We’re not just building better tech. We’re rewriting how data moves and what the world can do with it. With Confluent, data doesn’t sit still. Our platform puts information in motion, streaming in near real-time so companies can react faster, build smarter, and deliver experiences as dynamic as the world around them.

It takes a certain kind of person to join this team. Those who ask hard questions, give honest feedback, and show up for each other. No egos, no solo acts. Just smart, curious humans pushing toward something bigger, together.

One Confluent. One Team. One Data Streaming Platform.

The Data Science Team is at the heart of our company, building the central nervous system that drives better and faster decisions through data and predictive models. We are seeking an inspirational leader to guide a team of highly skilled data scientists in creating advanced forecasting models and predictive solutions using state of the art ML infrastructure.

We need a hands-on independent leader with expertise in various time series techniques and supervised and unsupervised modeling. This role also requires a strong advocate for MLOps to ensure team productivity and efficiency, along with a deep understanding of open-source libraries like MLFlow and Hydra to build scalable models with best practices.

If you are a visionary with a passion for ML and a knack for fostering innovation, we want to chat with you. The journey will be rewarding in every sense. Join us and make an impact!

• Leadership and Team Management:

  • Lead and mentor a team of highly skilled data scientists, fostering a collaborative and innovative environment.

  • Develop and execute a strategic vision for the ML Data Science team, aligning with company goals.

  • Ensure the team delivers high-quality predictive models and forecasting solutions that drive business value.

• Stakeholder Collaboration and Communication:

  • Collaborate with cross-functional teams to understand business needs and translate them into data science projects.

  • Communicate complex technical concepts and results to non-technical stakeholders in a clear and actionable manner.

• Time Series Forecasting:

  • Utilize statistical time series methodologies such as ARIMA and SARIMA, advanced forecasting strategies with deep learning, transformers, and LLMs to develop precise and scalable forecasting models.

  • Decompose time series data into trend, seasonality, baseline, and error components to improve forecast accuracy.

  • Experiment with and implement novel approaches to enhance forecasting performance.

• Supervised, Unsupervised, and Deep Learning Modelling:

  • Apply unsupervised learning techniques for customer segmentation and insights.

  • Build supervised learning models for classification tasks such as NBA, churn prediction, and cross-sell opportunities.

  • Develop and deploy deep learning models to solve complex business problems and enhance predictive accuracy.

• MLOps and Best Practices:

  • Implement MLOps to streamline model development, deployment, and monitoring, enhancing team productivity and efficiency.

  • Utilize open-source libraries such as MLFlow and Hydra to ensure scalable and reproducible model development.

  • Advocate for and enforce best practices in data science and machine learning workflows.

• Continuous Learning and Innovation:

  • Stay up-to-date with the latest trends and advancements in data science, machine learning, and AI.

  • Encourage continuous learning and development within the broader data team, fostering a culture of innovation.

• Advanced degree in Computer Science, Engineering, Statistics, or a related technical field.

• 10+ years of industry experience in Data Science, preferably in companies with a strong data-driven culture.

• 5+ years of experience leading and mentoring Data Science teams, collaborating with Data Engineering, enterprise systems, and Business Unit embedded operations teams.

• Proven leadership in developing and executing strategic visions for ML Data Science teams aligned with company goals.

• Proficiency in Python and data science libraries such as tensorflow, scikit-learn, pandas, NumPy, etc., for model development, evaluation, and deployment.

• Ability to ensure the delivery of high-quality predictive models and forecasting solutions that drive business value.

• Expertise in statistical time series methodologies such as ARIMA, SARIMA, and advanced forecasting strategies using deep learning, transformers, and LLMs.

• Proficiency in supervised, unsupervised, and deep learning techniques for customer segmentation, classification tasks (e.g., NBA, churn prediction), and complex business problem-solving.

• Experience implementing MLOps to streamline model development, deployment, and monitoring, enhancing team productivity and efficiency.

• Strong communication and presentation skills to collaborate with cross-functional teams, translate business needs into data science projects, and communicate technical concepts to non-technical stakeholders effectively.

• Experience with GCP Vertex AI ML platform or similar platforms for model development, deployment, and management.

• Experience implementing MLOps best practices to streamline end to end model building.

• Experience in effectively driving measurable business outcomes using advanced modeling techniques

Come As You Are

Belonging isn’t a perk here. It’s the baseline. We work across time zones and backgrounds, knowing the best ideas come from different perspectives. And we make space for everyone to lead, grow, and challenge what’s possible.

We’re proud to be an equal opportunity workplace. Employment decisions are based on job-related criteria, without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, veteran status, or any other classification protected by law.