Manager-Data Scientist

6 days ago

Ahmedabad, India RK HR Management Private Limited Full time
Responsibilities:

Lead a team of 1-3 data scientists working across agile podsLead your team in complex data science projects, working closely with stakeholders to identify opportunities and develop solutions that drive business value.Develop, test, and deploy predictive models using machine learning and statistical techniquesCollaborate with stakeholders to identify opportunities and design solutionsExplore and analyze large datasets to inform business decisionsCreate repeatable, interpretable, and scalable models and statistical productsEngineer new features and test various modeling approaches to develop industry-leading analytics productsContribute to the development of our data science capabilities and best practicesCommunicate complex technical concepts to non-technical stakeholders, including data insights and recommendationsStay up-to-date with industry trends and emerging technologies in data science, making recommendations for how to leverage these advancements to drive business growthCoach and develop your team, driving technical best practices and contributing to their career growth within data science

Requirements:Master’s degree in Data Science, Computer Science, Engineering, or Statistics5+ years of applied experience in data science or related fieldExpertise in implementing ML and AI algorithms in Python and/or RFluency in SQLStrong understanding of machine learning, data wrangling, and exploratory analysisAbility to work collaboratively with stakeholders to deliver high-impact resultsExcellent communication and problem-solving skillsPreferred Qualifications:Prior people management experienceExperience with Big Data technologies such as Snowflake and SparkExperience with cloud-based technologies such as AzureFamiliarity with Agile development methodologiesExperience working in a cross-functional team environmentExpertise with the following modeling methods: Design of Experiments, ANOVA, multivariate regression, discrete and continuous optimization, survival analysis, discrete event simulation

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