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data scientist traditional ml

Tata Consultancy Services

<div>
 
 
 Role
 
 - Data Scientist (Traditional ML)
 
 
 
 Experience
 
 - 10 to 15 Years
 
 
 
 Location
 
 - PAN INDIA
 
 
 
 
 
 
 
 
 
 Job description
 
 
 
 
 
 
 Excellent knowledge AI/ML including algorithm development
 
 
 In-depth knowledge in Data (collection, preparation, analysis, visualization)
 
 
 Hands-on experience in Python based development
 
 
 Hands-on experience on multi cloud (Azure, AWS and GCP)
 
 
 Hands on experience AI/ML implementation
 
 
 Hands on experience GenAI and Agentic AI
 
</div>

Data Scientist (Traditional ML)

HSBC

<div>
 
 Some Careers Have More Impact Than Others.
 
 
 
 If you&rsquo;re looking for a career where you can make a real impression, join HSBC and discover how valued you&rsquo;ll be.
 
 
 HSBC is one of the largest banking and financial services organisations in the world, with operations in 62 countries and territories. We aim to be where the growth is, enabling businesses to thrive and economies to prosper, and, ultimately, helping people to fulfil their hopes and realise their ambitions.
 
 
 We are currently seeking an experienced professional to join our team in the role of
 
 Machine Learning Data Scientist
 
 
 
 
 Business: Global Banking &amp; Markets
 
 
 
 
 Principal Responsibilities
 
 
 
 <ul>
 <li>
 The Role Holder will be responsible for leading the data science activities within the project, working with business analysts, data scientists and developers:
 </li>
 <li>
 Reviewing the proof of concept, current state and opportunities to utilise AI/ML in the Trade and Transaction Reporting Controls area.
 </li>
 <li>
 Proposing appropriate AI/ML models and techniques that will best fit with the data domains, volumes, available tools and business priorities.
 </li>
 <li>
 Using a range of AI/ML techniques and programming languages to transform data, analyse data and identify potential data quality issues.
 </li>
 <li>
 Building scalable machine learning pipelines and using feature engineering and optimisation methods to improve data set performance.
 </li>
 <li>
 Working with technology to integrate and separate data feeds to map, produce, transform and test new machine learning pipelines.
 </li>
 <li>
 Work with Business Partners to clarify problems/opportunities and propose solutions underpinned by strong data analysis of underlying controls and processes
 </li>
 <li>
 To understand and operate within HSBC&rsquo;s AI/ML governance and procedures
 
 
 </li>
 </ul>
 
 Requirements
 
 
 
 <ul>
 <li>
 Relevant Bachelor's or equivalent University degree in AI/Machine Learning.
 </li>
 <li>
 Evidence of a successful track record of leading delivery of AI/ML solutions within Markets/Investment Banks.
 </li>
 <li>
 Strong data scientist with experience in anomaly detection techniques, particularly in the trade data domain.
 </li>
 <li>
 Awareness of a broad range of ML techniques.
 </li>
 <li>
 Google Vertex an advantage.
 </li>
 <li>
 Good overall understanding of Primary Trading systems, trading products and front to back trade lifecycle flows.
 </li>
 <li>
 Demonstrated experience working with SMEs and key stakeholders to support understanding of the problem/data.
 </li>
 <li>
 Be capable of communicating complex data science/AI/ML techniques and processes to business users and SMEs
 </li>
 <li>
 Drive and resilience as must be comfortable working in rapidly changing and ambiguous situations.
 </li>
 <li>
 Hands on ability to perform data analysis to drive business insights and decision making.
 </li>
 <li>
 Proactive and willing to use own initiative to resolve issues.
 </li>
 <li>
 Excellent communication and interpersonal skills.
 </li>
 <li>
 Structured and methodical in planning their own book of work, delivery of artefacts, managing multiple competing priorities and setting expectations with stakeholders.
 
 
 </li>
 </ul>
 
 You&rsquo;ll achieve more at HSBC
 
 
 
 HSBC is an equal opportunity employer committed to building a culture where all employees are valued, respected and opinions count. We take pride in providing a workplace that fosters continuous professional development, flexible working and, opportunities to grow within an inclusive and diverse environment. We encourage applications from all suitably qualified persons irrespective of, but not limited to, their gender or genetic information, sexual orientation, ethnicity, religion, social status, medical care leave requirements, political affiliation, people with disabilities, color, national origin, veteran status, etc., We consider all applications based on merit and suitability to the role.&rdquo;
 
 
 Personal data held by the Bank relating to employment applications will be used in accordance with our Privacy Statement, which is available on our website.
 
 
 <ul>
 <li>
 Issued By HSBC Electronic Data Processing (India) Private LTD***
 </li>
 </ul>
</div>

Machine Learning Data Scientist (Blr)

PwC Acceleration Center India

<div>
 
 PwC AC is hiring for Data scientist
 
 
 Apply and get a chance to work with one of the Big4 companies #PwC AC.
 
 
 
 
 
 
 Job Tit
 
 le
 
 :
 
 Data scientist
 
 
 
 Years of Experienc
 
 e: 3-7 years
 
 
 
 Shift Timin
 
 gs: 11AM-8PM
 
 
 
 Qualificati
 
 on: Graduate and above(Full time)
 
 
 
 
 
 
 About PwC CTIO &ndash; AI Engineering
 
 
 
 PwC&rsquo;s
 
 Commercial Technology and Innovation Office (CTIO)
 
 is at the forefront of emerging technology, focused on building transformative AI-powered products and driving enterprise innovation. The
 
 AI Engineering
 
 team within CTIO is dedicated to researching, developing, and operationalizing cutting-edge technologies such as Generative AI, Large Language Models (LLMs), AI Agents, and more. Our mission is to continuously explore what's next&mdash;enabling business transformation through scalable AI/ML solutions while remaining grounded in research, experimentation, and engineering excellence.
 
 
 
 
 
 
 Role Overview
 
 
 
 We are seeking a
 
 Senior Associate &ndash; Data Science/ML/DL/GenAI
 
 to join our high-impact, entrepreneurial team. This individual will play a key role in designing and delivering scalable AI applications, conducting applied research in GenAI and deep learning, and contributing to the team&rsquo;s innovation agenda. This is a hands-on, technical role ideal for professionals passionate about AI-driven transformation.
 
 
 
 
 
 
 Key Responsibilities
 
 
 <ul>
 <li>
 Design, develop, and deploy machine learning, deep learning, and Generative AI solutions tailored to business use cases.
 </li>
 <li>
 Build scalable pipelines using Python (and frameworks such as Flask/FastAPI) to operationalize data science models in production environments.
 </li>
 <li>
 Prototype and implement solutions using state-of-the-art LLM frameworks such as LangChain, LlamaIndex, LangGraph, or similar. Also developing applications in streamlit/chainlit for demo purposes.
 </li>
 <li>
 Design advanced prompts and develop agentic LLM applications that autonomously interact with tools and APIs.
 </li>
 <li>
 Fine-tune and pre-train LLMs (HuggingFace and similar libraries) to align with business objectives.
 </li>
 <li>
 Collaborate in a cross-functional setup with ML engineers, architects, and product teams to co-develop AI solutions.
 </li>
 <li>
 Conduct R&amp;D in NLP, CV, and multi-modal tasks, and evaluate model performance with production-grade metrics.
 </li>
 <li>
 Stay current with AI research and industry trends; continuously upskill to integrate the latest tools and methods into the team&rsquo;s work.
 </li>
 </ul>
 
 
 
 
 
 Required Skills &amp; Experience
 
 
 <ul>
 <li>
 
 3 to 7 years
 
 of experience in Data Science/ML/AI roles.
 </li>
 <li>
 Bachelor&rsquo;s degree in Computer Science, Engineering, or equivalent technical discipline (BE/BTech/MCA).
 </li>
 <li>
 Proficiency in Python and related data science libraries: Pandas, NumPy, SciPy, Scikit-learn, TensorFlow, PyTorch, Keras, etc.
 </li>
 <li>
 Hands-on experience with
 
 Generative AI
 
 , including prompt engineering, LLM fine-tuning, and deployment.
 </li>
 <li>
 Experience with Agentic LLMs and task orchestration using tools like LangGraph or AutoGPT-like flows.
 </li>
 <li>
 Strong knowledge of NLP techniques, transformer architectures, and text analysis.
 </li>
 <li>
 Proven experience working with cloud platforms (preferably Azure; AWS/GCP also considered).
 </li>
 <li>
 Understanding of production-level AI systems including CI/CD, model monitoring, and cloud-native architecture. (Need not develop from scratch)
 </li>
 <li>
 Familiarity with ML algorithms: XGBoost, GBM, k-NN, SVM, Decision Forests, Naive Bayes, Neural Networks, etc.
 </li>
 <li>
 Exposure to deploying AI models via APIs and integration into larger data ecosystems.
 </li>
 <li>
 Strong understanding of model operationalization and lifecycle management.
 </li>
 </ul>
 
 
 
 
 
 Good to Have
 
 
 <ul>
 <li>
 Experience with Docker, Kubernetes, and containerized deployments for ML workloads.
 </li>
 <li>
 Use of MLOps tooling and pipelines (e.g., MLflow, Azure ML, SageMaker, etc.).
 </li>
 <li>
 Experience in full-stack AI applications, including visualization (e.g., PowerBI, D3.js).
 </li>
 <li>
 Demonstrated track record of delivering AI-driven solutions as part of large-scale systems.
 </li>
 </ul>
 
 
 
 
 
 Soft Skills &amp; Team Expectations
 
 
 <ul>
 <li>
 Strong written and verbal communication; able to explain complex models to business stakeholders.
 </li>
 <li>
 Ability to independently document work, manage requirements, and self-drive technical discovery.
 </li>
 <li>
 Desire to innovate, improve, and automate existing processes and solutions.
 </li>
 <li>
 Active contributor to team knowledge sharing, technical forums, and innovation drives.
 </li>
 <li>
 Strong interpersonal skills to build relationships across cross-functional teams.
 </li>
 <li>
 A mindset of continuous learning and technical curiosity.
 </li>
 </ul>
 
 
 
 
 
 Preferred Certifications
 
 (at least two are preferred)
 
 
 
 <ul>
 <li>
 Certifications in Machine Learning, Deep Learning, or Natural Language Processing.
 </li>
 <li>
 Python programming certifications (e.g., PCEP/PCAP).
 </li>
 <li>
 Cloud certifications (Azure/AWS/GCP) such as Azure AI Engineer, AWS ML Specialty, etc.
 </li>
 </ul>
 
 
 
 
 
 Why Join PwC CTIO?
 
 
 <ul>
 <li>
 Be part of a mission-driven AI innovation team tackling industry-wide transformation challenges.
 </li>
 <li>
 Gain exposure to bleeding-edge GenAI research, rapid prototyping, and product development.
 </li>
 <li>
 Contribute to a diverse portfolio of AI solutions spanning pharma, finance, and core business domains.
 </li>
 <li>
 Operate in a startup-like environment within the safety and structure of a global enterprise.
 </li>
 <li>
 Accelerate your career as a deep tech leader in an AI-first future.
 </li>
 </ul>
</div>

Data Scientist

Tata Communications

<div>
 
 About The Company
 
 
 
 Tata Communications Redefines Connectivity with Innovation and IntelligenceDriving the next level of intelligence powered by Cloud, Mobility, Internet of Things, Collaboration, Security, Media services and Network services, we at Tata Communications are envisaging a New World of Communications
 
 
 
 Team &ndash;
 
 Artificial Intelligence Centre of Excellence
 
 
 
 Role:
 
 Data Scientist
 
 
 
 Location:
 
 Bengaluru
 
 
 
 Job Type:
 
 Full-time
 
 
 
 Experience Level:
 
 1-5 Years
 
 
 
 Position Overview
 
 
 
 We are seeking an experienced Data Scientist with a strong background in Machine Learning, Natural Language Processing (NLP), Generative AI, and Retrieval-Augmented Generation (RAG). The ideal candidate will possess 1 to 5 years of hands-on experience in developing and deploying advanced data-driven solutions. You will play a key role in our AI-CoE team, contributing to cutting-edge projects that drive innovation and business value. A special focus area for this role would be to build AI enabled products that would result in the creation of monetizable product differentiators for Tata Communications products and services.
 
 
 
 Detailed Job Description &amp; Key Responsibilities
 
 
 
 <ul>
 <li>
 Research and implement state-of-the-art ML algorithms and tools to build PoCs and MVPs
 </li>
 <li>
 Develop, Test, and Deploy machine learning models for various business and Telco use cases.
 </li>
 <li>
 Perform data preprocessing, feature engineering and ML/DL model evaluation.
 </li>
 <li>
 Optimize and fine-tune models for performance and scalability.
 </li>
 <li>
 Good understanding of NLP concepts and projects involving entity recognition, text classification, and language modelling like GPT
 </li>
 <li>
 Build and refine RAG models to improve information retrieval and answer generation systems.
 </li>
 <li>
 Integrate RAG methods into existing applications to enhance data accessibility and user experience.
 </li>
 <li>
 Work closely with cross-functional teams including software engineers, product managers, and domain experts.
 </li>
 <li>
 Communicate technical concepts to non-technical stakeholders effectively.
 </li>
 <li>
 Document processes, methodologies, and model development for internal and external stakeholders.
 
 
 </li>
 </ul>
 
 Skills
 
 
 
 <ul>
 <li>
 Bachelor&rsquo;s or master&rsquo;s degree in Computer Science, Data Science, Statistics, Mathematics, or a related field from reputed institutions.
 </li>
 <li>
 Strong knowledge of probability and statistics.
 </li>
 <li>
 Working knowledge of machine learning and deep learning skills.
 </li>
 <li>
 Strong knowledge of programming knowledge &ndash; Python, SQL and commonly used frameworks &amp; tools &ndash; PyTorch, Sci-kit, NumPy, Gen AI tools like langchain/llamaIndex
 </li>
 <li>
 Working knowledge of MLOPs principles and implementing projects with Big Data in batch and streaming mode.
 </li>
 <li>
 Excellent problem-solving skills and a proactive attitude.
 </li>
 <li>
 Strong communication and teamwork abilities.
 </li>
 <li>
 Ability to manage multiple projects and meet deadlines
 </li>
 <li>
 Interview will involve coding tests.
 </li>
 </ul>
</div>

Assistant Manager - Technology & Platform Development

ACL Digital

<div>
 
 Key Responsibilities:
 
 <ul>
 <li>
 Apply advanced forecasting methodologies to estimate sales and revenue for newly launched and pipeline pharmaceutical products (Demand Forecasting good to have skills).
 </li>
 <li>
 Incorporate financial modelling and corporate finance principles into forecasting frameworks to support long-term strategic planning.
 </li>
 <li>
 Develop robust, data-driven models that incorporate market dynamics, patient behaviour, and competitive intelligence to generate accurate and actionable forecasts.
 </li>
 <li>
 Collaborate cross-functionally with marketing, commercial, and research teams to ensure alignment of forecasts with strategic objectives and product positioning.
 </li>
 <li>
 Leverage statistical, machine learning, and deep learning techniques to uncover insights that inform launch strategies and optimize product performance.
 </li>
 <li>
 Partner with key business stakeholders to identify, scope, and execute predictive analytics initiatives that address critical business needs and deliver measurable value.
 </li>
 <li>
 Maintain a strong understanding of the pharmaceutical landscape from financial operations to commercialization To provide objective, data-driven input into strategic decisions.
 </li>
 <li>
 Collaborate within the analytics team, openly sharing knowledge and seeking feedback to enhance the quality and impact of analytical deliverables.
 </li>
 <li>
 Stay current with emerging techniques and tools in predictive analytics, ensuring methodological rigor and adaptability in approach.
 </li>
 <li>
 Work comfortably with varied data sources and types, ensuring seamless integration and analysis across structured and unstructured datasets.
 </li>
 </ul>
 
 
 
 
 
 Requirements:
 
 
 
 
 
 <ul>
 <li>
 Minimum of 5 years of working experience as a Data Scientist in industry.
 </li>
 <li>
 Deep and broad knowledge of Data Science methods and tools including Simulation model building principles, Machine Learning, and best practices:
 </li>
 <li>
 Point Forecasting and Probabilistic Forecasting.
 </li>
 <li>
 Statistical Forecasting: ARIMA, THETA, Exponential Smoothing
 </li>
 <li>
 ML-based Forecasting: GBM, LightGBM, XGBoost, Linear Regression
 </li>
 <li>
 DL-based Forecasting: DeepAR, NBEATS, LSTM, RNN
 </li>
 <li>
 Hierarchical Forecasting
 </li>
 <li>
 Cross-Validation: Rolling-window, Expanding-window, K-fold, Hold-out
 </li>
 <li>
 MLOps is also good to have skills.
 </li>
 <li>
 Any type of simulation model experience (Good to have).
 </li>
 <li>
 Agent-based Simulation Model using Anylogic (Good to have).
 </li>
 <li>
 Exposure to LLM or GPT good to have skills
 </li>
 </ul>
 
 
 
 
 
 Key Skills:
 
 Data Scientist, Machine Learning, Statistical Forecasting, Python
 
 
 
</div>

JPMorganChase

<div>
 
 Job Description
 
 
 
 Job Summary:
 
 
 J.P. Morgan Compliance, Conduct, and Operational Risk (CCOR) Data Science function is at the forefront of developing innovative AI and ML solutions to enhance risk management and compliance processes. Our team leverages advanced analytics, AI, Machine learning technologies, including Large Language Models (LLMs), to transform how we manage compliance, conduct, and operational risks across the organization.
 
 
 Join our CCOR Data Science team as a Lead Data Scientist, where you will play a crucial role in developing AI/ML solutions to enhance compliance and risk management. Your primary responsibilities will include leveraging advance AI / ML techniques, LLMs and Agentic AI to develop and deploy models for various tasks such as anomaly detection, risk assessment, and compliance monitoring. You will work with diverse datasets to improve our risk management processes and ensure regulatory compliance. As part of a leading analytics community, you will have opportunities for skill development and career growth in AI, machine learning, and data science.
 
 
 
 Job Responsibilities
 
 
 
 <ul>
 <li>
 Design, deploy, and manage AI/ML models, leverages advance AI/ML techniques, LLMs and Agentic AI for developing compliance and risk management related solution.
 </li>
 <li>
 Conduct research on AI techniques to enhance model performance in the compliance and risk domains.
 </li>
 <li>
 Collaborate with cross-functional teams to identify requirements, develop solutions, and deploy models in the production system.
 </li>
 <li>
 Communicate technical concepts effectively to both technical and non-technical stakeholders.
 </li>
 <li>
 Develop and maintain tools and frameworks for model training, evaluation, and optimization.
 </li>
 <li>
 Analyze and interpret data to evaluate model performance and identify areas for improvement.
 
 
 </li>
 </ul>
 
 Required Qualifications, Capabilities, And Skills
 
 
 
 <ul>
 <li>
 Master&rsquo;s degree in quantitative discipline or an MBA with an undergraduate degree in areas such as Computer Science, Statistics, Economics, Mathematics etc. from top tier Universities.
 </li>
 <li>
 Minimum of 8 years of relevant experience in developing AI/ML solutions, with recent exposure to LLMs and Agentic AI.
 </li>
 <li>
 Programming skills in Python, with experience in frameworks like PyTorch or TensorFlow.
 </li>
 <li>
 Thorough knowledge of machine learning concepts, including transformers and language modeling.
 </li>
 <li>
 Experience in data pre-processing, feature engineering, and data analysis.
 </li>
 <li>
 Excellent problem-solving skills and the ability to communicate ideas and results clearly.
 </li>
 <li>
 Familiarity with data structures and algorithms for effective problem-solving in machine learning workflows.
 
 
 </li>
 </ul>
 
 ABOUT US
 
 
 
 JPMorganChase, one of the oldest financial institutions, offers innovative financial solutions to millions of consumers, small businesses and many of the world&rsquo;s most prominent corporate, institutional and government clients under the J.P. Morgan and Chase brands. Our history spans over 200 years and today we are a leader in investment banking, consumer and small business banking, commercial banking, financial transaction processing and asset management.
 
 
 We recognize that our people are our strength and the diverse talents they bring to our global workforce are directly linked to our success. We are an equal opportunity employer and place a high value on diversity and inclusion at our company. We do not discriminate on the basis of any protected attribute, including race, religion, color, national origin, gender, sexual orientation, gender identity, gender expression, age, marital or veteran status, pregnancy or disability, or any other basis protected under applicable law. We also make reasonable accommodations for applicants&rsquo; and employees&rsquo; religious practices and beliefs, as well as mental health or physical disability needs. Visit our FAQs for more information about requesting an accommodation.
 
 
 
 About The Team
 
 
 
 Our professionals in our Corporate Functions cover a diverse range of areas from finance and risk to human resources and marketing. Our corporate teams are an essential part of our company, ensuring that we&rsquo;re setting our businesses, clients, customers and employees up for success.
</div>

Vice President – Data Science / Applied AI ML

PhonePe

<div>
 
 
 Job Description:
 
 
 
 We are looking for an experienced Data Scientist with 6+ years of experience to join our team and drive impactful data-driven solutions. The ideal candidate will possess deep expertise in machine learning, statistical modeling, and big data processing, along with a proven ability to work with cross-functional teams and effectively communicate insights to stakeholders. This role requires a strategic mindset, strong leadership, and the ability to translate complex data problems into actionable business insights.
 
 
 
 
 
 
 Key Responsibilities:
 
 
 <ul>
 <li>
 Lead and drive the development of advanced machine learning models to solve high-impact business challenges.
 </li>
 <li>
 Collaborate with stakeholders (business leaders, product managers, engineering teams) to identify opportunities where data science can add business value.
 </li>
 <li>
 Embed yourself with business to understand the strategy and propose data solutions to accelerate outcomes.
 </li>
 <li>
 Design and implement scalable data pipelines and real-time analytics solutions.
 </li>
 <li>
 Guide and mentor data scientists, fostering a culture of innovation and best practices.
 </li>
 <li>
 Conduct deep-dive analyses to extract meaningful insights from complex and large datasets.
 </li>
 <li>
 Ensure machine learning models are explainable, reproducible, and aligned with business objectives.
 </li>
 <li>
 Present findings and recommendations to key stakeholders in a clear and actionable manner.
 </li>
 <li>
 Work closely with engineering teams to deploy ML models into production environments at scale.
 </li>
 <li>
 Own end-to-end model lifecycle management, including data preprocessing, feature engineering, model training, validation, and monitoring.
 </li>
 </ul>
 
 
 
 
 
 Required Qualifications:
 
 
 <ul>
 <li>
 
 Bachelor's or Master&rsquo;s degree
 
 in Computer Science, Data Science, Statistics, Mathematics, or a related field (Ph.D. preferred but not mandatory).
 </li>
 <li>
 
 6+ years of experience
 
 in data science, machine learning, or applied statistics. Experience in
 
 financial services, fintech, e-commerce, or similar data-driven industries
 
 .
 </li>
 <li>
 Strong expertise in
 
 Python, SQL
 
 with proficiency in
 
 machine learning frameworks
 
 such as TensorFlow, PyTorch, or Scikit-Learn.
 </li>
 <li>
 Solid understanding of
 
 big data technologies
 
 (Spark, PySpark, Hadoop, or similar).
 </li>
 <li>
 Hands-on experience in
 
 model deployment
 
 using cloud platforms (AWS, GCP, Azure) and ML Ops frameworks (MLflow, Kubeflow, etc.).
 </li>
 <li>
 Expertise in
 
 statistical modeling, predictive analytics
 
 .
 </li>
 <li>
 Experience working with
 
 real-time and batch-processing systems
 
 .
 </li>
 <li>
 Demonstrated ability to
 
 translate business problems into data science solutions
 
 .
 </li>
 <li>
 Excellent problem-solving, critical-thinking, and analytical skills.
 </li>
 <li>
 
 Strong communication and stakeholder management skills
 
 , with the ability to explain technical concepts to non-technical audiences.
 </li>
 </ul>
 
 
 
 
 
 Preferred Qualifications:
 
 
 <ul>
 <li>
 Experience in
 
 financial services, fintech, e-commerce, or similar data-driven industries
 
 .
 </li>
 </ul>
</div>

Explore 427+ Data scientist traditional ml in Mangaluru India this November. Find roles across top companies and apply now to boost your career.

427 data scientist traditional ml jobs IN Mangaluru India

Data Scientist (Traditional ML)

Machine Learning Data Scientist (Blr)

Data Scientist

Assistant Manager - Technology & Platform Development

Data Scientist

Vice President – Data Science / Applied AI ML

Data Scientist