DATA SCIENTIST

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, and 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

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

Exposure to graph theory, time-series analysis, or numerical methods
Experience with real-time data pipelines, GraphQL, SQL, or NoSQL
Experience in scientific computing or simulation modeling

Honesty, integrity, and fairness
Respect for individual ability, creativity, and diversity
Teamwork and open communication
Passion and commitment
Enjoyment of work and life