- ಅನುಭವ
- 5–7 yrs
- ಸಂಬಳ
- —
- ತೆರೆಯುವಿಕೆಗಳು
- 1
- ಪೋಸ್ಟ್ ಮಾಡಲಾಗಿದೆ
- 3 ಗಂಟೆಗಳು ಹಿಂದೆ
- Work mode
- ಕಚೇರಿಯಲ್ಲಿ
- Eligibility
- Candidates with 5 to 7 years of relevant data science experience who are able to work full-time in Mississauga, Ontario, Canada.
- Resume
- Required to apply
Where you'll work
ಕೆಲಸದ ವಿವರ
Role Summary
Capgemini is hiring a full-time permanent Data Scientist in Mississauga, Ontario, Canada. This position calls for a seasoned professional with 5 to 7 years of experience who can create, build, and release machine learning solutions that scale well in production.
What You Will Do
- Own the full lifecycle of model development, starting with framing the problem and continuing through production rollout.
- Create, test, and refine machine learning models for practical business needs.
- Analyze data, engineer useful features, and assess model quality.
- Plan and run experiments, including A/B tests, to support decision-making.
- Work closely with teams across the business to convert requirements into data science deliverables.
- Maintain strong production performance by improving reliability, scalability, and model stability.
- Streamline data processes and reduce query latency through workflow and performance improvements.
Required Technical Background
The ideal candidate should be highly proficient in Python and advanced SQL, with solid depth in statistical methods and machine learning. Hands-on experience delivering complete data science solutions is essential.
- Strong Python programming skills at an expert level.
- Practical experience with Pandas, NumPy, and SciPy.
- Working knowledge of Scikit-learn and Statsmodels.
- Ability to use Matplotlib and Seaborn for visualization.
- Experience with XGBoost and LightGBM.
- Exposure to TensorFlow and/or PyTorch.
- Advanced SQL skills, including complex joins, CTEs, and window functions.
- Ability to improve query efficiency and tune performance.
- Experience with data modeling and schema design.
- Strong understanding of statistics, hypothesis testing, predictive modeling, and feature engineering.
- Experience validating models and improving their performance.
- Knowledge of experimental design and A/B testing.
Nice-to-Have Experience
- Experience working on natural language processing projects.
- Background in time series forecasting.
- Exposure to recommendation systems.
- Familiarity with generative AI or LLM-based applications.
- Experience with MLOps and deployment frameworks.
- Use of Power BI or Tableau for visualization.
- Exposure to cloud ML platforms such as Azure ML, AWS SageMaker, or GCP Vertex AI.