Data Scientist-KMPL Support Services-Analytics

As a Data Scientist, you will be responsible for developing and implementing advanced analytics solutions to address complex business challenges. You will work closely with cross-functional teams to understand their data needs and provide valuable insights. Your expertise in data modeling, machine learning, and statistical analysis will be instrumental in driving the company's strategic initiatives.

• Master's or Ph.D. degree in a quantitative field such as Statistics, Mathematics, Computer Science, or a related discipline.
• Minimum 3 years of experience in a data science role, preferably in a financial services or consulting environment.
• Strong programming skills in Python, R, or similar languages for data analysis and modeling.
• Proficiency in using data visualization tools such as Tableau, Power BI, or similar platforms.
• Experience with big data technologies (e.g., Hadoop, Spark) is preferred.
• Excellent problem-solving and analytical skills, with a track record of delivering innovative solutions.
• Ability to communicate complex technical concepts to both technical and non-technical stakeholders.
• Strong collaboration and teamwork skills, with a willingness to work in a dynamic and fast-paced environment.
• A passion for data-driven decision-making and a desire to drive business impact through analytics.
• A self-starter with a proactive approach to learning and staying updated with industry trends.

• Design and develop robust data models and algorithms to extract meaningful insights from large datasets.
• Apply machine learning techniques to build predictive models and optimize business processes.
• Collaborate with stakeholders to understand their data requirements and translate them into actionable analytics solutions.
• Conduct thorough data analysis and visualization to communicate complex information effectively.
• Stay updated with the latest advancements in data science and machine learning technologies.
• Ensure data quality and integrity by implementing robust data validation processes.
• Document and present your findings to both technical and non-technical audiences.
• Provide technical support and guidance to other team members on data-related projects.
• Contribute to the development of data-driven products and services, enhancing the company's competitive advantage.