Data Scientist

Job Description

Medium-Senior Level Data Engineer / Data Analyst who can work independently on complex business requirements converting them into data transformation scripts that produce well structured, clean and explainable outcomes.

This role involves more than just technical skill, it requires the ability to communicate effectively with colleagues, challenge unclear or incomplete requirements, and proactively improve how data is collected, analyzed, and utilized.

Experience and Education Required 

At least 6 years of experience as Data Analyst / Data Engineer/Data Scientist

 Job Profile: 

• Data Collection & Integration: Identify, gather, and consolidate data from diverse sources, including internal databases and spreadsheets ensuring data integrity and relevance.

• Data Cleaning & Transformation: Apply thorough data quality checks, cleaning processes, and transformations using Python (Pandas) and SQL to prepare datasets.

• Automation & Scalability: Develop and maintain scripts that automate repetitive data preparation tasks.

• Exploratory Analysis & Insight Generation: Utilize statistical methods, visualization tools, and critical thinking to uncover trends, patterns, and anomalies.

• Requirement Clarification & Communication: Interact directly with colleagues to clarify objectives, challenge assumptions.

• Documentation & Best Practices: Maintain clear, concise documentation of data workflows, coding standards, and analytical methodologies to support knowledge transfer and scalability.

• Collaboration & Stakeholder Engagement: Work closely with colleagues who provide data, raising questions about data validity, sharing insights, and co-creating solutions that address evolving needs.

• Autonomy & Proactivity: Operate with minimal supervision, demonstrating initiative in problem-solving, prioritizing tasks, and continuously improving the quality and impact of your work

Technical Skills:

• Minimum of 3 years of experience as a Data Analyst, Data Engineer, or related role, ideally with a bachelor's degree or higher in a relevant field.

• Strong proficiency in Python (Pandas, Scikit-learn, Matplotlib) and SQL, with experience working across various data formats and sources.

• Familiarity with Jupyter notebooks for rapid prototyping and comfort moving from exploratory analysis to production-level code.

• Proven ability to automate data workflows, implement code-based best practices, and maintain documentation to ensure reproducibility and scalability.

Behavioral Skills:

• Excellent communication skills for engaging with colleagues, clarifying requirements, and conveying analytical results in a meaningful, non-technical manner.

• Demonstrated critical thinking skills, including the willingness to question assumptions, evaluate data quality, and recommend alternative approaches when necessary.

• A self-directed, resourceful problem-solver who collaborates well with others while confidently managing tasks and priorities independently.