Job Overview :
We are seeking an experienced Statistician with strong Python programming skills to join our team. This role requires expertise in statistical modeling, data analysis, and a strong foundation in Python to help drive data-driven insights and strategies. The ideal candidate will apply statistical methods to solve complex business challenges, streamline data processes, and deliver actionable insights.
Key Responsibilities
- Statistical Analysis: Conduct in-depth statistical analyses and interpret data trends to support decision-making processes.
- Model Development: Develop and validate statistical models (regression, classification, time-series forecasting, etc.) to solve complex business problems.
- Data Management & Preprocessing: Gather, clean, and preprocess data from multiple sources to prepare it for analysis.
- Programming in Python: Use Python to automate data processing, run simulations, and create scripts to streamline data workflows.
- Reporting & Visualization: Build and maintain dashboards, visualizations, and reports to communicate findings to stakeholders in a clear, concise, and actionable format.
- Collaboration: Work closely with data engineers, analysts, and cross-functional teams to support data-driven projects.
- Continuous Learning: Stay updated with the latest trends and best practices in statistics, data science, and Python programming.
Requirements
- Education: Bachelor's or Master's degree in Statistics, Mathematics, Data Science, or a related field.
- Experience: Minimum of [2-5] years of experience in a similar role with hands-on experience in Python.
- Technical Skills:
- Strong expertise in Python and popular data libraries (e.g., Pandas, NumPy, SciPy, StatsModels).
- Experience with data visualization tools (e.g., Matplotlib, Seaborn, Plotly).
- Proficiency in SQL and working knowledge of databases.
- Knowledge of machine learning concepts and familiarity with libraries like scikit-learn.
- Statistical Knowledge: Strong foundation in statistical techniques such as hypothesis testing, regression, Bayesian analysis, and time-series analysis.
- Analytical Thinking: Ability to analyze complex data, identify patterns, and generate actionable insights.
- Communication: Excellent communication skills with the ability to present complex statistical findings to a non-technical audience.
Preferred Qualifications
- Experience with big data technologies (e.g., Spark) and cloud platforms (e.g., AWS, GCP, Azure).
- Familiarity with machine learning frameworks (e.g., TensorFlow, PyTorch).
- Previous experience in [relevant industry, if applicable].
