Job Summary:
We are seeking a highly analytical and results-driven Data Scientist (26 years experience) to analyze complex datasets, uncover actionable insights, and build predictive models that support strategic business decisions. The ideal candidate will have hands-on experience in machine learning, statistical analysis, and data visualization, along with the ability to translate data findings into meaningful business recommendations.
Key Responsibilities:
- Collect, clean, and preprocess structured and unstructured data from multiple sources.
- Develop, train, validate, and deploy machine learning models for predictive and prescriptive analytics.
- Perform exploratory data analysis (EDA) to identify trends, correlations, and patterns.
- Conduct statistical analysis to support hypothesis testing and business experimentation.
- Build scalable data pipelines and reusable analytical workflows.
- Create interactive dashboards and visual reports using tools like Tableau and Power BI.
- Translate complex analytical results into clear, actionable insights for non-technical stakeholders.
- Collaborate with data engineers to optimize data storage and retrieval.
- Monitor model performance and continuously improve accuracy and efficiency.
- Document methodologies, experiments, and model results for reproducibility.
- Stay up to date with emerging data science techniques and industry best practices.
Required Skills & Qualifications:
- 26 years of experience in data science, machine learning, or related analytical roles.
- Strong programming skills in Python and/or R.
- Hands-on experience with data manipulation and analysis libraries such as:
- Pandas
- NumPy
- Scikit-learn
- Strong knowledge of SQL for data extraction and manipulation.
- Solid understanding of machine learning algorithms (regression, classification, clustering, ensemble methods).
- Strong foundation in statistics, probability, and hypothesis testing.
- Experience with data visualization tools such as:
- Tableau
- Microsoft Power BI
- Experience working with large datasets and performing feature engineering.
- Strong analytical thinking and problem-solving skills.
- Ability to communicate technical findings to business stakeholders effectively.
Preferred Qualifications:
- Experience with deep learning frameworks (TensorFlow, PyTorch).
- Exposure to cloud platforms (AWS, Azure, or GCP) for model deployment.
- Knowledge of big data technologies (Spark, Hadoop).
