Sr. Advanced Data Scientist leveraging advanced analytics and data science at Honeywell. Developing solutions for business growth and operational efficiency in the Atlanta office.
About the role
- Data Scientist developing AI-powered mobile applications at AppNation. Ensure data flow and infrastructure management in a fast-paced mobile tech environment.
Responsibilities
- Ensure Healthy Data Flow: Collaborate with development teams to verify, troubleshoot, and maintain a consistent, reliable flow of data from all our sources (including mobile apps and third-party platforms) into our data systems.
- Own Data Infrastructure: Take ownership of building and optimizing our internal data infrastructure and pipelines, including designing efficient data models/tables and streamlining data workflows as we scale.
- Enable Visualization Tools: Assist in the implementation and effective use of modern data visualization platforms (Looker, Metabase), ensuring teams have well-designed data models and self-service dashboards to derive insights easily.
- Improve Data Culture: Champion a data-driven culture across teams by promoting best practices and translating data into actionable insights that drive decision-making.
- Lead Cross-Team Communication: Act as the point person for data-related collaboration, ensuring smooth and effective communication and alignment between marketing, product, and engineering teams on all data needs.
- Interpret & Report Data: Transform raw data into clear, compelling reports and actionable recommendations that support strategic decision-making processes.
- Experiment & Optimize: Design and analyze experiments (e.g., A/B tests) and use insights to continuously improve product and marketing performance. When needed, contribute to lightweight predictive work such as LTV forecasting and user behavior analysis to support growth decisions.
Requirements
- Proven Data Experience: At least 2 years of hands-on experience in data analysis, business intelligence, or a related role (exposure to data engineering/analytics engineering is a plus), with a strong understanding of mobile product analytics and KPIs.
- SQL & BigQuery Proficiency: Advanced SQL skills and experience with cloud-based data warehouses (especially Google BigQuery), including writing complex, optimized queries on large datasets.
- ETL & Dashboard Skills: Solid experience with ETL processes and managing data pipelines; proficiency with business intelligence tools such as Looker, Metabase or Tableau. Experience with modern data workflow frameworks (e.g., Dataform or dbt on GCP) is a strong plus.
- Programming Knowledge: Proficiency in Python for scripting, automation, and data analysis tasks. Ability to write code to support ETL pipelines and perform statistical analysis when needed.
- Mobile Analytics Tools: Experience with mobile attribution/analytics platforms like Appsflyer or Adjust is a big plus, especially for campaign tracking and user acquisition analysis.
- Analytical and growth-oriented: Strong problem-solving skills with the ability to turn complex data into clear, actionable insights. Comfortable shifting between priorities, from building pipelines and optimizing data models to delivering dashboards, while continuously improving as our analytics setup evolves.
- Cross-functional communicator: Comfortable working across departments and proactively sharing insights. Able to present findings clearly to both technical and non-technical audiences, with a structured narrative that drives alignment and action.
Benefits
- Work with exceptional people.
- A platform for growth.
- Competitive compensation.
- Unmatched benefits.
Job title
Job type
Experience level
Salary
Not specified
Degree requirement
No Education Requirement
Tech skills
Location requirements
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