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business intelligence analyst Jobs in Pune India

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data analyst-data management and analytics-data ops/data analyst Jobs in Pune India

data analyst-data management and analytics-data ops/data analyst

data engineer-business intelligence Jobs in Pune India

data engineer-business intelligence

data scientist

Calsoft

<div>
 
 Job Title: AI/ML Engineer &ndash;
 
 
 GenAI / Agentic AI
 
 
 Experience: 3+ Years
 
 
 Location: Pune / Indore / Bangalore / Kolkata Role
 
 
 Summary
 
 
 We are looking for an experienced AI/ML Engineer &ndash; GenAI / Agentic AI to design, build, and deploy intelligent, autonomous AI systems. The role involves working on Large Language Models (LLMs), Retrieval-Augmented Generation (RAG) pipelines, and Agentic AI frameworks to solve real-world enterprise problems. Key Responsibilities
 
 
 &bull; Design, develop, and deploy Generative AI and Agentic AI solutions using LLMs
 
 
 
 
 
 &bull; Build and optimize RAG pipelines with vector databases (FAISS, Pinecone, Weaviate, etc.)
 
 
 &bull; Develop multi-agent systems using frameworks like LangChain, LangGraph, AutoGen, CrewAI
 
 
 &bull; Integrate LLMs with enterprise systems, APIs, tools, and workflows
 
 
 &bull; Fine-tune and prompt-engineer LLMs for domain-specific use cases
 
 
 &bull; Implement evaluation, monitoring, and guardrails for GenAI systems
 
 
 &bull; Collaborate with product, data, and cloud teams for scalable deployment
 
 
 &bull; Ensure performance, cost optimization, security, and compliance
 
 
 Mandatory Skills
 
 
 &bull; Python (Strong proficiency)
 
 
 &bull; AI/ML fundamentals &ndash; NLP, Deep Learning, Transformers
 
 
 &bull; Generative AI &amp; LLMs (OpenAI, Azure OpenAI, Gemini, Anthropic, LLaMA, etc.)
 
 
 &bull; Agentic AI frameworks &ndash; LangChain / LangGraph / AutoGen / CrewAI
 
 
 &bull; RAG architecture and vector databases
 
 
 &bull; Prompt engineering &amp; LLM orchestration
 
 
 &bull; REST APIs, microservices integration Good to Have
 
 
 &bull; Fine-tuning LLMs (LoRA, PEFT)
 
 
 &bull; Experience with MLOps / LLMOps (MLflow, Kubeflow, monitoring tools) &bull; Cloud platforms: AWS / Azure / GCP
 
 
 &bull; Knowledge of Docker, Kubernetes
 
 
 &bull; Experience in enterprise use cases (BFSI, Healthcare, Retail, Telecom) Qualifications
 
 
 &bull; B.E. / B.Tech / M.Tech / MCA in Computer Science, AI, Data Science, or related field
 
 
 &bull; 5+ years of hands-on experience in AI/ML with recent focus on GenAI / Agentic AI Why Join Us
 
 
 &bull; Work on cutting-edge Agentic AI &amp; GenAI platforms
 
 
 &bull; Opportunity to build autonomous, production-grade AI systems
 
 
 &bull; High-impact enterprise projects &bull; Collaborative and innovation-driven environment
 
</div>

Data Scientist

Mastercard

<div>
 
 Our Purpose
 
 
 
 
 Mastercard powers economies and empowers people in 200+ countries and territories worldwide. Together with our customers, we&rsquo;re helping build a sustainable economy where everyone can prosper. We support a wide range of digital payments choices, making transactions secure, simple, smart and accessible. Our technology and innovation, partnerships and networks combine to deliver a unique set of products and services that help people, businesses and governments realize their greatest potential.
 
 
 
 
 Title And Summary
 
 
 
 Director, Data Scientist
 
 
 Director, Data Science
 
 
 
 Overview
 
 
 
 We believe in the power of data to transform the way we do business. As part of our Finance Modernization initiative, we are reimagining how AI and Data Analytics, drive insight, efficiency, and strategic decision making.
 
 
 The Global Business Services Center (GBSC) Analytics &amp; Automation team is a hub of innovation. an idea incubator composed of strong contributors with leadership capabilities, business acumen, and technical expertise. The team identifies ways to leverage data and AI for answering business questions and driving operational efficiency. We innovate using AI and data analysis techniques to discover actionable insights and communicate data in new and more effective ways for influencing business decisions, encouraging, improving processes and productivity, and overall evolving the way we do business.
 
 
 As Director, Data Science, you will drive foundational AI strategy and execution for business operations. You will define roadmap, architect solutions, and lead cross-functional delivery to unlock and communicate measurable efficiency and innovation. You will work hands-on with data scientists, ML and platform engineers, and senior business leaders to deliver high-impact use cases.
 
 
 
 Your Role And Responsibilities
 
 
 
 <ul>
 <li>
 Develop AI-driven strategies to support business value.
 </li>
 <li>
 Identify, qualify, and prioritize high-impact AI opportunities across business domains.
 </li>
 <li>
 Translate north star vision into executable plans, building alignment among relevant executives and business stakeholders on timing and delivery.
 </li>
 <li>
 Enable quick and iterative delivery of AI solutions with consistent value creation.
 </li>
 <li>
 Collaborate with cross-functional teams (Finance BAs, Privacy, AI Governance, Info Security, BizOps, etc.) to design development patterns fit for productionizing and scale.
 </li>
 <li>
 Monitor industry trends and emerging technologies to ensure the organization remains at the forefront of AI and automation advancements.
 </li>
 <li>
 Oversee the needs for documenting knowledge, creating templates, and authoring playbooks to help the team scale.
 </li>
 <li>
 Oversee the end-to-end implementation of data science and AI solutions&mdash;from concept and prototype through deployment, integration, and performance monitoring.
 </li>
 <li>
 Develop and maintain a value realization framework that quantifies the business impact of data science initiatives (e.g., cost optimization, working capital improvements, revenue enhancement, or process automation).
 </li>
 <li>
 Continuously evaluate and refine models and solutions to maximize financial and operational outcomes.
 </li>
 <li>
 Lead and manage the ML Ops team, ensuring scalable deployment, automation, and monitoring of machine learning models across environments.
 
 
 
 </li>
 </ul>
 
 All About You
 
 
 
 <ul>
 <li>
 10 to 12+ years hands-on leadership of technology strategies, leveraging data and AI to solve complex business problems and drive measurable impact in large, regulated environments.
 </li>
 <li>
 Proven track record influencing and aligning executives and cross-functional teams to deliver outcomes at scale.
 </li>
 <li>
 Strong communicator &ndash; executive presence, crisp storytelling, and the ability to translate complex technical concepts into actionable business strategy.
 </li>
 <li>
 Highly competent problem solving and solutioning skills; able to demonstrate business need as well as technical solution discovery and design.
 </li>
 <li>
 Proven experience in productionizing AI capabilities based on large datasets, and modern AI patterns (LLMs, RAG, vector databases, embeddings, prompt/response optimization, agents &amp; tools).
 
 
 
 </li>
 </ul>
 Good to Have
 
 
 <ul>
 <li>
 Experience in the financial institutions or payments industry.
 </li>
 <li>
 Knowledge of cloud computing (Databricks, AWS).
 </li>
 <li>
 Familiarity with agile methodologies
 
 
 
 </li>
 </ul>
 
 Corporate Security Responsibility
 
 
 
 All activities involving access to Mastercard assets, information, and networks comes with an inherent risk to the organization and, therefore, it is expected that every person working for, or on behalf of, Mastercard is responsible for information security and must:
 
 
 <ul>
 <li>
 Abide by Mastercard&rsquo;s security policies and practices;
 </li>
 <li>
 Ensure the confidentiality and integrity of the information being accessed;
 </li>
 <li>
 Report any suspected information security violation or breach, and
 </li>
 <li>
 Complete all periodic mandatory security trainings in accordance with Mastercard&rsquo;s guidelines.
 </li>
 </ul>
</div>

Director, Data Scientist

Infosys

<div>
 Working experience in Agile environment
 
 
 <ul>
 <li>
 knowledge on Cloud Infrastructure and data source integrations
 </li>
 <li>
 Knowledge on relational Databases and Cognos Analytics
 </li>
 <li>
 Self-motivated, be able to work independently as well as being a team player
 </li>
 <li>
 Strong client service focus and willingness to respond to queries and provide deliverables within prompt timeframes.
 </li>
 </ul>
</div>

Data Scientist (CV)

<div>
 
 Introduction
 
 
 
 In this role, you'll work in one of our IBM Consulting Client Innovation Centers (Delivery Centers), where we deliver deep technical and industry expertise to a wide range of public and private sector clients around the world. Our delivery centers offer our clients locally based skills and technical expertise to drive innovation and adoption of new technology.
 
 
 
 Your Role And Responsibilities
 
 
 
 <ul>
 <li>
 Work with broader team to build, analyze and improve the AI solutions.
 </li>
 <li>
 You will also work with our software developers in consuming different enterprise applications.
 
 
 </li>
 </ul>
 
 Required Technical And Professional Expertise
 
 
 
 <ul>
 <li>
 Resource should have 5-7 years of experience. Sound knowledge of Python and should know how to use the ML related services.
 </li>
 <li>
 Proficient in Python with focus on Data Analytics Packages.
 </li>
 <li>
 Strategy Analyse large, complex data sets and provide actionable insights to inform business decisions.
 </li>
 <li>
 Strategy Design and implementing data models that help in identifying patterns and trends. Collaboration Work with data engineers to optimize and maintain data pipelines.
 </li>
 <li>
 Perform quantitative analyses that translate data into actionable insights and provide analytical, data-driven decision-making. Identify and recommend process improvements to enhance the efficiency of the data platform. Develop and maintain data models, algorithms, and statistical models
 
 
 </li>
 </ul>
 
 Preferred Technical And Professional Experience
 
 
 
 <ul>
 <li>
 Experience with conversation analytics. Experience with cloud technologies
 </li>
 <li>
 Experience with data exploration tools such as Tableu
 </li>
 </ul>
</div>

Data Scientist-Artificial Intelligence

PwC India

<div>
 
 Job Position Title: Data Scientist Gen AI
 
 
 Location: PAN India
 
 
 Years of experience required: 5-9 Years
 
 
 Mandatory skill sets: AI chatbots, Data structures, GenAI object-oriented programming, IDE, API, LLM Prompts, PyTorch, TensorFlow
 
 
 
 
 
 
 
 
 Responsibilities:
 
 
 Position responsibilities and expectations &middot; Designing and building analytical /DL/ ML algorithms using Python, R and other statistical tools. &middot; Strong data representation and lucid presentation (of analysis/modelling output) using Python, R Markdown &middot; Ability to learn new scripting language or analytics platform. Technical Skills required (must have) &middot; HandsOn Exposure to Generative AI (Design, development of GenAI application in production) &middot; Strong understanding of RAG, Vector Database, Lang Chain and multimodal AI applications. &middot; Strong understanding of deploying and optimizing AI application in production. &middot; Strong knowledge of statistical and data mining techniques like Linear &amp; Logistic Regression analysis, Decision trees, Bagging, Boosting, Time Series and Non-parametric analysis. &middot; Strong knowledge of DL &amp; Neural Network Architectures (CNN, RNN, LSTM, Transformers etc.) &middot; Strong knowledge of SQL and R/Python and experience with distributing data/computing tools/IDEs. &middot; Experience in advanced Text Analytics (NLP, NLU, NLG). &middot; Understanding of LLM Ops, ML Ops for scalable ML development. &middot; Working knowledge on agents like PyTorch, TensorFlow &middot; Proven capability in using Generative AI services like OpenAI, Google (Gemini) &middot; Understanding of Agentic AI Framework (Lang Graph, Auto gen etc.) &middot; Understanding of fine-tuning for pre-trained models like GPT, LLaMA, Claude etc. using LoRA, QLoRA and PEFT technique.
 
</div>

Generative AI Engineer

Siemens Digital Industries Software

<div>
 We are a leading global software company dedicated to the world of computer aided design, 3D modeling and simulation&mdash; helping innovative global manufacturers design better products, faster! With the resources of a large company, and the energy of a software start-up, we have fun together while creating a world class software portfolio. Our culture encourages creativity, welcomes fresh thinking, and focuses on growth, so our people, our business, and our customers can achieve their full potential.
 
 
 Are you enthusiastic about turning data into actionable insights? Do you enjoy collaborating with cross-functional teams to solve complex problems? Do you thrive in building automated processes that transform how organizations make decisions? Do you excel at creating dashboards that tell compelling stories through data?
 
 
 Then you are the perfect candidate to join our Software business as a Business Intelligence Analyst in our innovative data-driven customer success team.
 
 
 Position Overview
 
 
 You will join a newly formed data science team focused that provides immediate return on investment by delivering critical insights to our Sales and Customer Success teams.
 
 
 This key role supports the team by:
 
 
 <ul>
 <li>
 Creating insightful dashboards to support a sophisticated customer health scoring system. Our primary mission is establishing a robust warning system that identifies at-risk customers and enables proactive intervention. This role will be key for creating a data-driven customer success practice across our SaaS portfolio. You will empower our sales and customer success teams with timely insights to prevent churn and identify expansion opportunities.
 </li>
 <li>
 Creating and managing existing key dashboards used by end-users across the Global Sales, Customer Success, Customer Support, and Professional Services organization(s).
 
 
 </li>
 </ul>
 You will work within a small, high-impact technical team comprised of Data Architect and Data Scientists to build the integrations, processes, and visualizations that will transform our approach to customer success.
 
 
 Your initial focus will be on implementing a manual warning system that can quickly deliver value, while also laying the groundwork for future automation.
 
 
 An ideal candidate will have strong data analysis skills combined with technical expertise in building dashboards and data pipelines within a SaaS environment. This role will be working at the intersection of data science, customer success, and sales enablement to drive measurable outcomes for our organization. It is imperative that this individual contributor can communicate effectively and collaborate with internal global customers to successfully deploy insightful analytics for the business.
 
 
 
 Responsibilities
 
 
 
 <ul>
 <li>
 Dashboard
 </li>
 <li>
 Create comprehensive and insightful dashboards that offer actionable insights to sales teams
 </li>
 <li>
 Build reliable data pipelines between various sources and our analytics platforms
 </li>
 <li>
 Dashboard + Data security and governance administrator
 </li>
 <li>
 Perform data cleansing, transformation, and replication to ensure high-quality inputs for the Customer Health Index and other key data sources used by the organization
 </li>
 <li>
 Continuously improve dashboards and reports based on user feedback and evolving business needs
 </li>
 <li>
 Data-Related:
 </li>
 <li>
 Define and develop data products by specific use cases in our data aggregation platform
 </li>
 <li>
 Work closely with the Data Scientist to operationalize analytical models and algorithms
 </li>
 <li>
 Document data flows, definitions, and processes to ensure sustainability and scalability
 </li>
 <li>
 Cross-Functional and Requirements Gathering:
 </li>
 <li>
 Develop and implement a manual warning system for at-risk customers that can be quickly operationalized
 </li>
 <li>
 Define and establish how and where customer health information will be visible to different stakeholders
 </li>
 <li>
 Collaborate with sales teams to ensure the data insights meet their immediate needs and enhance their workflows
 </li>
 <li>
 Find patterns in customer data that can inform success strategies and expansion opportunities
 
 
 </li>
 </ul>
 Work Environment
 
 
 <ul>
 <li>
 This job is a hybrid role that requires you to be in the Siemens Pune office for at least three days each week.
 </li>
 <li>
 You must work according to the US time zones for at least three days each week.
 
 
 </li>
 </ul>
 
 Required Knowledge/Skills, Education, And Experience
 
 
 
 <ul>
 <li>
 Bachelor's degree in Computer Science, Data Science, Data Analytics, or related field
 </li>
 <li>
 3+ years demonstrated ability in data analysis, business intelligence, or related role in a SaaS environment
 </li>
 <li>
 Strong knowledge and experience with Business Intelligence Applications, such as Tableau, CRM Analytics, and/or PowerBI
 </li>
 <li>
 Strong SQL skills and experience with Snowflake or similar cloud data platforms
 </li>
 <li>
 Python proficiency with experience in data manipulation and analysis
 </li>
 <li>
 Experience developing dashboards that deliver actionable business insights
 </li>
 <li>
 Knowledge of ETL processes and data pipeline development
 </li>
 <li>
 Experience working with sales and customer success teams to deliver data-driven insights
 </li>
 <li>
 Familiarity with customer health metrics and SaaS business models
 </li>
 <li>
 Understanding of data cleansing and quality assurance methodologies
 </li>
 <li>
 Exceptional work ethic towards data-driven decision making and process improvement
 </li>
 <li>
 Strong analytical thinking and problem-solving capabilities
 </li>
 <li>
 Superb communication skills with ability to translate technical concepts to business partners
 </li>
 <li>
 Self-motivated with ability to work independently in a fast-paced environment
 
 
 </li>
 </ul>
 
 Preferred Qualifications
 
 
 
 <ul>
 <li>
 Experience with Salesforce CRM, Certinia, and Gainsight (or similar customer success platforms)
 </li>
 <li>
 Knowledge of pandas, data frames, and other Python data science libraries
 </li>
 <li>
 Experience with establishing data products in an enterprise environment
 </li>
 <li>
 Experience in data transformation using dbt, Alteryx, Tableau Prep, or similar tools
 </li>
 <li>
 Background in customer success operations or SaaS product analytics
 </li>
 <li>
 Experience working with globally distributed teams
 </li>
 <li>
 Salesforce or Tableau certifications desired, but optional
 
 
 </li>
 </ul>
 We offer a role with responsibility, independence, and the possibility to contribute proactively. You will be joining a dynamic team of data and SaaS experts with a highly innovative approach. We foster a teamwork culture with room for individual development, impact, and career growth.
 
 
 Why us?
 
 
 Working at Siemens Software means flexibility - Choosing between working at home and the office at other times is the norm here. We offer great benefits and rewards, as you'd expect from a world leader in industrial software.
 
 
 A collection of over 377,000 minds building the future, one day at a time in over 200 countries. We're dedicated to equality, and we welcome applications that reflect the diversity of the communities we work in. All employment decisions at Siemens are based on qualifications, merit, and business need. Bring your curiosity and creativity and help us shape tomorrow!
 
 
 Siemens Software. Transform the Everyday
 
 
 #SWSaaS
 
 
</div>

Business Intelligence Analyst

<div>
 <ul>
 <li>
 5 - 9 years of professional experience as a Data Analyst with good decision-making, analytical and problem-solving skills.
 </li>
 <li>
 Working knowledge / experience of Big Data frameworks like Hadoop, Hive and Spark.
 </li>
 <li>
 Hands-on experience in query languages like HQL or SQL (Spark SQL) for Data exploration.
 </li>
 <li>
 Data mapping: Determine the data mapping required to join multiple data sets together across multiple sources.
 </li>
 <li>
 Documentation - Data Mapping, Subsystem Design, Technical Design, Business Requirements.
 </li>
 <li>
 Exposure to Logical to Physical Mapping, Data Processing Flow to measure the consistency, etc.
 </li>
 <li>
 Data Asset design / build: Working with the data model / asset generation team to identify critical data elements and determine the mapping for reusable data assets.
 </li>
 <li>
 Understanding of ER Diagram and Data Modeling concepts
 </li>
 <li>
 Exposure to Data quality validation
 </li>
 <li>
 Exposure to Data Management, Data Cleaning and Data Preparation
 </li>
 <li>
 Exposure to Data Schema analysis.
 </li>
 <li>
 Exposure to working in Agile framework.
 </li>
 <li>
 SQL, Pyspark, Python with Wholesale Banking Domain knowledge / Credit &amp; Lending domain knowledge.
 </li>
 <li>
 Knowledge of Credit Risk Frameworks such as Basel II, III, IFRS 9 and Stress Testing and understanding their drivers - advantageous
 </li>
 <li>
 Retail Credit / Traded Credit knowledge - applications will be considered.
 
 
 </li>
 </ul>
 
 Good To Have
 
 
 
 <ul>
 <li>
 BFSI Domain knowledge
 </li>
 <li>
 Data Visualization - Tableau or Qlik Sense
 </li>
 <li>
 Exposure to Hadoop, Hive and ETL.
 </li>
 <li>
 Working knowledge of any cloud services like AWS or GCP or Azure.
 </li>
 <li>
 Any relevant certifications would be a plus.
 </li>
 </ul>
</div>

Data Analyst-Data Management and Analytics-Data Ops/Data Analyst

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