Senior Data Scientist

 We seek a Senior Data Scientist with expertise in traditional machine learning techniques, strong mathematical skills, and the ability to develop innovative business solutions. The ideal candidate will have experience applying machine learning models to solve real-world problems, focusing on improving business outcomes through data-driven insights.

Key Responsibilities:

1. Develop and implement machine learning models using traditional techniques such as decision trees, random forests, support vector machines, and logistic regression.
2. Analyze and process large datasets to identify trends, patterns, and insights that can drive business decisions.
3. Collaborate with cross-functional teams to understand business objectives and design ML solutions that meet organizational goals.
4. Validate and fine-tune models to ensure accuracy, scalability, and performance in real-world applications.
5. Use mathematical principles (e.g., statistics, probability, linear algebra) to enhance the effectiveness of models and algorithms.
6. Continuously monitor and optimize machine learning systems for performance, accuracy, and relevance.
7. Document processes, model architectures, and experiment results to communicate with both technical and non-technical stakeholders.

Desired Skills and Qualifications:

• Traditional Machine Learning Expertise: Strong experience with classical ML models like decision trees, k-means clustering, Naive Bayes, SVMs, etc.
• Mathematics and Statistics Proficiency: Solid foundation in mathematics, especially in linear algebra, calculus, probability, and statistics to support the development of accurate models.
• Business Solutioning Skills: Ability to translate business challenges into ML solutions and explain technical outcomes in a business context.
• Data Processing & Analysis: Proficient in data manipulation and feature engineering techniques using tools like Python.
• Programming Skills: Expertise in Python (pandas, scikit-learn, NumPy) , with experience in building and deploying ML models.
• Problem-Solving & Critical Thinking: Strong analytical skills to assess various machine learning algorithms and select the best fit for business problems.
• Communication & Collaboration: Ability to work closely with business stakeholders to understand their needs and convey technical results effectively.
• Experience with ML Tools & Frameworks: Experience using ML libraries such as Scikit-learn, XGBoost, and LightGBM.
• Model Evaluation and Optimization: Familiarity with techniques like cross-validation, grid search, and hyperparameter tuning to improve model accuracy.
• Business Acumen: Understanding of the business domain and the ability to apply ML in areas like customer segmentation, forecasting, and risk assessment.

Preferred Qualifications:

• Bachelor’s or Master’s degree in Computer Science, Data Science, Mathematics, or a related field.
• 3+ years of experience working on machine learning projects, particularly with traditional ML methods.
• Experience with business problem-solving and the ability to create impact through data insights.
• Familiarity with cloud platforms like AWS, Azure, or Google Cloud for ML deployment.