Job Opening For Data Scientist

About the Role:

We are seeking a highly skilled Data Scientist with strong expertise in Classification, Clustering, CLM, Random Forest, and Segmentation techniques. The ideal candidate will be responsible for leveraging advanced analytics, statistical modeling, and machine learning to derive actionable business insights and support data-driven decision-making.

Key Responsibilities:

Design, develop, and implement machine learning and statistical models for business problems related to customer analytics and behavioral insights.

Perform Classification and Clustering analysis to identify meaningful customer groups and predict outcomes.

Apply Random Forest and other ensemble learning algorithms for predictive modeling and optimization.

Develop and maintain Customer Lifecycle Management (CLM) models to improve retention, engagement, and acquisition strategies.

Conduct Segmentation analysis to define and refine target audiences for marketing and product strategies.

Collaborate with business, engineering, and analytics teams to translate data insights into actionable recommendations.

Present analytical findings and visualizations to stakeholders in an easily interpretable format.

Stay updated with emerging technologies and best practices in machine learning and data science.

Required Skills & Qualifications:

Bachelors or Master’s degree in Data Science, Statistics, Computer Science, or related field.

4–8 years of experience in data analytics, statistical modeling, or machine learning.

Strong hands-on experience with Classification, Clustering, Random Forest, and Segmentation techniques.

Proficiency in tools like Python, R, SQL, and ML libraries (e.g., scikit-learn, pandas, NumPy).

Experience with data visualization tools like Power BI, Tableau, or Matplotlib.

Familiarity with Customer Lifecycle Management (CLM) models and marketing analytics.

Excellent analytical, problem-solving, and communication skills.

Good to Have:

Experience with Big Data platforms (Spark, Hadoop).

Knowledge of Deep Learning frameworks (TensorFlow, PyTorch).

Exposure to A/B testing and marketing analytics.