Data Scientist

Dreaming big is in our DNA. It’s who we are as a company. It’s our culture. It’s our heritage. And more than ever, it’s our future. A future where we’re always looking forward. Always serving up new ways to meet life’s moments. A future where we keep dreaming bigger. We look for people with passion, talent, and curiosity, and provide them with the teammates, resources and opportunities to unleash their full potential. The power we create together – when we combine your strengths with ours – is unstoppable. Are you ready to join a team that dreams as big as you do?

• Purpose of the role
  

• Key tasks & accountabilities
• Analyze and interpret complex datasets to uncover actionable insights.
• Design, develop, and implement machine learning and deep learning models using tools and frameworks such as Pandas, Scikit-learn, TensorFlow, Keras, PyTorch, etc.
• Collaborate with cross-functional teams to understand business requirements and provide data-driven solutions.
• Create and maintain scalable data pipelines and workflows.
• Use statistical techniques to test hypotheses and validate models.
• Optimize machine learning algorithms for efficiency and scalability.
• Communicate insights and model performance to stakeholders via data visualization and presentations.
• Stay up-to-date with the latest advancements in data science, machine learning, and big data technologies.
• Qualifications, Experience, Skills
  

Level Of Educational Attainment Required

• B. Tech in Computer Science, or Background in Statistics, Economics, Mathematics.
  

Previous Work Experience & Skills Required

• Data Analytics: Proficiency in statistical analysis and deriving insights from data.
• Business Exposure: Experience in building optimization model, Marketing mix model.
• Machine Learning & Deep Learning Frameworks: Strong working knowledge of libraries like Pandas, Scikit-learn, TensorFlow, Keras, and PyTorch.
• Programming: Proficiency in Python and experience using GitHub for version control.
• Databases: Expertise in working with structured and unstructured data using databases.
• Cloud Platforms: Hands-on experience with Azure infrastructure for data storage, Azure DataBricks processing, and deployment.
• Data Visualization: Ability to create compelling visualizations using tools like Matplotlib, Seaborn, or Power BI.
• Complex Datasets: Exposure to working with large and intricate datasets in various domains.
• Version Control: Experience using GitHub for version control, collaboration, and managing repositories effectively