Senior Data Scientist

Cint; United States; On-site; USD 160,000 - 220,000; 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 the statistical methodologies and machine learning codebases powering our Media Measurement products, translating raw global data into strategic insights that drive the ResTech industry forward.

Lead the research, discovery, and end-to-end development phases for new and existing models related to media measurement, extract and analyze massive datasets, and

Qualifications

• 5+ years of data science experience, preferably in market research or advertising analytics.
• Strong knowledge of ML techniques and advanced statistics.
• Proficiency in Python and SQL for analytics and modeling.

Responsibilities

• Architect statistical methodologies and ML codebases powering Media Measurement products.
• Lead research, discovery and end-to-end development of ML models for media measurement.
• Extract, manipulate and analyze massive datasets to inform product roadmap and strategy.
• Collaborate with engineering and product teams on model design, deployment and validation.
• Develop, validate and maintain statistical and machine learning models.
• Translate complex statistical outputs into clear visualizations and presentations for diverse audiences.

Skills

Python for ML

SQL querying

Spark big data

Multivariate testing

Stochastic modeling

Tree-based models

Clustering

Regression modeling

Sampling theory

Survey design

Statistics

Predictive modeling

Experimental design

Hypothesis testing

Online surveys

Digital attribution

Education

Master's degree in Statistics

Job description

• As a Senior Data Scientist, you will sit at the intersection of product, engineering, and advanced analytics


• You will architect the statistical methodologies and machine learning codebases that power our Media Measurement products, directly translating raw global data into strategic insights that drive the ResTech industry forward


• Lead the research, discovery, and end to end development phases for new and existing machine learning models relating to media measurement


• Extract, manipulate, and analyze massive datasets to uncover insights that shape and direct our product roadmap


• Partner closely with engineering and product teams to align on the technical design, deployment, and ongoing validation of scalable machine learning models


• Transform complex statistical outputs into compelling visualizations and presentations that resonate with diverse business and technical audiences


• Lead research, discovery, and development phases for new and existing statistical models relating to media measurement


• Plan, develop, and maintain data science projects end to end with minimal supervision


• Analyze large, complex datasets to extract insights that 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


• Conduct ongoing evaluation and validation of internal and external product methodologies


• Communicate findings and statistical recommendations through clear visualizations and presentations for technical and non-technical stakeholders

Strong knowledge of machine learning techniques, such as:

Deep understanding of advanced statistical techniques and concepts, including: Sampling Theory Survey Design Experience in media measurement and digital attribution Clustering Tree-based models and their real-world trade-offs Regression and their real-world trade-offs Ability to manipulate, analyze, and interpret large data sources independently Experience with multivariate testing Stochastic Modeling or Simulation 5 years of experience in a data science capacity, preferably in market research or advertising analytics Proficiency in Python for statistical analysis and machine learning model implementation Working knowledge in the application of statistical and modeling techniques Ability to write and optimize SQL queries Strong analytical skills with a focus on data validation and accuracy Master degree or equivalent in Statistics, Quantitative Sciences, Data Science, Operations Research, or another quantitative field Self-starter capable of carrying out projects end to end with minimal supervision Hypothesis Testing Experimental Design, Regression or Predictive Modeling Experience with predictive modeling Ability to independently research and learn new methods, tools, and techniques Properties of Distributions Experience modeling and quantifying outcomes by linking attitudinal survey data to behavioral purchase data Parametric and Non-Parametric Tests Experience working with big data technologies, such as Spark Experience in online survey methodologies