Senior Data Science Analyst, Consumer Solutions

Role Overview: At TransUnion, you will be part of an environment that encourages professional development and provides access to support and mentorship. You will have the opportunity to pursue your passions and take ownership of your career with the help of colleagues and mentors. Regardless of your job title, you will be empowered to learn new things and be a leader every day. Key Responsibilities: - Establish and enhance ongoing monitoring programs around key performance indicators for consumer products. - Conduct in-depth product analysis to identify trends, patterns, and insights for informed business decisions. - Develop, implement, and maintain advanced data models to support product development and optimization. - Design and execute experiments to test hypotheses and measure the impact of product changes. - Utilize statistical methods and machine learning techniques to analyze large datasets and generate actionable insights. - Present analytical findings and recommendations to internal and external stakeholders in a clear and concise manner. - Mentor and guide junior data analysts, fostering a culture of continuous learning and improvement. - Collaborate with cross-functional teams to understand business needs and deliver data-driven solutions. - Contribute to omnichannel fraud reporting by analyzing breach databases to identify trends and generate summaries of findings. Qualifications Required: - Masters or PhD degree in a quantitative discipline such as Mathematics, Statistics, Engineering, or Analytics with at least one (1) year of relevant professional experience, or a Bachelors degree in a quantitative field with at least three (3) years of relevant professional experience. - Proficiency with programming and data manipulation languages such as SQL, Hive, Spark; experience with statistical programs such as R or Python; high level of familiarity with Microsoft Office tools. - Strong experience with data visualization tools (e.g., Tableau, Power BI). - Expertise in statistical analysis and machine learning techniques. - Proven analytical, critical thinking, and creative problem-solving skills with attention to detail. - Strong communication skills to convey complex data insights to non-technical stakeholders. - Strong project and time management skills with the ability to manage multiple assignments effectively. - Experience working in an agile environment is a plus. (Note: The additional details of the company were not present in the provided job description) Role Overview: At TransUnion, you will be part of an environment that encourages professional development and provides access to support and mentorship. You will have the opportunity to pursue your passions and take ownership of your career with the help of colleagues and mentors. Regardless of your job title, you will be empowered to learn new things and be a leader every day. Key Responsibilities: - Establish and enhance ongoing monitoring programs around key performance indicators for consumer products. - Conduct in-depth product analysis to identify trends, patterns, and insights for informed business decisions. - Develop, implement, and maintain advanced data models to support product development and optimization. - Design and execute experiments to test hypotheses and measure the impact of product changes. - Utilize statistical methods and machine learning techniques to analyze large datasets and generate actionable insights. - Present analytical findings and recommendations to internal and external stakeholders in a clear and concise manner. - Mentor and guide junior data analysts, fostering a culture of continuous learning and improvement. - Collaborate with cross-functional teams to understand business needs and deliver data-driven solutions. - Contribute to omnichannel fraud reporting by analyzing breach databases to identify trends and generate summaries of findings. Qualifications Required: - Masters or PhD degree in a quantitative discipline such as Mathematics, Statistics, Engineering, or Analytics with at least one (1) year of relevant professional experience, or a Bachelors degree in a quantitative field with at least three (3) years of relevant professional experience. - Proficiency with programming and data manipulation languages such as SQL, Hive, Spark; experience with statistical programs such as R or Python; high level of familiarity with Microsoft Office tools. - Strong experience with data visualization tools (e.g., Tableau, Power BI). - Expertise in statistical analysis and machine learning techniques. - Proven analytical, critical thinking, and creative problem-solving skills with attention to detail. - Strong communication skills to convey complex data insights to non-technical stakeholders. - Strong project and time management skills with the ability to manage multiple assignments effectively. - Experience working in an agile environment is a plus. (Note: The additional details of the company were not pre