Staff Data Scientist @ Cint
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About Cint
Cint is a pioneer in research technology (ResTech) with a programmatic marketplace spanning over 150 countries and nearly 300 million respondents. They help clients gather insights and build business strategies with confidence.
Role Overview
As a Staff Data Scientist, you will design and develop advanced statistical and machine learning solutions for Media Measurement and Data Solutions. You will drive high-impact initiatives, collaborate cross-functionally, and mentor team members while translating business challenges into scalable, data-driven strategies.
Key Responsibilities
- Develop and deploy statistical models, ML algorithms, and analytics solutions.
- Collaborate with teams to design and automate media measurement methodologies.
- Lead research and transition prototypes into scalable solutions.
- Create customer-facing methodology resources and support business teams.
- Manage projects from concept to high-quality delivery independently.
- Mentor team members and serve as a technical leader.
- Communicate insights with compelling visualizations and reports.
Qualifications
Advanced degree in a quantitative field (Ph.D. or Master's) with 7+ years of experience in data science, including 2+ years in media measurement or marketing analytics. Must have strong programming skills in Python, advanced SQL, proficiency with ML libraries, and experience with big data technologies.
Preferred Qualifications & Benefits
- Experience in online survey methodologies.
- Competitive salary, annual bonus, and comprehensive insurance plans.
- 401K matching, unlimited PTO/sick days, remote work options.
- Paid maternity/paternity leave and supportive team culture.
Key skills/competency
Staff Data Scientist, statistical modeling, machine learning, Python, SQL, media measurement, data analysis, big data, mentoring, project management
How to Get Hired at Cint
🎯 Tips for Getting Hired
- Customize your resume: Emphasize data science and ML projects.
- Research Cint: Review their culture, product suite, and industry trends.
- Highlight technical skills: Showcase Python, SQL, and ML frameworks expertise.
- Prepare for interviews: Practice explaining complex methodologies clearly.