Senior Data Scientist - Media Measurement & ML Leader

Cint; Stockholms kommun; On-site; GBP 70,000 - 110,000; Full time

Job summary

Cint is seeking a Senior Data Scientist to sit at the intersection of product, engineering, and advanced analytics. You will architect statistical methodologies and machine learning codebases powering our Media Measurement products, translating raw global data into strategic insights that drive the ResTech industry forward.

You will lead research, discovery, and end-to-end development of models, analyze massive datasets, and collaborate with engineering and product teams to ensure scalable

Qualifications

• Masters degree or equivalent in Statistics, Quantitative Sciences, Data Science or a related field.
• At least 5 years in a data science role, preferably in market research or advertising analytics.
• Ability to independently manipulate and interpret large data sources.

Responsibilities

• Lead research, discovery, and development phases for new and existing statistical models for media measurement.
• Plan, develop, and maintain data science projects end to end with minimal supervision.
• Analyze large, complex datasets to inform product strategy.
• Collaborate with cross-functional engineering and product teams on model design and implementation.
• Develop, validate, and maintain statistical and machine learning models.
• Communicate findings through clear visualizations and presentations for technical and non-technical stakeholders.

Skills

Python for stats

Statistical analysis

Machine learning

SQL queries

Big data

Data visualization

Education

Masters degree

Tools

Spark

Job description

Cint is seeking a Senior Data Scientist to sit at the intersection of product, engineering, and advanced analytics. You will architect statistical methodologies and machine learning codebases powering our Media Measurement products, translating raw global data into strategic insights that drive the ResTech industry forward.

You will lead research, discovery, and end-to-end development of models, analyze massive datasets, and collaborate with engineering and product teams to ensure scalable