Design and implement scalable data pipelines to collect, process, and analyze large datasets. Collaborate with cross-functional teams to deliver end-to-end production-ready solutions. Translate complex datasets into clear, actionable recommendations for both technical and non-technical stakeholders.
Key Highlights
Key Responsibilities
Technical Skills Required
Benefits & Perks
Nice to Have
Job Description
Role: Data Engineer (Machine Learning)
Location: 100% Remote
Duration: Long Term Contract (2+ years)
Role Overview
The team builds data and machine learning services for advertiser sellers, helping them optimize ad budgets and campaign goals by recommending the right inventory, keywords, budgets, and bids, and continuously improving campaign performance. This is a high-growth area with strong business impact and involves working with massive datasets and applied data science techniques.
Key Responsibilities
Collaborate with Applied Researchers, Engineers, Analytics, and cross-functional teams to deliver end-to-end production-ready solutions
Design and implement scalable data pipelines to collect, process, and analyze large datasets
Integrate and deploy ML models into production systems
Perform deep data analysis to identify trends, interpret experimentation, and size opportunities in the advertising domain
Translate complex datasets into clear, actionable recommendations for both technical and non-technical stakeholders
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Build dashboards to monitor system and business performance
Must-Have Skills
Building data pipelines and dashboards
Implementing and deploying ML models
Strong dataset analysis and ability to provide actionable insights
Excellent communication skills and ability to work with business partners across all levels
Active participation in team discussions and solutioning
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Requirements
BS/MS in Computer Science or equivalent experience
Experience with big data tools: Spark, Hadoop
Strong knowledge of databases: SQL, NoSQL
Good understanding of machine learning applications
Strong programming skills: SQL, Python, Scala, or Java
Experience solving data science problems and deploying models into production for evaluation
Strong analytical skills in large dataset analysis, data mining, segmentation
Data visualization experience (Tableau/Kibana) is a plus
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