Lead Data Scientist

Lead Data Scientists at Excella drive the development and implementation of advanced analytics solutions, ensuring alignment with business objectives and technical best practices. They provide strategic leadership in data science projects, mentor team members, and influence decision-making through data-driven insights.

Responsibilities:

• Lead the design and execution of data science projects, ensuring high-impact analytics solutions.
• Partner with client stakeholders to understand business challenges and develop data-driven strategies.
• Oversee data acquisition and integration, ensuring data quality and reliability.
• Apply and refine machine learning and predictive modeling techniques to solve complex business problems.
• Guide the deployment and integration of predictive models into business applications.
• Develop and implement strategies for optimizing model performance and monitoring over time.
• Present findings and recommendations to executives, translating complex data concepts into actionable business strategies.
• Mentor and support junior and senior team members in data science methodologies and best practices.
• Influence data governance and best practices within the organization.

Qualifications:

• 6+ years of experience in predictive analytics using tools like Python, R, or Scala.
• 6+ years of experience writing complex SQL queries for data extraction and transformation.
• Extensive experience applying machine learning techniques, including deep learning and NLP.
• Expertise in working with large-scale data platforms, including Hadoop, Spark, and cloud-based solutions.
• Strong background in leading data science teams and mentoring junior data scientists.
• Proven ability to translate business problems into data science solutions.
• Excellent communication skills for engaging with stakeholders at all levels, including executives.
• Experience leading projects within Agile Scrum frameworks.
• Strong strategic thinking, problem-solving skills, and ability to drive decision-making based on data insights.
• Familiarity with DevOps Research and Assessment (DORA) and its application in analytics.
• Continuous learning mindset with a passion for staying up to date on emerging data science technologies.