Junior 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?

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About Us

Job Summary

Data Scientist

Statistical modelling, Predictive modelling, Time Series Forecasting

Key Responsibilities

• Develop and Implement Models:
• Design and implement and Maintain time series forecasting models to predict key business metrics.
• Utilize advanced statistical techniques and machine learning algorithms to improve model accuracy.
• Data Analysis and Insight Generation:
• Analyze large and complex datasets to identify trends, patterns, and anomalies.
• Generate actionable insights that inform business strategies and operational improvements.
• Collaborate with Cross-Functional Teams:
• Work closely with deployment and development data scientists, and other stakeholders to understand business needs.
• Communicate Findings:
• Present analysis results and insights to stakeholders in a clear and concise manner.
• Prepare reports, visualizations, and dashboards to communicate data findings.
• Continuous Improvement:
• Monitor model performance and implement enhancements as necessary.
• Stay updated with the latest developments in data science, machine learning, and time series forecasting.
  

Qualifications

• Education:
• Bachelor’s or Master’s degree in Data Science, Statistics, Mathematics, Computer Science, or a related field.
• Experience:
• Proven experience with time series analysis and forecasting techniques is a plus
• Technical Skills:
• Python (Data Structures, Control Flow, OOPs, Modules and Packages, Exception Handling, VENV)
• MLOPs Fundamentals (Model Development, VCS, CI, CD, Serving, Monitoring & Logging, Registry, Data and Model Lineage)
• Experience with machine learning frameworks (e.g., scikit-learn, TensorFlow is a plus).
• Familiarity with data visualization tools (e.g., Power BI, matplotlib, plotly, streamlit).
• Data Analysis Tools - Pandas, Excel (Pivot Tables, Charts, Macros, Conditional Formatting, Shortcuts)
• Insights presentation - Powerpoint
• Version Control System (Git) - Basic Commands, Branching and Merging, Pull Requests & Code Reviews
• Soft Skills:
• Excellent problem-solving and analytical skills.
• Strong communication and presentation abilities.
• Ability to work collaboratively in a team environment.