Data Scientist - Classical ML- 5-9 yrs- Gurgaon
We are seeking a highly motivated Data Scientist specializing in Classical Machine Learning with 5-9 years of experience to join our analytics team. The ideal candidate should have strong expertise in Data Science, Machine Learning, Python, SQL, and Cloud platforms (AWS / Azure / GCP).
This role requires close collaboration with business and technical stakeholders to translate business problems into scalable data science solutions. The candidate will be responsible for developing, implementing, and optimizing classical machine learning models to drive data-driven decision making.
Key Responsibilities
- Engage with business stakeholders to understand requirements, define analytical objectives, and translate them into machine learning solutions.
- Develop, implement, and optimize classical machine learning models for predictive and analytical use cases.
- Perform data extraction, transformation, and analysis using Python and SQL.
- Conduct data preprocessing, feature engineering, and model selection to improve model performance.
- Build and evaluate models using supervised and unsupervised learning techniques.
- Work with large structured and semi-structured datasets to generate actionable insights.
- Deploy and integrate machine learning solutions within cloud environments.
- Monitor model performance and continuously improve models through experimentation and tuning.
- Collaborate with cross-functional teams including product, engineering, and analytics teams.
- Communicate analytical findings and insights to technical and non-technical stakeholders.
Required Skills & Qualifications
- 5-9 years of hands-on experience in Data Science or Machine Learning roles.
- Strong programming expertise in Python (NumPy, Pandas, Scikit-learn, etc.).
- Strong SQL skills for querying and manipulating large datasets.
- Solid understanding of classical machine learning algorithms such as:
- Regression models
- Decision Trees
- Random Forest
- Gradient Boosting (XGBoost / LightGBM)
- Clustering techniques
- Strong understanding of statistics, probability, and model evaluation metrics.
- Experience in data preprocessing, feature engineering, and model validation techniques.
- Familiarity with data visualization and exploratory data analysis techniques.
- Ability to translate business problems into analytical frameworks.
- Strong problem-solving and analytical thinking skills.
Preferred Qualifications
- Experience working with cloud platforms such as AWS, Azure, or GCP.
- Familiarity with ML model deployment and MLOps practices.
- Experience working with big data tools or distributed data processing frameworks.
- Exposure to data visualization tools such as Power BI, Tableau, or similar platforms.
- Experience working in production ML environments.
Key Competencies
- Strong analytical and problem-solving skills
- Business-focused and data-driven mindset
- Excellent communication and presentation skills
