Quad Graphics was founded in 1971 by Harry V. Quadracci, who dreamed of a company where employees and management worked together as partners. He established the company in an abandoned factory in Pewaukee, Wisconsin.

Its first press, the "America IV," was crucial during the difficult early years. In 1979, the company achieved a major breakthrough by securing a contract to print Newsweek magazine, which fueled its growth.

Over time, Quad Graphics evolved into a global marketing company, offering comprehensive solutions for brands such as Adidas, Chevrolet, and Toyota, among many others. Its focus on innovation and transformation has been key to its success.

As a Data Scientist on Quad's Insights and Analytics team, you will play a pivotal role in driving the effectiveness of media campaigns through advanced data analysis. You will develop, evaluate, and refine media effectiveness models to enhance our clients' media strategies. Your role involves translating complex data insights into actionable recommendations and presenting these findings to internal team members and perhaps clients to support media investment decisions.

Key Responsibilities:

• Model Development: Build, evaluate, and refine statistical and machine learning models to assess and improve media effectiveness. Develop, contribute to, or edit existing algorithms and data pipelines to support media planning and optimization.
• Data Analysis: Conduct thorough analyses of media performance data, including engagement metrics, conversion rates, and impression volumes and costs. Identify trends, patterns, and insights to inform media strategy.
• Insights Generation: Translate complex data findings into clear, actionable insights. Prepare detailed reports and visualizations that communicate the impact and effectiveness of media strategies to clients.
• Continuous Improvement: Constantly seek ways to improve processes and algorithms. Stay updated with publicly available whitepapers and webinars in the media performance measurement industry. Propose, discuss and implement improvements to existing models and processes

Job Requirements:

Education:

• Bachelor's degree in Data Science, Statistics, Computer Science, Mathematics, or a related field. A Master's degree or higher is preferred.

Experience:

• Minimum of 3-6 years of experience in data science or analytics, with a focus on media effectiveness, marketing analytics, or related areas.
• Experience working in an agency or client-facing role is a plus.

Certificates, Licenses, Registrations:

• Relevant certifications such as Certified Analytics Professional (CAP), Google Analytics Individual Qualification (GAIQ), or equivalent are advantageous.

Knowledge, Skills and Abilities:

• · ADVANCED ENGLISH
• Proven experience in data science, particularly in building and deploying predictive, explanatory, or decomposition models.
• Technical understanding of time-series regression techniques and Bayesian models.
• Ability to write analytic code in Python within a Snowflake environment.
• Highly adept at writing SQL.
• Strong proficiency in statistical analysis and machine learning techniques.
• Experience with data visualization tools and techniques for effective communication of insights.
• Excellent problem-solving skills and attention to detail.
• Strong verbal and written communication skills, with the ability to present complex data in a clear and understandable manner.
• Ability to work independently and as part of a collaborative team.
• Technical Skills: Proficiency in programming languages such as Python or R. Experience with data manipulation and analysis libraries (e.g., Pandas, NumPy) and machine learning frameworks (e.g., Scikit-learn, TensorFlow).
• Data Tools: Expertise in SQL for querying databases, and familiarity with data visualization tools such as Tableau, Power BI, or similar.

We Offer:

• Salary: $35,000- 43,00MXN per month.
• PERMANENT REMOTE WORK
• Grocery vouchers.
• Life insurance.
• Discounted cafeteria service.
• Salary increases.
• Free parking.
• Free uniforms.
• 
  

Work Schedule: Monday to Friday