Senior Data Scientist

Overview

Key responsibilities

• Lead the development and implementation of data science solutions for complex business problems.
• Utilize advanced data mining and machine learning techniques to gather, analyze, and interpret large datasets.
• Develop and deploy predictive models and algorithms to enhance decision-making processes.
• Lead the design and implementation of experiments to test hypotheses and optimize models.
• Provide strategic guidance and mentorship to junior data scientists and analysts.
• Collaborate with cross-functional teams to identify data-driven opportunities and provide actionable insights.
• Develop and maintain scalable data pipelines and data-driven applications.
• Contribute to the development and implementation of AI and machine learning infrastructure.
• Stay current with industry trends and best practices in data science and machine learning.
• Communicate findings and insights to stakeholders in a clear and compelling manner.
• Contribute to the continuous improvement of data science processes and methodologies.
• Conduct in-depth analyses to derive insights and drive data-based decision-making.
• Lead the development and implementation of data governance and data quality initiatives.
• Participate in the hiring and talent development of the data science team.

Required qualifications

• Master's or Ph.D. in Computer Science, Statistics, Mathematics, or related field.
• Proven experience as a data scientist or similar role, with a strong track record of delivering impactful data science solutions.
• Proficiency in programming languages such as Python, R, or Java.
• Expertise in machine learning, statistical analysis, and data visualization techniques.
• Solid understanding of advanced mathematical and statistical concepts.
• Experience with big data technologies such as Hadoop, Spark, or Hive.
• Strong problem-solving and critical thinking skills.
• Ability to work effectively in a collaborative, cross-functional team environment.
• Excellent communication and presentation skills to effectively convey complex findings and insights.
• Experience with data manipulation and analysis tools such as SQL, Pandas, or NumPy.
• Proven ability to lead and mentor junior data scientists and analysts.
• Experience in designing and implementing scalable data science solutions.
• Strong attention to detail and commitment to delivering high-quality work.
• Knowledge of data governance and data quality best practices.
• Relevant certifications in data science, machine learning, or related fields are a plus.