Data Scientist Lead - Remote / Telecommute

Data Science Lead

Pay Range: $90.69hr - $94.69hr

Lead data science initiatives by applying advanced analytics, machine learning, and AI techniques to drive business insights and solutions.

Mentor team members and ensure delivery of scalable, high-quality data products aligned with organizational goals.

Responsibilities:

• Lead data mining, data extraction, and application of algorithms to generate actionable insights.
• Synthesize analytical findings and present insights to stakeholders and senior leadership.
• Drive adoption and implementation of machine learning and AI solutions across the organization.
• Apply AI techniques to solve business problems within data and resource constraints.
• Mentor and develop junior data scientists to enhance analytical capabilities.
• Translate business priorities into actionable data science deliverables.
• Lead implementation of ML/AI/DS best practices for new data products.
• Design and build scalable, robust data science solutions and software.

Required Qualifications:

• Bachelor’s degree in Statistics, Mathematics, Computer Science, or related field.
• 8+ years of relevant data science or analytics experience.
• In lieu of a degree, 12+ years of relevant experience.
• Strong expertise in statistical modeling and analytical techniques.
• Advanced proficiency in SQL across multiple syntaxes.
• Experience with model evaluation, tuning, and performance optimization.
• Ability to operationalize and scale data science solutions.
• Strong communication and documentation skills.

Preferred Qualifications:

• Expertise in a wide range of data science tools and frameworks.
• Experience supporting data exploration and advanced analytics initiatives.
• Proven ability to design and deploy scalable machine learning solutions.

Skills and Competencies:

• Leadership and mentoring capabilities.
• Strong analytical and problem-solving skills.
• Ability to translate complex data into actionable insights.
• Effective communication with technical and non-technical stakeholders.
• Strategic thinking with a focus on business outcomes.
• Ability to manage multiple priorities and deliver high-quality results.