Data Scientist – Python, ML & Predictive Modeling

Data Scientist – Python, ML \& Predictive Modeling

Duration: 12 months

Work Model: 100% Remote

Programming \& Tools

• Strong proficiency in Python (NumPy, Pandas, Scikit-learn, TensorFlow/PyTorch).
• Working knowledge of statistical analysis and modeling.
• Experience with Jupyter Notebooks, RStudio, and data visualization tools.
• Familiarity with SQL and data querying.

Machine Learning \& AI

• Solid understanding of supervised and unsupervised machine learning algorithms.
• Hands-on experience with:

+ Regression (Linear, Logistic) + Classification (Decision Trees, Random Forests, SVM) + Clustering (K-Means, Hierarchical)

• Experience with deep learning frameworks such as TensorFlow and PyTorch is a plus.

Predictive Modeling

• Proven experience in predictive modeling and forecasting.
• Ability to build, validate, and deploy predictive models.
• Strong understanding of:

+ Feature engineering + Model evaluation techniques (ROC, Precision/Recall, Cross-Validation)

• Experience working with real-world datasets to derive actionable insights.

Statistics \& Data Analysis

• Strong foundation in statistics and probability.
• Experience with hypothesis testing, regression analysis, and statistical modeling.
• Proficiency in data cleaning, transformation, and exploratory data analysis (EDA).

Data \& Deployment (Preferred)

• Experience with cloud platforms such as AWS, Azure, or GCP.
• Familiarity with Docker and containerization is a plus.
• Exposure to MLOps practices and CI/CD for machine learning models.

Soft Skills

• Strong analytical and problem-solving skills.
• Ability to translate business problems into data-driven solutions.
• Effective communication and storytelling with data.
• Collaborative mindset with cross-functional teams.

Nice-to-Have

• Experience with big data technologies such as Spark and Hadoop.
• Exposure to NLP, computer vision, or time-series forecasting.
• Knowledge of model deployment APIs such as Flask and FastAPI.