Job Description:

As a Senior Data Scientist (CL2), you will leverage your advanced expertise to deliver sophisticated data-driven solutions with minimal supervision. You are a natural researcher, continuously curious about advancements in data science and artificial intelligence, and will play a key role in enabling the Data Management and Systems Operations (DSO) department to implement state-of-the-art solutions. Your work will focus on driving real business impact by discovering actionable insights, building cutting-edge machine learning models, and integrating advanced analytics into end-to-end business solutions.

Key Responsibilities:

• Develop advanced machine learning models: Build and deploy models to solve domain-specific problems, incorporating the latest trends in AI/ML (e.g., generative AI, transformers, reinforcement learning).
• Data Exploration: Analyze large datasets to unearth trends, patterns, anomalies, and key business insights, leveraging deep learning and other advanced techniques.
• Collaborate on Data Visualizations: Partner with data analysts and engineers to create impactful visualizations, enabling decision-making through intuitive storytelling.
• Build AI-driven Automation: Integrate prescriptive, predictive, and generative analytics into business workflows, contributing to full-scale automation solutions powered by AI.
• Prototype and Proof of Concept (PoC): Develop PoCs for emerging technologies and AI-driven business solutions (e.g., AI-enabled chatbots, NLP applications, and edge computing).
• Mentor and Guide: Provide high-level consultancy and mentorship to associates and junior data scientists, fostering a culture of innovation and continuous learning.
• Lead AI Adoption Initiatives: Stay abreast of the latest AI/ML advancements (e.g., federated learning, explainable AI) and champion their integration within the organization to maintain a competitive edge.

Required Qualifications:

Education: Bachelor’s or Master’s degree in Statistics, Mathematics, Engineering, Computer Science, or a related field with a strong quantitative focus.

Experience:

• At least 3-5 years of experience in data science, with a proven track record of building and deploying advanced machine learning models.
• Strong proficiency in Python, R, or similar programming languages for data science.
• Experience with big data frameworks (e.g., Hadoop, Spark) and cloud-based platforms (AWS, Google Cloud, or Azure) for scalable solutions.
• Experience with AI/ML platforms such as Amazon SageMaker, Azure Machine Learning, or Cloudera Data Platform.
• Technical Skills: Expertise in data wrangling and using data science libraries such as Scikit-learn, Pandas, NumPy, TensorFlow, Keras, and PyTorch.

Desirable Qualifications:

• AI Experience: Experience in NLP, computer vision, or reinforcement learning would be a strong plus.
• Big Data Expertise: Hands-on experience with streaming data technologies (e.g., Apache Kafka) and real-time analytics.
• Leadership Skills: Previous experience leading a team of data scientists or data analysts is desirable.