Key Responsibilities :

- Collect, preprocess, clean, and transform structured and unstructured data to ensure data quality and usability for analytical and machine learning applications.

- Perform exploratory data analysis (EDA), statistical analysis, and data visualization to identify trends, patterns, and business opportunities.

- Develop and implement machine learning models for classification, prediction, segmentation, and recommendation systems.

- Apply data mining techniques such as association rule mining, market basket analysis, clustering, and pattern discovery to solve business challenges.

- Design and execute feature engineering and feature selection strategies to improve model performance and scalability.

- Work with large-scale datasets using distributed computing frameworks and big data technologies such as Hadoop or Spark.

- Collaborate with business stakeholders, data engineers, and cross-functional teams to translate business requirements into analytical solutions.

- Ensure ethical and responsible use of data by adhering to privacy regulations, governance standards, and industry best practices.

Required Qualifications :

- Bachelors or Masters degree in Computer Science, Data Science, Statistics, Mathematics, Engineering, or a related field.

- Minimum 5 years of hands-on experience in Data Science, Data Analytics, or Data Engineering roles.

- Proven experience in applying data mining and machine learning techniques to real-world business problems.

- Strong understanding of statistical analysis, predictive modeling, and machine learning fundamentals.

Required Skills :

Technical Competencies :

- Expert proficiency in Python programming.

- Strong experience with :

1. Pandas

2. NumPy

3. Scikit-learn

- Advanced SQL skills and experience working with relational databases.

- Strong understanding of data preprocessing, feature engineering, and model evaluation techniques.

- Experience with data visualization and reporting tools such as :

1. Matplotlib

2. Power BI

3. Tableau

- Knowledge of machine learning algorithms, clustering techniques, and predictive analytics.

- Familiarity with big data technologies such as Hadoop and Apache Spark.

- Basic understanding of cloud platforms including AWS, GCP, or Azure.

Preferred Skills :

- Experience building scalable machine learning pipelines and production-ready analytical solutions.

- Knowledge of advanced analytics, recommendation systems, and optimization techniques.

- Exposure to MLOps, model deployment, and cloud-based data platforms.

- Experience working in Agile development environments.