Senior Data Scientist

Skills:

· Python/R- either/or but Python is mostly used

· Statistical background

· AWS

· Tableau

· Azure

· Visualization tools -building out dashboards - will help to redesign

· Data Science analysis

· Data analytics

· statistical analysis

· 5-8+years’ experience-data pipelines

Basic Qualifications

• 6+ years of hands-on experience in machine learning and advanced analytics. Experience in the advertising domain is preferred.
• Solid understanding of Client technologies, mathematics and statistics.
• Proficient with Python, Java, Scala, large scale Client/DL platforms and processing tech stack.
• Passion to understand the ad business and apply accurate research study according to the business scenario, and seek innovation opportunities to enhance business effectiveness.
• Passion for technology, open to interdisciplinary work, and experience in building data-driven services and applications.
• Proven track record of thriving in a fast-paced, data-driven, collaborative and iterative applied research environment is required.

NICE-TO-HAVE

• Experience in digital video advertising or digital marketing domain
• Experience with CTR/CVR model, generative AI
• Experience building and deploying full stack Client pipelines: data extraction, data mining, model training, feature development, testing, and deployment
• Experience engineering big-data solutions using technologies like EMR, S3, Spark, Databricks
• Experience loading and querying cloud-hosted databases such as Snowflake
• Familiarity with automated deployment, AWS infrastructure, Docker or similar containers

Job Type: Full-time

Pay: Up to $130,000.00 per year

Experience level:

• 8 years

Schedule:

• 8 hour shift

Application Question(s):

• This is a Hybrid role based Seattle, WA . Please confirm your current location with zip code,
• This is a fulltime role and we are looking for Green Card and US Citizens. Please confirm your visa status

Experience:

• Senior Data Scientist: 6 years (Preferred)
• Python: 3 years (Preferred)
• data pipelines: 5 years (Preferred)
• AWS: 2 years (Preferred)

Work Location: In person