Data Scientist

The ideal candidate's favorite words are learning, data, scale, and agility. You will leverage your strong collaboration skills and ability to extract valuable insights from highly complex data sets to ask the right questions and find the right answers.

Responsibilities

• Design, implement, and update media mix models to find the optimal investment mix across marketing channels.
• Interpret and translate findings from the MMM into actionable business insights.
• Design, implement, and update ML/DL/NLP/GenAI Models. Interpret and translate findings from the built models into actionable business insights.
• Work closely with other data scientists and business intelligence analysts to create deep dive analyses to address questions from stakeholders.
• Support regular share-outs by creating visualizations and delivering presentations as needed.
• Continuously monitor model performance in production via automation and iterate to maintain relevance.
• Experiment with novel methods to improve MMM accuracy and interpretability.
• Validate models through back-testing and evaluation of observed data.
• Deliver data insights at the appropriate level of detail and perform fast follow-up to feedback.

Qualifications

• Bachelor's degree or equivalent experience in quantative field (Statistics, Mathematics, Computer Science, Engineering, etc.)
• You Have: 3 to 5 years experience in Data Science and ML Engineering.
• MS or Ph.D in Statistics/Data Science/Computer Science or related disciplines with specialization in machine learning techniques.
• Knowledge of both supervised and unsupervised machine learning techniques.
• Have full stack experience in data collection, aggregation, analysis, visualization, productionalization, and monitoring of data science products.
• The ability to write robust code in Python and leverage associated machine learning packages.
• Strong in Python coding.
• Experience using Jupyter Notebooks.
• Working experience on one of the cloud platforms Azure/AWS/GCP.
• Familiarity with a variety of statistical models and methods (i.e., causal methods, tree-based algorithms, time series analysis, regression analysis).
• Communicate concisely and persuasively with engineers and product managers.
• Strong detail orientation with a penchant for data accuracy.
• Familiar with version control systems (Git, BitBucket).
• Must successfully pass a background check.

You might also have:

• Digital marketing experience.
• Experience using project management tools like those from Atlassian (JIRA, Confluence).
• Can wrangle data using SQL and Pandas.