seek a detail-oriented and analytically minded Data Scientist/Data Analyst to independently translate complex business requirements into structured, clean, and explainable data transformation scripts. The ideal candidate will not only demonstrate technical expertise but also excel in clear communication, problem-solving, and proactive collaboration, contributing significantly to improving data collection, analysis, and utilization processes.
Key Responsibilities
Data Manipulation & Transformation
- Process in-memory data efficiently using Python and Pandas.
- Extract, clean, and structure data from multiple sources, including SQL databases and external APIs.
Exploratory Analysis & Insight Generation
- Use statistical methods and visualization tools (e.g., Matplotlib, Excel) to identify trends, patterns, and anomalies.
- Assess data quality and recommend improvements for enhanced accuracy and reliability.
Prototyping & Production Development
- Develop exploratory solutions and prototypes using Jupyter notebooks.
- Transition prototypes into production-ready Python code while adhering to best practices and coding standards.
Documentation & Best Practices
- Maintain clear and comprehensive documentation of data workflows, coding standards, and analytical methodologies for scalability and knowledge transfer.
Requirement Clarification & Communication
- Collaborate with colleagues to refine business requirements, ensuring accurate interpretation and execution.
- Effectively communicate insights and analytical findings to non-technical stakeholders.
Collaboration & Stakeholder Engagement
- Work closely with data providers and business stakeholders to validate data accuracy and develop meaningful solutions.
Autonomy & Continuous Improvement
- Take initiative in problem-solving, prioritization, and continuously enhancing work quality with minimal supervision.
Required Skills & Experience
- Minimum of 5 years of experience as a Data Analyst, Data Scientist, or a related role.
- Bachelor’s degree (or higher) in a relevant field preferred.
- Proficiency in Python (Pandas, Matplotlib), SQL, MS Excel, and Jupyter notebooks.
- Experience in automating data workflows and applying best coding practices.
- Strong analytical thinking, attention to detail, and commitment to data quality.
- Excellent communication skills for collaboration and presenting insights to stakeholders.
- Ability to work independently and adapt to evolving business needs.
Preferred (Optional) Skills
- Familiarity with Machine Learning frameworks such as Scikit-learn.
- Experience with Large Language Models (LLMs) and prompt engineering.
Technologies & Infrastructure
- Technologies: Python (Pandas, Matplotlib, Scikit-learn), SQL, MS Excel.
- Infrastructure: GitHub.
