Data Scientist - Predictive Analytics & Machine Learning

As a Data Science Lead, you will be responsible for guiding a team of data scientists and analysts to deliver high-quality results. Your key responsibilities include: - Leading and mentoring a team of data scientists and analysts to ensure high-quality deliverables. - Designing, developing, and optimizing machine learning models such as classification, regression, clustering, and forecasting. - Building and maintaining big data processing pipelines using PySpark, Spark SQL, and distributed computing environments. - Architecting and deploying scalable ML solutions on Azure platforms like Azure Databricks, Azure ML, ADLS, ADF. - Overseeing feature engineering, model lifecycle management, monitoring, and performance tuning. - Collaborating with cross-functional teams to translate business requirements into analytical solutions. - Presenting insights, model outputs, and recommendations to technical and business stakeholders. To excel in this role, you are required to have the following qualifications: - 8 years of hands-on experience in data science and ML development. - Strong expertise in leading complex analytical problem solving using traditional ML architecture, supervised and unsupervised learning, time series, and deep learning, along with excellent team leadership skills. - Proficiency in Python, PySpark, scikitlearn, XGBoost, and related ML libraries. - Solid experience with Azure data and ML services. - Understanding of distributed computing and performance optimization using Spark. - Demonstrated ability to lead technical teams, conduct code reviews, mentor juniors, and manage project execution. - Excellent communication, stakeholder management, and problem-solving abilities. - Familiarity with MLOps practices and CI/CD pipelines. This job offers an opportunity to work with cutting-edge technologies and collaborate with diverse teams to drive impactful business solutions. As a Data Science Lead, you will be responsible for guiding a team of data scientists and analysts to deliver high-quality results. Your key responsibilities include: - Leading and mentoring a team of data scientists and analysts to ensure high-quality deliverables. - Designing, developing, and optimizing machine learning models such as classification, regression, clustering, and forecasting. - Building and maintaining big data processing pipelines using PySpark, Spark SQL, and distributed computing environments. - Architecting and deploying scalable ML solutions on Azure platforms like Azure Databricks, Azure ML, ADLS, ADF. - Overseeing feature engineering, model lifecycle management, monitoring, and performance tuning. - Collaborating with cross-functional teams to translate business requirements into analytical solutions. - Presenting insights, model outputs, and recommendations to technical and business stakeholders. To excel in this role, you are required to have the following qualifications: - 8 years of hands-on experience in data science and ML development. - Strong expertise in leading complex analytical problem solving using traditional ML architecture, supervised and unsupervised learning, time series, and deep learning, along with excellent team leadership skills. - Proficiency in Python, PySpark, scikitlearn, XGBoost, and related ML libraries. - Solid experience with Azure data and ML services. - Understanding of distributed computing and performance optimization using Spark. - Demonstrated ability to lead technical teams, conduct code reviews, mentor juniors, and manage project execution. - Excellent communication, stakeholder management, and problem-solving abilities. - Familiarity with MLOps practices and CI/CD pipelines. This job offers an opportunity to work with cutting-edge technologies and collaborate with diverse teams to drive impactful business solutions.