Back
Remote role and recognizable brand increase applicants, but ML specialization limits broad competition.
Core ML and data engineering skills transfer across industries, though retail marketing analytics adds domain bias.
Requires strong mandatory ML, deep learning, cloud and big-data tooling, so screening will be strict.
Login to See Your Match Score
Create a free account or log in to unlock your CV match score across:
Develop and deploy advanced data science models and algorithms using machine learning and statistical methods to support customer analytics for business growth.
Collaborate with cross-functional teams including GapTech, PDM, and marketing partners to prepare data pipelines and deliver actionable insights.
Own quality and impact of data solutions, sharing responsibility for team outcomes, resources, and compliance with policies.
Proficiency in R, Python, Spark, and SQL, including experience with cloud environments like Azure.
Experience with machine learning and predictive modeling techniques such as logistic regression, decision trees, ANN/CNN, boosted trees, SVM, TensorFlow.
Work Experience Required: Not explicitly mentioned in the JD.
Ability to manipulate large, diverse data sets from multiple sources and develop automated data processing pipelines.
Experienced in building and validating AI/ML models with a proven track record of delivering measurable business impact.
Skilled in both detailed data analysis and summarizing findings to drive actionable business recommendations.
Strong collaborator with cross-functional teams and ability to influence analytics and product roadmaps effectively.