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Data Scientist - Enterprise Functions

Circle K

Support Office IndiaFull-timePosted 5 days agoStill listed 4 days ago

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At a glance

Compensation
No compensation found
Location
Support Office India
Schedule
Full-time
Work Authorization
Not specified

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Requirements

Credentials this posting asks for.

Bachelor's degree

Job overview

Circle K India Data & Analytics team seeks a Data Scientist or Senior Data Scientist to deliver advanced analytics projects, partner with global marketing, merchandising, technology and business units, and develop machine learning models and data‑driven insights.

Skills & qualifications

RequiredNice to have

Skills

PythonRKNIMEMLflowDVCDockerPyTorchTensorFlowPandasScikit‑LearnAWSAzureGCPHadoopSparkMySQLMicrosoft SQL ServerMongoDBDynamoDBPower BITableauAlteryxMicrosoft ExcelMachine LearningStatistical ModelingData MiningBig DataBusiness IntelligenceAnalyticsExperimental DesignDelivery ExcellenceBusiness DispositionSocial IntelligenceInnovation and Agility

Qualifications

Bachelor’s DegreeMaster’s Degree3 - 4 Years for Data ScientistRelevant Working Experience in a Data Science/Advanced Analytics Role

Full job description

Job Description Alimentation Couche-Tard Inc., (ACT) is a global Fortune 200 company. A leader in the convenience store and fuel space, it has footprint across 31 countries and territories. Circle K India Data & Analytics team is an integral part of ACT’s Global Data & Analytics Team, and the Data Scientist/Senior Data Scientist will be a key player on this team that will help grow analytics globally at ACT. The hired candidate will partner with multiple departments, including Global Marketing, Merchandising, Global Technology, and Business Units.

About the role The incumbent will be responsible for delivering advanced analytics projects that drive business results including interpreting business, selecting the appropriate methodology, data cleaning, exploratory data analysis, model building, and creation of polished deliverables.

Roles & Responsibilities Analytics & Strategy

  • 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

Operational Excellence

  • Follow industry standards in coding solutions and follow programming life cycle to ensure standard practices across the project

  • 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.

Stakeholder Engagement

  • Working collaboratively across multiple sets of stakeholders – Business functions, Data Engineers, Data Visualization experts to deliver on project deliverables

  • Articulate complex data science models to business teams and present the insights in easily understandable and innovative formats

Job Requirements Education

  • 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 Experience

  • 3 - 4 years for Data Scientist

  • Relevant working experience in a data science/advanced analytics role

Behavioural Skills

  • Delivery Excellence

  • Business disposition

  • Social intelligence

  • Innovation and agility

Knowledge

  • Functional Analytics (Supply chain analytics, Marketing Analytics, Customer Analytics, etc.)

  • Statistical modelling using Analytical tools (R, Python, KNIME, etc.)

  • Knowledge of statistics and experimental design (A/B testing, hypothesis testing, causal inference)

  • Practical experience building scalable ML models, feature engineering, model evaluation metrics, and statistical inference.

  • Practical experience deploying models using MLOps tools and practices (e.g., MLflow, DVC, Docker, etc.)

  • Strong coding proficiency in Python (Pandas, Scikit-learn, PyTorch/TensorFlow, etc.)

  • Big data technologies & framework (AWS, Azure, GCP, Hadoop, Spark, etc.)

  • Enterprise reporting systems, relational (MySQL, Microsoft SQL Server etc.), non-relational (MongoDB, DynamoDB) database management systems and Data Engineering tools

  • Business intelligence & reporting (Power BI, Tableau, Alteryx, etc.)

  • Microsoft Office applications (MS Excel, etc.)

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