Data Science Consultant
- Ability to understand business goals and translate them into Machine Learning use cases and model design
- Understanding and applying clustering/sampling techniques to design
- Grow your understanding of the multi-channel marketing optimization problem space
- Performing exploratory data analysis to understand relationships, opportunities to influence outcomes and how to attribute cross channel outcomes
- Being able to quickly iterate over common feature transformation and model types in order to find the best predictive models
- Being able to interpret the models that are being generated
- Developing proofs of concept to verify your ideas
- Closing the loop to make sure that the proposed solution is performing as it should and is correctly understood by clients
- Working closely with clients throughout
- A Bachelor's in a quantitative field (engineering, mathematics, physics, machine learning, statistics or computer science) are the ideal candidates.
- At least 2+ years of industry experience outside of academia
- Ability to travel 30%, on average, based on the work you do and the client and industries/sectors you serve
- Must be legally authorized to work in the United States without the need for employer sponsorship now or at any time in the future
- A Master's in a quantitative field (engineering, mathematics, physics, machine learning, statistics or computer science) are the ideal candidates.
- Good problem decomposition skills and autonomy when faced with solving data problems
- Experience manipulating large marketing data sets and performing ETL
- Excellent hands-on knowledge of modeling approaches such as Boosted Trees, Logistic regression, Classification Techniques, Unsupervised models, LLM, and experimental design
- Experience with large data sets generated in the Ad Tech or Marketing technology spaces
- Excellent verbal and written communication skills are required. Candidates must be proficient in conveying complex data insights in an accessible manner to a non-technical audience, including those outside the data science department. This entails adeptness in tailoring messages effectively and choosing appropriate visual aids to facilitate understanding.
- Proficiency in high level scripting language, such as Python or R
- Understanding of the strategic application of data science methodologies in driving valuable business outcomes for large enterprises
- If you have code in the open domain (for example GitHub) or have written about AI/DS please share this with us
- Experience with Deep Learning architectures and/or Reinforcement Learning
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