Senior Data Science Engineer
$116,500–$210,100 year
On-site · New York City, New York, United States or Philadelphia, Pennsylvania, United States
Job Summary
Senior Data Science Engineer leading end-to-end machine learning and data-product development. Build scalable data, training, and inference pipelines using distributed processing and cloud technologies. Apply statistical methods, experimentation, and validation to ensure impact. Write production-quality code and contribute to CI/CD and observability. Collaborate across engineering, product, and business teams while leading other engineers and data scientists. Requires expertise in AI/ML, cloud platforms (GCP/AWS), Python and PySpark, and experience with large-scale data systems and data warehousing (BigQuery, Snowflake, Redshift). Strong emphasis on turning analytical insights into scalable, privacy-conscious advertising solutions. 18+ years of age and legally authorized to work in the United States. Travel required.
Required Qualifications
- Bachelor's Degree plus 5 years of related work experience OR Advanced degree with 3 years of related experience (Required)
- 4-7 years experience building and deploying machine learning and deep learning solutions at scale; familiarity with MLOps and DevOps practices and tools. (Required)
- 4-7 years Experience working within big data architecture, modern analytical data platforms, and large-scale data warehousing technologies (e.g. BigQuery, Snowflake, Redshift) (Required)
- 4-7 years Experience working with large-scale distributed data systems and cloud platforms (e.g. SQL, Python, Scala, AWS) (Required)
- 4-7 years Experience solving complex data, machine learning, or algorithmic challenges in production environment using modern engineering practices.(Required)
- Knowledge, Skills and Abilities: Strong background in AI/ML, data structures, statistical modeling, optimization algorithms, big data, and design thinking. Advanced knowledge of cloud-based services (GCP, AWS) and Python, PySpark and related Python libraries (e.g. pandas, scikit-learn, scipy, numpy) for advanced data science tasks.
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