Data Scientist - Python

In this role, you will be responsible for the following: - Collecting, preprocessing, cleaning, and transforming structured and unstructured data to ensure data quality and usability for analytical and machine learning applications. - Performing exploratory data analysis (EDA), statistical analysis, and data visualization to identify trends, patterns, and business opportunities. - Developing and implementing machine learning models for classification, prediction, segmentation, and recommendation systems. - Applying data mining techniques such as association rule mining, market basket analysis, clustering, and pattern discovery to solve business challenges. - Designing and executing feature engineering and feature selection strategies to improve model performance and scalability. - Working with large-scale datasets using distributed computing frameworks and big data technologies such as Hadoop or Spark. - Collaborating with business stakeholders, data engineers, and cross-functional teams to translate business requirements into analytical solutions. - Ensuring ethical and responsible use of data by adhering to privacy regulations, governance standards, and industry best practices. Qualifications required for this role include: - 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. Additionally, the technical competencies required for this role are as follows: - Expert proficiency in Python programming. - Strong experience with Pandas, NumPy, and 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 Matplotlib, Power BI, and 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 for this role include: - 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. In this role, you will be responsible for the following: - Collecting, preprocessing, cleaning, and transforming structured and unstructured data to ensure data quality and usability for analytical and machine learning applications. - Performing exploratory data analysis (EDA), statistical analysis, and data visualization to identify trends, patterns, and business opportunities. - Developing and implementing machine learning models for classification, prediction, segmentation, and recommendation systems. - Applying data mining techniques such as association rule mining, market basket analysis, clustering, and pattern discovery to solve business challenges. - Designing and executing feature engineering and feature selection strategies to improve model performance and scalability. - Working with large-scale datasets using distributed computing frameworks and big data technologies such as Hadoop or Spark. - Collaborating with business stakeholders, data engineers, and cross-functional teams to translate business requirements into analytical solutions. - Ensuring ethical and responsible use of data by adhering to privacy regulations, governance standards, and industry best practices. Qualifications required for this role include: - 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. Additionally, the technical competencies required for this role are as follows: - Expert proficiency in Python programming. - Strong experience with Pandas, NumPy, and 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 Matplotlib, Power BI, and Tableau. - Knowledge of machine learning algorithms, clustering techniques, and predictive analytics. - Familiarity with big data