Machine Learning Scientist II - Performance Marketing
Are you a data-driven and innovative individual with a passion for performance marketing? Do you have a strong background in machine learning and data analysis? TripAdvisor is seeking a Machine Learning Scientist II to join our dynamic team and drive our performance marketing strategies to the next level. In this role, you will have the opportunity to leverage cutting-edge technologies and work with large datasets to optimize and improve our marketing campaigns. As a key member of our team, you will have the chance to make a significant impact on the success of our company. We are looking for a highly skilled and motivated individual who thrives in a fast-paced and collaborative environment. If this sounds like you, we would love to hear from you!
- Develop and implement machine learning algorithms to optimize and improve performance marketing strategies.
- Conduct thorough data analysis to identify trends, patterns, and insights that will inform marketing decisions.
- Utilize cutting-edge technologies and tools to analyze large datasets and extract meaningful insights.
- Collaborate with cross-functional teams, including marketing, data science, and engineering, to drive the success of marketing campaigns.
- Stay up-to-date with industry trends and advancements in machine learning and data analysis to continuously improve strategies and processes.
- Communicate results and findings to stakeholders and make recommendations for improvement.
- Take ownership of projects and proactively identify opportunities to drive business growth.
- Work with a sense of urgency and meet tight deadlines in a fast-paced environment.
- Conduct A/B testing and experiments to improve marketing performance and ROI.
- Develop and maintain dashboards and reports to monitor and track key performance metrics.
- Mentor and train junior team members on machine learning techniques and best practices.
- Continuously seek out new ways to optimize and improve performance marketing efforts.
Advanced Knowledge Of Machine Learning Algorithms And Techniques: A Machine Learning Scientist Ii - Performance Marketing At Tripadvisor Must Possess A Strong Understanding Of Various Machine Learning Algorithms And Techniques Such As Regression, Classification, Clustering, Deep Learning, And Reinforcement Learning.
Expertise In Data Analysis And Modeling: This Role Requires The Ability To Analyze Large And Complex Datasets, Identify Patterns And Trends, And Develop Statistical Models To Optimize Performance Marketing Strategies.
Experience With Big Data Tools And Technologies: Proficiency In Working With Big Data Tools And Technologies Such As Hadoop, Spark, And Sql Is Essential For This Role, As The Machine Learning Scientist Ii Will Be Responsible For Handling And Processing Large Volumes Of Data.
Strong Programming Skills: The Ideal Candidate Should Have A Strong Proficiency In Programming Languages Such As Python, R, And Java, As Well As Experience With Data Manipulation And Visualization Libraries.
Previous Experience In Performance Marketing: A Successful Machine Learning Scientist Ii - Performance Marketing Should Have Prior Experience Working In The Performance Marketing Domain, With A Deep Understanding Of Online Advertising Platforms, Ad Targeting, And Campaign Optimization Techniques.
Data Analysis
Marketing Strategy
Big Data
Deep Learning
A/B testing
Natural language processing
Statistical modeling
Machine learning algorithms
Predictive analytics
Python programming
Campaign optimization
Communication
Conflict Resolution
Emotional Intelligence
Leadership
Time management
creativity
Teamwork
Adaptability
Problem-Solving
Decision-making
According to JobzMall, the average salary range for a Machine Learning Scientist II - Performance Marketing in Lisbon, Portugal is between €50,000-€80,000 per year. This may vary based on the specific company and level of experience of the individual.
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TripAdvisor, Inc. is an American travel and restaurant website company that shows hotel and restaurant reviews, accommodation bookings and other travel-related content.
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