Revlon is looking to leverage data science and analytics to drive business growth by providing actionable insights and optimizing marketing strategies.
Requirements
- Proficient in Python for data analysis and modeling.
- Strong SQL skills for data manipulation and querying.
- Experience with Nielsen and IRI data is highly desirable.
- Demonstrated experience in building and deploying predictive models using deep learning and machine learning algorithms.
- Knowledge about Generative AI is a plus.
- Knowledge of data visualization tools (Power BI) is a plus.
- Experience with media mix modeling.
Responsibilities
- Oversee the design and execution of data science projects, including predictive modeling, machine learning, and statistical analysis.
- Utilize Python and SQL to manipulate and analyze large datasets.
- Develop and apply media mix models to optimize marketing spend across various channels.
- Generate media insights to inform marketing strategies and measure the effectiveness of media campaigns.
- Maintain familiarity with Nielsen or IRI data, and integrate this information into analyses and models.
- Develop and maintain documentation for data science processes and models.
- Ensure the quality and accuracy of data and analytics deliverables.
Other
- Excellent communication skills to effectively collaborate with cross-functional teams and present findings to stakeholders.
- Communicate complex data findings in a clear and concise manner to non-technical stakeholders.
- Stay current with the latest data science trends, tools, and technologies, and mentor team members to develop their skills.
- Excellent problem-solving skills and attention to detail.
- Strong communication and interpersonal skills, with the ability to present complex data insights to various stakeholders.
- Ability to manage multiple projects and deadlines in a fast-paced environment.
- Bachelor’s or Master’s degree in Data Science, Statistics, Computer Science, or a related field.
- 5+ years of experience in data science and analytics, with at least 2 years in building large scale data science models.
