Senior Data Scientist

Key Responsibilities
Model Development: Design, develop, and deploy machine learning models and statistical algorithms to solve business problems.Data Strategy: Work with large-scale structured and unstructured data to identify patterns, trends, and actionable insights.Business Collaboration: Partner with product managers, engineers, and stakeholders to frame problems, gather requirements, and deliver measurable results.Experimentation & Validation: Design A/B tests and validate model performance using rigorous evaluation metrics.Pipeline Building: Develop and maintain data pipelines and model deployment workflows using tools such as Python, Spark, and SQL.Mentorship: Provide technical guidance and mentorship to junior data scientists and analysts.Reporting & Visualization: Create dashboards and reports using tools like Tableau, Power BI, or Plotly to communicate insights effectively.

Qualifications
Bachelors or Masters degree in Computer Science, Data Science, Statistics, Mathematics, or a related field. PhD is a plus.7+ years of hands-on experience in data science, machine learning, or analytics roles.Strong proficiency in Python (pandas, scikit-learn, NumPy, etc.) and SQL.Experience with cloud platforms (e.g., AWS, GCP, Azure), implementation on-premises and distributed computing tools like Spark.Proven experience in designing and deploying production-grade ML solutions.Excellent understanding of supervised and unsupervised learning, feature engineering, model interpretability, and MLOps practices.Strong communication and stakeholder management skills.Preferred SkillsExperience in a domain such as telecom, enterprise solutions, retail, or financeFamiliarity with deep learning frameworks (TensorFlow, PyTorch).Experience with NLP, computer vision, or time series forecasting.Knowledge of data governance, ethical AI, and responsible data use.

• Linux
• Oracle ODI (Data Integration)
• SQLite