Lead Data Scientist - Machine Learning

As a Lead Data Scientist, you will be responsible for applying data science and machine learning techniques to derive insights and manipulate data effectively. Your role will involve utilizing AI methodologies for data processing and analysis. Your key responsibilities will include: - Demonstrating expertise in SQL, Python (including pandas, numpy, scikit-learn, scipy, statsmodels), and experience with gradient boosting methods such as xgboost, lightgbm, or catboost. - Leveraging strong math and statistics background to develop descriptive and probabilistic theories, sampling techniques, and problem-solving skills. - Building and executing advanced solutions for audience analytics and insights. - Handling large-scale, multi-source data with proficiency in SQL and version control tools like Git. - Utilizing Python for modeling and analytics, specifically with pandas, numpy, scikit-learn, scipy, and statsmodels. - Experience with data visualization tools like Power BI, especially for geo-coded data, is a significant advantage. - Understanding and implementing data governance practices including data QA, naming taxonomy, and data & platform integration. Qualifications required for this role include: - 6+ years of work experience in applied data science, analytics, or ML engineering. - Certification in Data Science. - Proficiency in data governance practices and collaborative coding workflows. - Strong analytical and problem-solving skills with a focus on AI methodologies for data manipulation and insight. You will also have the opportunity to work with Microsoft Power BI and enhance your skills as a data scientist in a dynamic environment. As a Lead Data Scientist, you will be responsible for applying data science and machine learning techniques to derive insights and manipulate data effectively. Your role will involve utilizing AI methodologies for data processing and analysis. Your key responsibilities will include: - Demonstrating expertise in SQL, Python (including pandas, numpy, scikit-learn, scipy, statsmodels), and experience with gradient boosting methods such as xgboost, lightgbm, or catboost. - Leveraging strong math and statistics background to develop descriptive and probabilistic theories, sampling techniques, and problem-solving skills. - Building and executing advanced solutions for audience analytics and insights. - Handling large-scale, multi-source data with proficiency in SQL and version control tools like Git. - Utilizing Python for modeling and analytics, specifically with pandas, numpy, scikit-learn, scipy, and statsmodels. - Experience with data visualization tools like Power BI, especially for geo-coded data, is a significant advantage. - Understanding and implementing data governance practices including data QA, naming taxonomy, and data & platform integration. Qualifications required for this role include: - 6+ years of work experience in applied data science, analytics, or ML engineering. - Certification in Data Science. - Proficiency in data governance practices and collaborative coding workflows. - Strong analytical and problem-solving skills with a focus on AI methodologies for data manipulation and insight. You will also have the opportunity to work with Microsoft Power BI and enhance your skills as a data scientist in a dynamic environment.