Lead Data Science Director

2 weeks ago

San Francisco, California, United States Unreal Gigs Full time
Job Title: Lead Data Science Manager

At Unreal Gigs, we're seeking a seasoned data science leader to spearhead our data science initiatives and drive the development of advanced analytics solutions. As the Lead Data Science Manager, you'll play a pivotal role in leading our data science team and collaborating closely with cross-functional teams to deliver actionable insights and recommendations that drive business impact.

Key Responsibilities:
  • Team Leadership: Provide strategic guidance, mentorship, and leadership to a team of data scientists, fostering a culture of excellence, innovation, and collaboration.
  • Project Management: Lead end-to-end data science projects, from problem formulation and data exploration to model development, deployment, and validation, ensuring timely delivery and high-quality results.
  • Advanced Analytics: Drive the development and implementation of advanced analytics solutions, including predictive modeling, machine learning, and artificial intelligence techniques, to solve complex business problems and drive business outcomes.
  • Model Development: Lead the development of predictive models, forecasting models, and optimization models to support business decision-making, leveraging techniques such as regression analysis, classification, clustering, and deep learning.
  • Data Exploration: Explore and analyze large and complex datasets to uncover actionable insights and identify patterns, trends, and correlations, using statistical analysis techniques and data visualization tools.
  • Model Deployment: Lead efforts to deploy and operationalize data science models in production environments, collaborating with software engineering teams to integrate models into business applications and processes.
  • Performance Monitoring: Implement monitoring and tracking mechanisms to assess the performance and impact of data science initiatives, proactively identifying opportunities for improvement and optimization.
  • Collaboration: Collaborate closely with cross-functional teams, including business stakeholders, data engineers, software developers, and product managers, to understand requirements and deliver data-driven solutions that meet business needs.
  • Documentation and Reporting: Document analysis methodologies, model development processes, and findings in clear and concise reports, ensuring transparency and reproducibility of results.
  • Mentorship and Development: Mentor and coach data scientists, providing guidance, support, and opportunities for skill development and career growth, and foster a culture of continuous learning and improvement within the team.
Qualifications:
  • Master's or Ph.D. degree in Computer Science, Statistics, Mathematics, Engineering, or related field.
  • 8+ years of experience in data science, with a focus on predictive modeling, machine learning, and advanced analytics.
  • Proven leadership experience, with a track record of successfully leading data science teams and delivering impactful insights and recommendations.
  • Proficiency in programming languages such as Python or R for data analysis and modeling, and experience with data science libraries such as TensorFlow, PyTorch, or scikit-learn.
  • Strong quantitative and analytical skills, with experience in statistical analysis, hypothesis testing, and machine learning algorithms.
  • Excellent communication and collaboration skills, with the ability to work effectively in cross-functional teams and communicate technical concepts to non-technical stakeholders.
  • Strong problem-solving skills and attention to detail, with the ability to analyze complex datasets and derive actionable insights.
Benefits:
  • Competitive salary: The industry standard salary for Lead Data Science Managers typically ranges from $190,000 to $250,000 per year, depending on experience and qualifications.
  • Comprehensive benefits package, including health insurance, retirement plans, and wellness programs.
  • Flexible work arrangements, including remote work options and flexible hours.
  • Generous vacation and paid time off.
  • Professional development opportunities, including access to training programs, conferences, and workshops.
  • State-of-the-art technology environment with access to cutting-edge tools and resources.
  • Vibrant and inclusive company culture with opportunities for growth and advancement.
  • Exciting projects with real-world impact at the forefront of data-driven innovation.

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