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We are looking for a Machine Learning Engineer/Data Scientist who will be working with big data and applying sophisticated analytics techniques in a lively and stimulating environment. Your insights will be used to improve customer acquisition and engagement, deliver an outstanding product and shopping experience, and better understand customer behavior.
The team's responsibilities span data integration supporting customers and internal business areas and ML deployment. We are looking for a talent with different skills, a passionate technologist dedicated to solving real-world business problems; to lead the excellence of ML/AI engineering practice.
What You'll Do on a Typical DayApply advanced analytic techniques such as machine learning, data mining, and statistical modeling to craft and implement mathematical models and algorithms to solve real-world marketing problems.Apply solid coding skills, strong analytical and innovative thinking, and Artificial Intelligence/ML expertise to quickly learn new domains and turn innovative ideas into working solutions.Use Statistics and Data Science techniques to make decisions based on data.Manipulate large datasets for business insights and drive solutions.Utilize appropriate methods and approaches to develop practical solutions for the business.Structure work, frame issues, and produce analyses that answer complex business questions in a pragmatic approach.Communicate complex analytical topics in a clean & simple way to multiple partners and senior leadership.Have some infrastructure knowledge (AWS, Kubernetes); cost-awareness would be a plus.What We're Looking For5+ years for Bachelor's or equivalent, 3+ years for Master's.Ability to conceptualize business problems and solve them through data analysis.Comfortable with pulling and manipulating data using SQL, PySpark.Good written and oral communication skills, including an ability to communicate across business areas.Ability to increase overall knowledge across the organization.Familiarity with one or more machine learning or statistics tools such as R, Stata, Python, and various libraries for other programming languages.Understand the concepts and steps involved in working with real-world large datasets: from domain-specific problem understanding, data preparation, travel-related data processing, data integration, data structures for ML, data pipelining, data modeling, and AI/ML algorithms; strong data science knowledge and skills.Industry experience on using Statistics and Data Science on real-world large datasets.Knowledge of hands-on practice in Python and R.
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