Karkidi
Senior Decision Support Data Scientist
Karkidi, Cupertino, California, United States, 95014
As a Data Scientist in our organization, you will engage in comprehensive statistical analysis and employ machine learning to generate predictive insights that drive business decision-making. Your role includes detailed analysis of complex datasets to discover trends and forecast outcomes, which will shape strategic initiatives. Working in tandem with our data engineering team, you'll aim to bolster our data infrastructure, enabling sophisticated predictive modelling. A crucial part of your job will be to not only articulate these predictive insights to senior leadership with clarity but also to operationalise these models, ensuring they are integrated effectively into business processes for real-world applications. Additionally, you are expected to continuously refine our analytical methodologies to keep pace with the evolving landscape of predictive analytics technology.Key Qualifications7+ years of practical experience in a data science role, with experience in implementing large AI/ML projects.Skilled in the use of statistical tools and programming (including Python, SQL).Proven experience with machine learning libraries and frameworks.Strong understanding of data structures and algorithms, as well as database management systems.Excellent problem-solving abilities and experience in hypothesis-driven statistical testing.Proven track record in operationalising models and integration into business processesExperience with Operations Research and optimisation techniques is a plus.Strong knowledge of supply chain processes including demand planning, inventory management, and logistics preferredDemonstrated skill in data visualisation and communication tools (e.g., Tableau).Ability to translate complex data insights into actionable business strategies.Exceptional communication and collaboration skills, with a track record of successful cross-functional collaboration.Education & ExperienceMaster’s degree in Data Science, Statistics, Computer Science, or a related field; Ph.D. preferred.
#J-18808-Ljbffr
#J-18808-Ljbffr