Data Scientist

Data Scientist at Tata Tele Business Services

This Data Scientist role at Tata Tele Business Services, within the AI Centre of Excellence (CoE), focuses on accelerating AI-driven transformation and innovation across the enterprise. You will be instrumental in designing scalable AI solutions, enabling predictive insights, and fostering AI adoption across various business units, contributing significantly to business impact through strategic alignment and execution.

Position Details

• Position Title: Data Scientist – AI Centre of Excellence (CoE)
• Reporting To: Head – AI CoE
• Location: Any (Remote/Hybrid options available)
• Industry: Experience in Telecom & Cloud Services preferred.

Qualifications

• Bachelors/Masters in a quantitative discipline (Computer science, Statistics, Econometrics, Mathematics, Engineering, and Science).
• 7+ years in analytics overall, including at least 3+ years in Gen AI, AI/ML solution delivery, analytics-led consulting, or change management.
• Proven track record in delivering Gen AI, AI/ML solutions at-scale and data-driven decision making at-scale.
• Deep understanding of AI governance, ML Ops, and responsible AI practices.
• Strong leadership and stakeholder management skills.
• Excellent communication and change-management capabilities.
• Familiarity with telecom BSS/OSS or cloud platforms is a plus.

Job Summary

The incumbent will serve as a senior individual contributor within the AI CoE Team, specializing in Predictive Analytics, Digital Analytics, Data Sciences, and Insights & Experimentation. Reporting to the Head – AI CoE, this role involves leading enterprise-wide AI initiatives by designing scalable solutions, enabling predictive insights, and fostering AI adoption across diverse business units. You will work on multiple initiatives across various departments, leveraging both traditional and big data, while closely partnering with stakeholders to translate complex business challenges into impactful AI-driven outcomes and ensure successful adoption.

Key Responsibilities

• Apply Advanced ML Algorithms and Statistics: Regression, Simulation, Scenario Analysis, Time Series Modelling, Classification (Logistic Regression, Decision Trees, SVM, KNN, Naive Bayes), Clustering (K-Means, Apriori), Ensemble Models (Random Forest, Boosting, Bagging), Neural Networks.
• Demonstrate deep expertise in Python, R, SQL, TensorFlow, PyTorch, Hugging Face, LangChain, LLMs, RAG, Vector Databases, Fine-tuning, evaluation, etc.
• Possess a good understanding of Azure and GCP, ETL, data pipelines, and Spark.
• Assess the accuracy of new data sources and data gathering techniques.
• Perform Exploratory Data Analysis and detailed analysis of business problems and technical environments in designing solutions.
• Apply Supervised, Unsupervised, Reinforcement Learning, and Deep Learning algorithms.
• Deliver Proof of Concepts (POCs) in 6-8 weeks with high accuracy (90%+) and demonstrate quick outcomes.
• Document use cases, solutions, and recommendations.
• Work analytically in a problem-solving environment and thrive in a fast-paced agile development environment.
• Coordinate with different functional teams to implement models and monitor outcomes.
• Collaborate with stakeholders across the organization (Operations, Products, Sales, Marketing, HR, Finance) to identify opportunities for leveraging organizational data and applying Predictive Modelling techniques to gain insights.
• Assist program and project managers in the design, planning, and governance of implementing Data Science solutions.

Objectives

• Accelerate AI-driven transformation and innovation.
• Maximize ROI from AI investments through strategic alignment and execution.
• Promote widespread AI adoption across business units.
• Ensure responsible, explainable, and secure AI usage.

Key Result Areas (KRAs)

• Business Impact (Revenue, EBIDTA, Cost) improvement through application of AI, Gen AI, AI/ML. Aim for at least 3 such applications per quarter.
• Time-to-market for AI solutions.
• AI adoption rate and cross-functional engagement, measured by Business unit NPS.
• Accuracy, reliability, and relevance of deployed models. Achieve 20% reduction in operational cost via AI-driven automation.
• Model deployment cycle time and cost savings achieved.
• Compliance with AI governance and ethical standards.

Expected Outcomes

• Rapid POCs / POTs with application of AI.
• Scalable and reusable AI solutions across the enterprise.
• Improved decision-making and operational efficiency.
• Strong AI governance and minimized risk exposure.

Key Competencies

• Product Thinking, Problem-solving & Business Value Orientation.
• Technical Curiosity & Applied AI Knowledge.
• Agile Delivery & Stakeholder Management.
• Cross-functional Collaboration.
• Data Storytelling & Influential Communication.
• Change Management & Adoption Leadership.
• Regulatory Awareness & Ethical AI Practices.
• Data-Driven Decision Making.

About Tata Tele Business Services

Transforming Businesses through Digitalization

Tata Tele Business Services (TTBS), a proud member of the Tata Group, stands as India’s premier provider of connectivity and communication solutions for businesses. Their extensive portfolio includes services spanning connectivity, collaboration, cloud, security, IoT, and marketing solutions, making TTBS a leader in ICT services for Indian businesses. With an unwavering commitment to customer-centricity and innovation, TTBS consistently earns recognition from both clients and industry peers.

Our People Shape Our Journey Ahead

As India’s leading enabler of digital connectivity and technology solutions, TTBS owes its success to the dedication and passion of its people. The company is committed to attracting the best talent, nurturing their growth, and mentoring them for leadership roles, all while upholding strong ethics and values.

Key skills/competency

• Predictive Analytics
• Generative AI
• Machine Learning
• Deep Learning
• Python
• TensorFlow
• LLMs
• Data Science
• Stakeholder Management
• AI Governance