Data Modeller / Engineer II

We are seeking a hands-on Python-focused Data Analyst / Data Scientist with strong problem-solving skills and recent experience working with real-world datasets. The ideal candidate will have practical experience using Python, Pandas, SQL, and statistical modeling techniques to build data-driven solutions, automate workflows, and analyze complex business data. This role requires candidates who are actively coding and comfortable solving problems independently in a live technical environment without AI assistance., * Develop and maintain Python-based solutions for data manipulation, transformation, and analysis.

Work extensively with Pandas, NumPy, SQL, and related data analysis libraries to process large datasets.

Build and optimize automated data pipelines, reporting workflows, and analytical tools.

Perform regression analysis, forecasting, trend analysis, and statistical modeling on business datasets.

Analyze structured and semi-structured data to identify insights, anomalies, and operational trends.

Collaborate with cross-functional teams to translate business problems into scalable analytical solutions.

Create dashboards, reports, and visualizations to support operational and strategic decision-making.

Participate in technical discussions and explain problem-solving approaches clearly during live coding exercises.

Strong hands-on experience with Python and Pandas in recent/current roles.

Experience with SQL and data manipulation techniques.

Practical experience with regression modeling, forecasting, statistical analysis, or predictive analytics.

Ability to independently write and debug Python code without AI assistance.

Experience working with large datasets and building analytical workflows.

Strong problem-solving and communication skills.

Bachelor’s degree in Computer Science, Software Engineering, Mathematics, Statistics, Information Systems, or related field preferred.

Preferred Qualifications * Experience with Scikit-learn, NumPy, Matplotlib, or Jupyter Notebook.

Exposure to cloud platforms such as AWS, Azure, or Snowflake.

Experience with ETL automation, dashboarding, or operational analytics.

Background in financial services, operational analytics, retail analytics, or pricing analytics is a plus.

Interview Process

Candidates should be prepared for: * A live Python and Pandas coding assessment

Real-time problem-solving and data manipulation exercises

Explaining coding decisions and analytical thought processes during screen sharing

Independent coding without the use of AI tools, Must have Python, Pandas, and a working development environment installed and ready for live coding exercises.