AppOmni - Lead Data Scientist
Requirements
• 7–10+ years of experience as a Data Scientist, Applied Scientist, Data Engineer, or Machine Learning Engineer, with ownership of production systems. • Strong experience building and operating large-scale data pipelines and distributed data processing systems. • Hands-on experience within the GCP ecosystem, particularly big data services such as Dataproc, Dataflow, PubSub, and related storage and data lake technologies. • Strong proficiency in Python, PySpark, and modern data processing frameworks. • Experience working across multiple disciplines of the data stack, including data engineering, analytics, infrastructure, monitoring/governance, APIs, and visualization. • Experience with real-time or streaming systems and orchestration frameworks such as Airflow and Apache Beam/Dataflow. • Strong foundation in statistical modeling, analytics, and applied data science techniques. • Experience designing and maintaining scalable ETL workflows and production data infrastructure. • Familiarity with monitoring, observability, governance, and reliability practices for production data systems. • Ability to thrive in highly cross-functional environments and contribute across a wide range of technical challenges. • Demonstrated versatility — a background that spans multiple types of data applications, infrastructure, and analytics work is highly valued. • Experience partnering closely with Product and Engineering to deliver customer-facing capabilities. • Strong written and verbal communication skills. • Culture • Culture • Our talented team is collaborative and supportive as we move quickly to research and develop new ideas, deliver new features to our customers, and iterate on ideas and innovations. We accomplish this by focusing on our five core values: Trust, Transparency, Quality, Customer Focus, and Delivery. Our team is determined to make a difference to positively impact our way of life by securing the technology that is changing the world.AppOmni is proud to be Certified by Great Place to WorkⓇ, as we seek to build a culture where all employees feel appreciated and supported, especially with clear and honest leadership, employee recognition, and an environment that fosters innovation and collaboration.We believe diversity fuels innovation and drives growth by bringing a wealth of different perspectives and skills. We’re committed to fostering an inclusive environment where every employee feels valued, heard, and empowered to reach their full potential. Join us in building a workplace where we can all thrive.
Responsibilities
• Design and implement scalable batch and real-time data processing systems across large and complex datasets. • Build and optimize ETL and streaming data pipelines using modern GCP big data technologies. • Lead development decisions around model choices, data architecture, data modeling, pipeline orchestration, analytics infrastructure, and production systems. • Develop statistical models and analytics capabilities that support product intelligence and operational insights. • Design and maintain production-grade data workflows using technologies such as Airflow, Dataflow, PubSub, and PySpark. • Contribute across multiple areas of the data ecosystem, including data engineering, monitoring and governance, visualization, and analytics tooling. • Establish monitoring, observability, and governance practices for data quality, pipeline reliability, and production health. • Partner closely with Engineering to operationalize scalable data infrastructure and analytics systems. • Collaborate with Product to shape intelligent, data-driven product capabilities and user experiences. • Act as a technical leader and thought partner across data engineering, analytics, infrastructure, and applied modeling initiatives. • Help evolve internal tooling and frameworks that improve scalability, reliability, and operational efficiency across the platform.
Benefits
• AppOmni is committed to supporting our employees' financial, professional, and personal well-being. To do this, we take a holistic view of compensation, one that values not just the immediate financial package but also the long-term growth of both our employees and our company. We're committed to pay equity and transparency and encourage all candidates to discuss their salary expectations with us early in the application process.Our total rewards package includes the following:
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