Responsibilities: Utilize your product knowledge and data science skills to identify opportunities for improving quality and customer satisfaction. Collaborate with cross-functional teams to design and implement data-driven solutions that drive continuous improvement in product quality and customer experience. Apply statistical methods and machine learning techniques to analyze complex data sets and extract meaningful insights. Develop data pipelines and deploy models to production environments. Conduct exploratory data analysis to uncover patterns and trends and communicate findings to stakeholders. Collaborate with data engineers to ensure efficient data storage, retrieval, and management. Stay up-to-date with the latest advancements in data science, cloud technologies, and project management methodologies. Actively participate in project planning, execution, and monitoring, ensuring timely delivery of high-quality solutions. Provide mentorship and guidance to junior team members, fostering a culture of learning and growth. Qualifications: 1) Product Knowledge: Strong understanding of the products and services offered by our company, with the ability to connect product features to customer satisfaction is merit. 2) Interest in Project Management: Demonstrated interest in project management methodologies, with the ability to coordinate and prioritize tasks effectively. 3) Data Science Expertise: Profound understanding of data science concepts, including data exploration, statistical modeling, machine learning, and predictive analytics. 4) Data Engineering and Strong Statistics Knowledge: Familiarity with data engineering principles, databases, data architecture, and data visualization. Strong statistical knowledge and expertise in applying statistical methods to real-world problems. 5) Cloud Experience: Hands-on experience with cloud platforms, particularly Azure, and understanding of cloud-based data science tools and technologies. 6) Work Experience: Prior experience in a data science or analytics role is preferred, with a proven track record of delivering impactful data-driven solutions. However, exceptional candidates with a strong academic background and relevant project experience will also be considered.
