Senior Data Scientist Job at AppOmni, Remote

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  • AppOmni
  • Remote

Job Description

Role Description

AppOmni is looking for a Senior Data Scientist to help define and build scalable, production-grade data pipelines and intelligent analytics capabilities within our SaaS platform. In this role, you will apply data science, statistical modeling, batch and real-time analytics, and large-scale data engineering to transform complex datasets into actionable product insights and customer-facing capabilities.

  • Work across a broad range of technical domains on pipelines, including ETL, statistical modeling, machine learning (supervised and unsupervised), and LLM.
  • Responsible for end-to-end data workflows, from ingestion and transformation through analytics implementation, orchestration, monitoring, governance, and production operations.
  • Hands-on individual contributor role with technical leadership responsibilities.
  • Partner closely with Product and Engineering to build reliable, scalable, and intelligent data-driven systems.

Qualifications

  • 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.
  • Nice-to-have: Experience with Databricks.

Requirements

  • 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.
  • Support 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 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

  • Base Salary: The annual base salary compensation range in the U.S. for this role is: $190,000 - $215,000 USD.
  • Stock Options: Opportunity to be an integral part of our journey forward.
  • Generous paid time off, paid company holidays, paid floating holidays, paid parental leave, paid sick time, and paid family leave for applicable states.
  • Health insurance - medical, dental, and vision with HSA option.
  • LifeWorks Employee Assistance Program.
  • Company-provided life insurance, AD&D, STD/LTD, and additional supplemental life insurance options.
  • 401(k) and Roth retirement saving accounts.
  • Monthly wellness benefit reimbursement.

Job Tags

Full time

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