We are looking for a skilled Data Scientist with a strong background in Mathematics, Statistics, and Machine Learning. The ideal candidate should have hands-on experience with Python, SQL, statistical analysis, and predictive modeling, along with the ability to analyze complex real-world datasets and develop reliable, data-driven solutions.
Roles & Responsibilities
- Analyze large and complex datasets to identify patterns, trends, and actionable insights.
- Develop, implement, and validate statistical and machine-learning models.
- Apply statistical methods, probability, and mathematical techniques to solve business problems.
- Work with messy, sparse, imbalanced, and imperfect real-world datasets.
- Perform data cleaning, preprocessing, feature engineering, and exploratory data analysis.
- Design experiments and apply appropriate statistical techniques for model evaluation.
- Validate models using suitable performance metrics and statistical methods.
- Evaluate model accuracy, reliability, uncertainty, and performance.
- Use Python and SQL for data analysis, modeling, and data manipulation.
- Collaborate with cross-functional teams to translate business requirements into analytical solutions.
- Document analytical approaches, modeling methodologies, and findings.
Required Skills & Qualifications
- Bachelor's or Master's degree in Mathematics, Statistics, Applied Mathematics, Data Science, or a related quantitative discipline.
- Strong hands-on experience in Python and SQL.
- Strong foundation in Statistics, Probability, and Applied Mathematics.
- Experience developing and validating statistical and Machine Learning models.
- Strong understanding of data preprocessing, exploratory data analysis, and feature engineering.
- Experience handling messy, sparse, imbalanced, and real-world datasets.
- Knowledge of experimental design, model validation, and performance evaluation metrics.
- Strong analytical, problem-solving, and critical-thinking skills.