
Senior Data Scientist
1 day ago
Role & responsibilities :
- Translate real-world problems into well-structured mathematical/statistical models
- Design and implement algorithms using linear algebra, optimization, and probability theory
- Develop predictive and classification models using ML techniques (e.g., regression, trees, neural networks, clustering)
- Conduct exploratory data analysis and feature engineering on large datasets
- Use hypothesis testing, inferential statistics, and confidence intervals to validate results
- Collaborate with product and engineering teams to integrate models into production pipelines
Required Skills & Competencies :
1. Mathematics & Statistics :
- Strong understanding of Linear Algebra, Multivariable Calculus, Probability & Statistics
- Hands-on experience with statistical inference, hypothesis testing, and confidence intervals
2. Machine Learning & Algorithms :
- Practical knowledge of supervised and unsupervised learning
- Comfortable with algorithms like regression, SVMs, decision trees, clustering
- Understanding of model performance evaluation (F1-score, AUC-ROC, cross-validation, etc.)
3. Technical Skills :
- Proficient in Python (NumPy, Pandas, Scikit-learn, Statsmodels)
- Experience with ML libraries like TensorFlow, PyTorch
- Exposure to Jupyter, Matplotlib/Seaborn, and Git
4. Problem-Solving Mindset :
- Strong analytical and critical thinking
- Ability to convert vague requirements into well-defined problems
- Comfortable dealing with incomplete, noisy, or unstructured data
Good to have :
1. Exposure to graph theory, time-series analysis, or numerical methods
2. Experience with real-time data pipelines, GraphQL, SQL, or NoSQL
3. Experience in scientific computing or simulation modeling
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