Position: Data Scientist

Organization: Circle K

Location: Haryana

Apply: https://in.linkedin.com/jobs/view/data-scientist-senior-data-scientist-at-circle-k-2828383930?refId=HpKLyeHyYHAjxL0kFdJXQQ%3D%3D&trackingId=aOhvsEaLe7uZv%2BN%2F8gKdlw%3D%3D&trk=public_jobs_similar-jobs

Responsibilities

• Analyse large-scale structured and unstructured data; develop deep-dive analyses and machine learning models in retail, marketing, merchandising, and other areas of the business
• Utilize data mining, statistical and machine learning techniques to derive business value from store, product, operations, financial, and customer transactional data
• Apply multiple algorithms or architectures and recommend the best model with in-depth description to evangelize data-driven business decisions
• Utilize cloud setup to extract processed data for statistical modelling and big data analysis, and visualization tools to represent large sets of time series/cross-sectional data
• Structure hypothesis, build thoughtful analyses, develop underlying data models, and bring clarity to previously undefined problems
• Partner with Data Engineering to build, design and maintain core data infrastructure, pipelines, and data workflows to automate dashboards and analyses
• Articulate complex data science models to business teams and present the insights in easily understandable and innovative formats

Qualifications and experience

• Bachelor’s degree required, preferably with a quantitative focus (Statistics, Business Analytics, Data Science, Math, Economics, etc.)
• Master’s degree preferred (MBA/MS Computer Science/M.Tech Computer Science, etc.)
• Relevant working experience in a data science/advanced analytics role
• 2 – 4 years for Data Scientist
• 4 – 6 years for Sr. Data Scientist
• Knowledge of Functional Analytics (Supply chain analytics, Marketing Analytics, Customer Analytics)
• Knowledge and ability to conduct statistical modelling using Analytical tools (R, Python, KNIME, etc.) and use big data technologies
• Knowledge of business intelligence & reporting (Power BI, Tableau, Alteryx, etc.)
• Knowledge of Enterprise reporting systems, relational (MySQL, Microsoft SQL Server etc.), non-relational database management systems and Data Engineering tools
• Knowledge and ability to use Big data technologies (Hadoop, Spark, Kafka, Presto etc) and Cloud computing services in Azure/AWS/GCP for data engineering, ML Ops
• Ability to delivery, strong disposition towards business and strong interpersonal communication
• Individual must be organized, dependable, able to multi-task and manage priorities, display initiative, and must have the ability to work independently in a demanding, fast-paced environment