Glassbox is looking for a Data Science Team Lead to join our Global R&D team.
We are Glassbox, the world's leader in digital experience intelligence (DXI), and on a mission to deliver frictionless digital journeys to leading brands and their customers all over the world
We are a hyper-growth scale-up company that continues to grow quarter-over-quarter, and our customers love us- named a 2022 leader in 9 G-2 categories based on customer reviews!
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So, now is the perfect time to come to Glassbox and help us accelerate our global leadership position!
Will you join us on this journey?
As a Data Science Team Lead at Glassbox, you have the unique opportunity to be part of an exciting venture that is shaping the future of customer experience analytics.
You will be at the helm of a skilled team, dedicated to solving complex problems and driving breakthrough innovations.
This role calls for a strategic thinker and a visionary, someone who can inspire and lead a multi-faceted team to turn data into actionable insights. Here, you will have the chance to harness cutting-edge technologies to make a significant impact in a growing industry, while also driving the professional development of a vibrant team.
What You Will Do
- Lead, mentor, and manage a talented team of data scientists, data engineers, and machine learning engineers
- Collaborate with product managers and stakeholders to define data-driven features and drive the analytics roadmap
- Develop and implement state-of-the-art analytics models to solve complex customer behavior and experience challenges
- Guide the development of machine learning systems for analytics, identifying trends, and offering insights for optimization
- Act as a thought leader within the organization and the industry, evangelizing the use of data and machine learning to solve critical business challenges
- Work closely with engineering and data teams to ensure streamlined deployment of analytics models in production
- Drive innovation within the team and company by staying current with trends and technologies in analytics and machine learning
What You Will Need
- 5+ years of hands-on experience as a data scientist, focusing on analytics, machine learning, or statistical modeling
- 2+ years of managerial experience leading data science or technical teams
- MS in Computer Science, Statistics, Mathematics, or a related quantitative field
- Proficiency in Python or Scala, and familiarity with libraries such as TensorFlow or PyTorch
- Experience with Spark for big data processing
- Familiarity with cloud services (preferably AWS) and Kubernetes for scaling machine learning models
- Solid understanding of MLOps practices for deploying and monitoring machine learning models in production
- Strong knowledge of machine learning algorithms, statistical models, and data mining techniques
Advantage
- Experience with product analytics or user behavior analysis
- Experience working with cross-functional teams including engineering, product, and business
