Senior Data Scientist - ML, Python

Job Summary The Senior Data Scientist plays a crucial role in transforming unstructured big data into actionable insights through advanced algorithms and innovative data models. This position is essential for developing strategies that enhance client service delivery and product optimization, using cutting-edge machine learning tools and techniques to drive data-driven decision-making within the organization.

Key Responsibilities

1. Design and implement advanced machine learning algorithms using TensorFlow and PyTorch to extract insights from large datasets, delivering customized analytical reports tailored to the needs of colleagues, clients, and stakeholders.
2. Leverage Python and SQL to develop and optimize data models that address specific organizational challenges, ensuring effective integration and management of data.
3. Analyze and mine large datasets to identify trends and patterns, utilizing advanced analytics techniques to interpret findings and provide actionable recommendations based on experimental results.
4. Collaborate with cross-functional teams to identify opportunities for utilizing data insights to formulate strategic business solutions that enhance operational efficiency and product offerings.
5. Create comprehensive visualizations and reports using data visualization tools to communicate complex analysis and results clearly, enabling informed decision-making for customers and stakeholders.

Skill Requirements Skill Matrix DS/ML (E2Band)

• Years of Experience: TEX: 6 yrs; REX: 5 yrs
• Location: Pan India or any constraint - Also mention location for physical attendance: Noida, Bangalore, Hyd, Chennai
• Project Type: Dev
• Team Handling / Individual Contributor: Both
• Shift Involved: No
• Customer Interview Involved: No
• Sell Rate: NA
• Notice Period:
  • P1: 0-30 days
  • P2: 30-45 days
  • P3: 45-90 days

Skill Mandatory Proficiency Level (1-5)

• Machine Learning & NLP: Yes (5)
• Python: Yes (5)
• Natural Language Processing (NLP): Yes (5)
• Machine Learning Model Evaluation: Yes (5)
• Kafka, Apache Spark: Yes (5)
• NumPy, pandas, scikit-learn, TensorFlow, PyTorch, XGBoost, LightGBM, NLTK, SpaCy, StatsModels, Cross-validation, ROC/AUC, Precision/Recall, F1-score, Confusion Matrix, Supervised/Unsupervised Learning, Deep Learning, Time Series, Reinforcement Learning, Hadoop, Apache Kafka, Apache Airflow: Good to Have (4)

Other Requirements

1. Optional but valuable certifications: Certified Data Scientist (CDS), TensorFlow Developer Certificate, or Professional Data Engineer Certification.