648 Xgboost Jobs - Page 9

Posted On: 14 Jul 2025 Location: Noida, UP, India Company: Iris Software Why Join Us? Are you inspired to grow your career at one of India’s Top 25 Best Workplaces in IT industry? Do you want to do the best work of your life at one of the fastest growing IT services companies ? Do you aspire to thrive in an award-winning work culture that values your talent and career aspirations ? It’s happening right here at Iris Software. About Iris Software At Iris Software, our vision is to be our client’s most trusted technology partner, and the first choice for the industry’s top professionals to realize their full potential. With over 4,300 associates across India, U.S.A, and Canada, we help our enterprise clients thrive with technology-enabled transformation across financial services, healthcare, transportation & logistics, and professional services. Our work covers complex, mission-critical applications with the latest technologies, such as high-value complex Application & Product Engineering, Data & Analytics, Cloud, DevOps, Data & MLOps, Quality Engineering, and Business Automation. Working at Iris Be valued, be inspired, be your best. At Iris Software, we invest in and create a culture where colleagues feel valued, can explore their potential, and have opportunities to grow. Our employee value proposition (EVP) is about “Being Your Best” – as a professional and person. It is about being challenged by work that inspires us, being empowered to excel and grow in your career, and being part of a culture where talent is valued. We’re a place where everyone can discover and be their best version. Job Description We are seeking a Data Science Engineer to design, build, and optimize scalable data and machine learning systems. This role requires strong software engineering skills, a deep understanding of data science workflows, and the ability to work cross-functionally to translate business problems into production-level data solutions. Key Responsibilities: Design, implement, and maintain data science pipelines from data ingestion to model deployment. Collaborate with data scientists to operationalize ML models and algorithms in production environments. Develop robust APIs and services for ML model inference and integration. Build and optimize large-scale data processing systems using Spark, Pandas, or similar tools. Ensure data quality and pipeline reliability through rigorous testing, validation, and monitoring. Work with cloud infrastructure (AWS) for scalable ML deployment. Manage model versioning, feature engineering workflows, and experiment tracking. Optimize performance of models and pipelines for latency, cost, and throughput. Required Qualifications: Bachelor’s or Master’s degree in Computer Science, Data Science, Engineering, or a related field. 5+ years of experience in a data science, ML engineering, or software engineering role. Proficiency in Python (preferred) and SQL; knowledge of Java, Scala, or C++ is a plus. Experience with data science libraries like Scikit-learn, XGBoost, TensorFlow, or PyTorch. Familiarity with ML deployment tools such as ML flow, Sage Maker, or Vertex AI. Solid understanding of data structures, algorithms, and software engineering best practices. Experience working with databases (SQL, NoSQL) and data lakes (e.g., Delta Lake, Big Query). Preferred Qualifications: Experience with containerization and orchestration (Docker, Kubernetes). Experience working in Agile or cross-functional teams. Familiarity with streaming data platforms (Kafka, Spark Streaming, Flink). Soft Skills: Strong communication skills to bridge technical and business teams. Excellent problem-solving and analytical thinking. Self-motivated and capable of working independently or within a team. Passion for data and a curiosity-driven mindset. Mandatory Competencies Data Science and Machine Learning - Data Science and Machine Learning - AI/ML Database - Database Programming - SQL Programming Language - Python - Panda Cloud - GCP - Cloud Data Fusion, Dataproc, BigQuery, Cloud Composer, Cloud Bigtable Database - No SQL - Elastic, Solr, Lucene etc Programming Language - Other Programming Language - Scala Agile - Agile - SCRUM DevOps/Configuration Mgmt - DevOps/Configuration Mgmt - Containerization (Docker, Kubernetes) Cloud - AWS - Tensorflow on AWS, AWS Glue, AWS EMR, Amazon Data Pipeline, AWS Redshift Beh - Communication and collaboration Perks and Benefits for Irisians At Iris Software, we offer world-class benefits designed to support the financial, health and well-being needs of our associates to help achieve harmony between their professional and personal growth. From comprehensive health insurance and competitive salaries to flexible work arrangements and ongoing learning opportunities, we're committed to providing a supportive and rewarding work environment. Join us and experience the difference of working at a company that values its employees' success and happiness.

Urgently Hiring for AI/ML Role We are seeking an experienced AI/ML Engineer with 3–5 years of hands-on experience in building and deploying machine learning solutions in the fintech and spend management domain. You will work on real-time forecasting, intelligent document processing (invoices/receipts), fraud detection, and other AI-powered features that enhance our finance intelligence platform. This role demands expertise in both time series forecasting and computer vision, as well as a solid understanding of how ML applies to enterprise finance operations. Key Responsibilities: Design, train, and deploy ML models for spend forecasting, budget prediction, expense categorization, and risk scoring. Build and optimize OCR-based invoice and receipt parsing systems using computer vision and NLP techniques. Implement time-series models (Prophet, ARIMA, LSTM, XGBoost, etc.) for forecasting trends in financial transactions, expenses, and vendor payments. Work on intelligent document classification, key-value extraction, and line-item detection from unstructured financial documents (PDFs, scanned images). Collaborate with product and finance teams to define high-impact AI use cases and deliver business-ready solutions. Integrate ML pipelines into production using scalable tools and platforms (Docker, CI/CD, cloud services). Monitor model performance post-deployment, conduct drift analysis, and implement retraining strategies. Required Skills & Qualifications: Core Machine Learning Strong knowledge of supervised and unsupervised ML techniques applied to structured and semi-structured financial data Experience in time-series analysis and forecasting algorithms such as: ARIMA, SARIMA Facebook Prophet XGBoost for regression LSTM / GRU models for sequential data Proficiency in Python and key libraries: scikit-learn, Pandas, NumPy, StatsModels, PyTorch, TensorFlow. Computer Vision & Document AI Hands-on experience with OCR tools such as Tesseract, Google Vision API, or AWS Textract. Knowledge of document layout analysis and field-level extraction using OpenCV, LayoutLM, or Google Document AI. Familiarity with annotation tools (Label Studio, CVAT) and post-processing OCR outputs for structured data extraction. Deployment & Engineering Experience in exposing ML models via Flask or FastAPI. Model packaging and deployment with Docker, version control with Git, and ML lifecycle tools like MLflow or DVC. Working knowledge of cloud platforms (AWS/GCP/Azure) and integrating models with backend microservices. Data & Domain Understanding of financial documents: invoices, receipts, expense reports, and GL data. Ability to work with tabular, image-based, and PDF-based financial datasets. SQL proficiency and familiarity with financial databases or ERP systems is a plus.

Data Scientist II Hyderabad, Telangana, India Date posted Jul 15, 2025 Job number 1847276 Work site Up to 50% work from home Travel 0-25 % Role type Individual Contributor Profession Research, Applied, & Data Sciences Discipline Data Science Employment type Full-Time Overview Security represents the most critical priorities for our customers in a world awash in digital threats, regulatory scrutiny, and estate complexity. Microsoft Security aspires to make the world a safer place for all. We want to reshape security and empower every user, customer, and developer with a security cloud that protects them with end to end, simplified solutions. The Microsoft Security organization accelerates Microsoft’s mission and bold ambitions to ensure that our company and industry is securing digital technology platforms, devices, and clouds in our customers’ heterogeneous environments, as well as ensuring the security of our own internal estate. Our culture is centered on embracing a growth mindset, a theme of inspiring excellence, and encouraging teams and leaders to bring their best each day. In doing so, we create life-changing innovations that impact billions of lives around the world. The Defender Experts (DEX) Research team is at the forefront of Microsoft’s threat protection strategy, combining world-class hunting expertise with AI-driven analytics to protect customers from advanced cyberattacks. Our mission is to move protection left—disrupting threats early, before damage occurs—by transforming raw signals into intelligence that powers detection, disruption, and customer trust. We’re looking for a passionate and curious Data Scientist to join this high-impact team. In this role, you'll partner with researchers, hunters, and detection engineers to explore attacker behavior, operationalize entity graphs, and develop statistical and ML-driven models that enhance DEX’s detection efficacy. Your work will directly feed into real-time protections used by thousands of enterprises and shape the future of Microsoft Security. This is an opportunity to work on problems that matter—with cutting-edge data, a highly collaborative team, and the scale of Microsoft behind you. Microsoft’s mission is to empower every person and every organization on the planet to achieve more. As employees we come together with a growth mindset, innovate to empower others, and collaborate to realize our shared goals. Each day we build on our values of respect, integrity, and accountability to create a culture of inclusion where everyone can thrive at work and beyond. Microsoft’s mission is to empower every person and every organization on the planet to achieve more. As employees we come together with a growth mindset, innovate to empower others, and collaborate to realize our shared goals. Each day we build on our values of respect, integrity, and accountability to create a culture of inclusion where everyone can thrive at work and beyond. Microsoft’s mission is to empower every person and every organization on the planet to achieve more. As employees we come together with a growth mindset, innovate to empower others, and collaborate to realize our shared goals. Each day we build on our values of respect, integrity, and accountability to create a culture of inclusion where everyone can thrive at work and beyond. Qualifications Bachelor’s or Master’s degree in Computer Science, Statistics, Applied Mathematics, Data Science, or a related quantitative field 5+ years of experience applying data science or machine learning in a real-world setting, preferably in security, fraud, risk, or anomaly detection Proficiency in Python and/or R, with hands-on experience in data manipulation (e.g., Pandas, NumPy), modeling (e.g., scikit-learn, XGBoost), and visualization (e.g., matplotlib, seaborn) Strong foundation in statistics, probability, and applied machine learning techniques Experience working with large-scale datasets, telemetry, or graph-structured data Ability to clearly communicate technical insights and influence cross-disciplinary teams Demonstrated ability to work independently, take ownership of problems, and drive solutions end-to-end Responsibilities Understand complex cybersecurity and business problems, translate them into well-defined data science problems, and build scalable solutions. Design and build robust, large-scale graph structures to model security entities, behaviors, and relationships. Develop and deploy scalable, production-grade AI/ML systems and intelligent agents for real-time threat detection, classification, and response. Collaborate closely with Security Research teams to integrate domain knowledge into data science workflows and enrich model development. Drive end-to-end ML lifecycle: from data ingestion and feature engineering to model development, evaluation, and deployment. Work with large-scale graph data: create, query, and process it efficiently to extract insights and power models. Lead initiatives involving Graph ML, Generative AI, and agent-based systems, driving innovation across threat detection, risk propagation, and incident response. Collaborate closely with engineering and product teams to integrate solutions into production platforms. Mentor junior team members and contribute to strategic decisions around model architecture, evaluation, and deployment. Benefits/perks listed below may vary depending on the nature of your employment with Microsoft and the country where you work.  Industry leading healthcare  Educational resources  Discounts on products and services  Savings and investments  Maternity and paternity leave  Generous time away  Giving programs  Opportunities to network and connect Microsoft is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to age, ancestry, citizenship, color, family or medical care leave, gender identity or expression, genetic information, immigration status, marital status, medical condition, national origin, physical or mental disability, political affiliation, protected veteran or military status, race, ethnicity, religion, sex (including pregnancy), sexual orientation, or any other characteristic protected by applicable local laws, regulations and ordinances. If you need assistance and/or a reasonable accommodation due to a disability during the application process, read more about requesting accommodations.

Job Title : Senior Data Scientist Location : Remote Department : Data Science / Analytics / AI & ML Experience : 710 years Employment Type : Summary : Responsibilities We are seeking an experienced and highly motivated Senior Data Scientist with 710 years of industry experience to lead advanced analytics initiatives and drive data-driven decision-making across the organization. The ideal candidate will be skilled in statistical modeling, machine learning, and data engineering, with a strong business sense and the ability to mentor junior team Responsibilities : Lead end-to-end data science projects from problem definition through model deployment. Build, evaluate, and deploy machine learning models and statistical algorithms to solve complex business problems. Collaborate with cross-functional teams including Product, Engineering, and Business stakeholders to integrate data science solutions. Work with large, complex datasets using modern data tools (e.g., Spark, SQL, Airflow). Translate complex analytical results into actionable insights and present them to non-technical audiences. Mentor junior data scientists and provide technical guidance. Stay current with the latest trends in AI/ML, data science, and data engineering. Ensure reproducibility, scalability, and performance of machine learning systems in Qualifications : Bachelors or Masters degree in Computer Science, Statistics, Mathematics, Engineering, or a related field. PhD is a plus. 710 years of experience in data science, machine learning, or applied statistics roles. Strong programming skills in Python and/or R; proficiency in SQL. Deep understanding of statistical techniques, hypothesis testing, and predictive modeling. Hands-on experience with ML libraries such as scikit-learn, TensorFlow, PyTorch, XGBoost, etc. Familiarity with data processing tools like Spark, Hadoop, or equivalent. Experience deploying models into production environments (APIs, MLOps, CI/CD pipelines). Excellent communication skills and ability to convey technical insights to business audiences. Experience working in cloud environments such as AWS, GCP, or Azure. (ref:hirist.tech)

Job Title: Manager – AI & Data Science Location: India (Remote/Hybrid) Reports To: Director – AI & Data Science / Engagement Lead About the Role We are seeking a skilled and proactive Manager – AI & Data Science to lead day-to-day delivery, innovation, and client engagement for our AI-driven marketing measurement and optimization programs (including MMO and IMT/ MIO). The role requires a hands-on leader who can manage a high-performing team, ensure flawless execution, and contribute to ongoing enhancement of AI/ML solutions that drive value for our clients and their partners. Key Responsibilities Project Leadership: Oversee delivery of AI/ML solutions, including Media Mix Optimization (MMO), Intelligent Media Targeting (IMT/MIO), and related marketing analytics initiatives. Client Engagement: Act as the primary point of contact for operational matters, collaborating closely with client stakeholders, media teams, and partner agencies. Solution Delivery: Ensure on-time, high-quality delivery of models, insights, and tools; manage model development, testing, deployment, and monitoring. Team Management: Lead and mentor a team of data scientists and analysts, fostering a culture of excellence, innovation, and accountability. Operational Excellence: Drive process improvements, documentation, and adoption of best practices across MLOps, data engineering, and analytics workflows. Innovation: Support the evolution of the company's AI product suite, contributing ideas and driving proof-of-concept initiatives (e.g., agentic AI, automation modules). Required Qualifications Master’s or Bachelor’s degree in Data Science, Computer Science, Statistics, Engineering, or related field. 8-10 years of experience in AI/ML, data science, or advanced analytics, including 3+ years in a managerial or technical leadership role. Demonstrated experience delivering AI/ML solutions in marketing analytics, media measurement, or optimization domains. Strong proficiency in machine learning frameworks (e.g., scikit-learn, XGBoost, TensorFlow, PyTorch) and data tools (e.g., SQL, Python, Spark). Exposure to MLOps principles, cloud platforms (e.g., Azure, GCP), and model deployment best practices. Excellent communication skills and ability to engage effectively with both technical and non-technical stakeholders. Preferred Skills Experience with media mix modeling (MMM), attribution models, or marketing effectiveness solutions. Understanding of ad platforms (e.g., Google, Meta, DV360) and integration of AI insights into media planning. Familiarity with Generative AI / LLM applications (nice to have). Prior exposure to working with global clients in a complex stakeholder environment. Why Join Us Opportunity to lead high-impact AI initiatives for a global industry leader. Work with cutting-edge tools and solutions in a highly collaborative, innovative environment. Grow your career through mentorship, learning, and exposure to enterprise-scale AI products.

As a Lead Data Scientist at our company, you will play a crucial role in our AI/ML team by leveraging your deep expertise in Generative AI, large language models (LLMs), and end-to-end ML engineering. Your responsibilities will involve designing and developing intelligent systems using advanced NLP techniques and modern ML practices. You will be a key player in building and optimizing ML pipelines and AI systems across various domains, as well as designing and deploying RAG architectures and intelligent chatbots. Collaboration with cross-functional teams to integrate AI components into scalable applications will be essential, along with providing technical leadership, conducting code reviews, and mentoring junior team members. You will drive experimentation with prompt engineering, agentic workflows, and domain-driven designs, while ensuring best practices in testing, clean architecture, and model reproducibility. To excel in this role, you must possess expertise in AI/ML, including Machine Learning, NLP, Deep Learning, and Generative AI (GenAI). Proficiency in working with the LLM stack, such as GPT, Chatbots, Prompt Engineering, and RAG, is required. Strong programming skills in Python, familiarity with essential libraries like Pandas, NumPy, and Scikit-learn, and experience with architectures like Agentic AI, DDD, TDD, and Hexagonal Architecture are essential. You should be comfortable with tooling and deployment using Terraform, Docker, REST/gRPC APIs, and Git, and have experience working on cloud platforms like AWS, GCP, or Azure. Familiarity with AI coding tools like Copilot, Tabnine, and hands-on experience with distributed training in NVIDIA GPU-enabled environments are necessary. A proven track record of managing the full ML lifecycle from experimentation to deployment is crucial for success in this position. Additionally, experience with vector databases, knowledge of GenAI frameworks like LangChain and LlamaIndex, contributions to open-source GenAI/ML projects, and skills in performance tuning of LLMs and custom models are considered advantageous. If you are passionate about leveraging AI technologies to deliver real-world solutions, we are excited to discuss how you can contribute to our cutting-edge AI/ML team.,

We are seeking for apassionate and skilled Python AI Engineer to design, develop and maintain hybrid AI Platform across multi-cloud and on-premises. Build an AI platform that enables real time machine learning and GenAI at scale along with governance and security frameworks.You will collaborate with data engineer, product managers, and software engineers to bring AI-driven products and features to life. Job description Work with frameworks like TensorFlow/PyTorch, Scikit-learn, or similar. Design and implement AI/ML models and algorithms using Python3. Develop and maintain scalable, production-grade machine learning pipelines. Conduct data exploration, preprocessing, feature engineering, and model evaluation. Optimize models for performance and scalability in production environments. Collaborate with cross-functional teams to integrate AI components into real-world applications. Stay up to date with the latest research and industry trends in AI and machine learning. Document experiments, code, and processes for reproducibility and transparency. Required education Bachelor's Degree Preferred education Master's Degree Required technical and professional expertise Strong programming skills in Python 3. Solid understanding of machine learning fundamentals (classification, regression, clustering, etc.). Experience with ML libraries and frameworks (e.g., Scikit-learn, TensorFlow/PyTorch, XGBoost, etc.). Experience in NLP related to Semantic models/Search using BERT/ transformer model. Experience with Gen AI ecosystem/tools is a plus. Experience in data wrangling using Pandas/Polaris, NumPy, SQL, etc. Good grasp of software engineering principles (version control, testing, modular code). Preferred technical and professional experience Familiarity with REST APIs and deployment practices (Dockerized Container, Flask/FastAPI, etc.). Understanding of cloud platforms (AWS, GCP, Azure) is a plus. Problem-SolvingExcellent analytical and problem-solving skills, with the ability to think critically and creatively. CommunicationStrong interpersonal and communication skills, with the ability to work effectively in a collaborative team environment

At EY, you’ll have the chance to build a career as unique as you are, with the global scale, support, inclusive culture and technology to become the best version of you. And we’re counting on your unique voice and perspective to help EY become even better, too. Join us and build an exceptional experience for yourself, and a better working world for all. Position Name ML Developer Taleo ID Position Level Staff Employment Type Permanent Number of Openings 1 Work Location Kochi, Chennai , Noida , Bangalore , Pune , Kolkata , TVM Position Details As part of EY GDS Assurance Digital, you will be responsible for leveraging advanced machine learning techniques to develop innovative, high-impact models and solutions that drive growth and deliver significant business value. You will be helping EY’s sector and service line professionals by developing analytics enabled solutions, integrating data science activities with business relevant aspects to gain insight from data. This is a full-time Machine Learning Developer role, responsible for building and deploying robust machine learning models to solve real-world business problems. You will be working on the entire ML lifecycle, including data analysis, feature engineering, model training, evaluation, and deployment. Requirements (including Experience, Skills And Additional Qualifications) A bachelor’s degree (BE/BTech/MCA & MBA) in Computer Science, Engineering, Information Systems Management, Accounting, Finance or a related field with adequate industry experience. Technical Skills Requirements Develop and implement machine learning models, including regression, classification (e.g., XGBoost, Random Forest), and clustering techniques. Conduct exploratory data analysis (EDA) to uncover insights and trends within data sets. Apply dimension reduction techniques to improve model performance and interpretability. Utilize statistical models to design and implement effective business solutions. Evaluate and validate models to ensure robustness and reliability. Should have solid background in Python Familiarity with Time Series Forecasting. Basic experience with cloud platforms such as AWS, Azure, or GCP. Exposure to ML Ops tools and practices (e.g., MLflow, Airflow, Docker) is a plus Additional skill requirements: Proficient at quickly understanding complex machine learning concepts and utilizing technology for tasks such as data modeling, analysis, visualization, and process automation. Skilled in selecting and applying the most suitable standards, methods, tools, and frameworks for specific ML tasks and use cases. Capable of collaborating effectively within cross-functional teams, while also being able to work independently on complex ML projects. Demonstrates a strong analytical mindset and systematic approach to solving machine learning challenges. Excellent communication skills, able to present complex technical concepts clearly to both technical and non-technical audiences. What we look for A Team of people with commercial acumen, technical experience, and enthusiasm to learn new things in this fast-moving environment. An opportunity to be a part of market-leading, multi-disciplinary team of 7200 + professionals, in the only integrated global assurance business worldwide. Opportunities to work with EY GDS Assurance practices globally with leading businesses across a range of industries What working at EY offers At EY, we’re dedicated to helping our clients, from startups to Fortune 500 companies — and the work we do with them is as varied as they are. You get to work with inspiring and meaningful projects. Our focus is education and coaching alongside practical experience to ensure your personal development. We value our employees, and you will be able to control your own development with an individual progression plan. You will quickly grow into a responsible role with challenging and stimulating assignments. Moreover, you will be part of an interdisciplinary environment that emphasizes high quality and knowledge exchange. Plus, we offer: Support, coaching and feedback from some of the most engaging colleagues around Opportunities to develop new skills and progress your career The freedom and flexibility to handle your role in a way that’s right for you About EY As a global leader in assurance, tax, transaction, and advisory services, we’re using the finance products, expertise, and systems we’ve developed to build a better working world. That starts with a culture that believes in giving you the training, opportunities, and creative freedom to make things better. Whenever you join, however long you stay, the exceptional EY experience lasts a lifetime. And with a commitment to hiring and developing the most passionate people, we’ll make our ambition to be the best employer by 2020 a reality. If you can confidently demonstrate that you meet the criteria above, please contact us as soon as possible. Join us in building a better working world. Apply now EY provides equal employment opportunities to applicants and employees without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, protected veteran status, or disability status. EY | Building a better working world EY exists to build a better working world, helping to create long-term value for clients, people and society and build trust in the capital markets. Enabled by data and technology, diverse EY teams in over 150 countries provide trust through assurance and help clients grow, transform and operate. Working across assurance, consulting, law, strategy, tax and transactions, EY teams ask better questions to find new answers for the complex issues facing our world today.

At EY, you’ll have the chance to build a career as unique as you are, with the global scale, support, inclusive culture and technology to become the best version of you. And we’re counting on your unique voice and perspective to help EY become even better, too. Join us and build an exceptional experience for yourself, and a better working world for all. Position Name ML Developer Taleo ID Position Level Staff Employment Type Permanent Number of Openings 1 Work Location Kochi, Chennai , Noida , Bangalore , Pune , Kolkata , TVM Position Details As part of EY GDS Assurance Digital, you will be responsible for leveraging advanced machine learning techniques to develop innovative, high-impact models and solutions that drive growth and deliver significant business value. You will be helping EY’s sector and service line professionals by developing analytics enabled solutions, integrating data science activities with business relevant aspects to gain insight from data. This is a full-time Machine Learning Developer role, responsible for building and deploying robust machine learning models to solve real-world business problems. You will be working on the entire ML lifecycle, including data analysis, feature engineering, model training, evaluation, and deployment. Requirements (including Experience, Skills And Additional Qualifications) A bachelor’s degree (BE/BTech/MCA & MBA) in Computer Science, Engineering, Information Systems Management, Accounting, Finance or a related field with adequate industry experience. Technical Skills Requirements Develop and implement machine learning models, including regression, classification (e.g., XGBoost, Random Forest), and clustering techniques. Conduct exploratory data analysis (EDA) to uncover insights and trends within data sets. Apply dimension reduction techniques to improve model performance and interpretability. Utilize statistical models to design and implement effective business solutions. Evaluate and validate models to ensure robustness and reliability. Should have solid background in Python Familiarity with Time Series Forecasting. Basic experience with cloud platforms such as AWS, Azure, or GCP. Exposure to ML Ops tools and practices (e.g., MLflow, Airflow, Docker) is a plus Additional skill requirements: Proficient at quickly understanding complex machine learning concepts and utilizing technology for tasks such as data modeling, analysis, visualization, and process automation. Skilled in selecting and applying the most suitable standards, methods, tools, and frameworks for specific ML tasks and use cases. Capable of collaborating effectively within cross-functional teams, while also being able to work independently on complex ML projects. Demonstrates a strong analytical mindset and systematic approach to solving machine learning challenges. Excellent communication skills, able to present complex technical concepts clearly to both technical and non-technical audiences. What we look for A Team of people with commercial acumen, technical experience, and enthusiasm to learn new things in this fast-moving environment. An opportunity to be a part of market-leading, multi-disciplinary team of 7200 + professionals, in the only integrated global assurance business worldwide. Opportunities to work with EY GDS Assurance practices globally with leading businesses across a range of industries What working at EY offers At EY, we’re dedicated to helping our clients, from startups to Fortune 500 companies — and the work we do with them is as varied as they are. You get to work with inspiring and meaningful projects. Our focus is education and coaching alongside practical experience to ensure your personal development. We value our employees, and you will be able to control your own development with an individual progression plan. You will quickly grow into a responsible role with challenging and stimulating assignments. Moreover, you will be part of an interdisciplinary environment that emphasizes high quality and knowledge exchange. Plus, we offer: Support, coaching and feedback from some of the most engaging colleagues around Opportunities to develop new skills and progress your career The freedom and flexibility to handle your role in a way that’s right for you About EY As a global leader in assurance, tax, transaction, and advisory services, we’re using the finance products, expertise, and systems we’ve developed to build a better working world. That starts with a culture that believes in giving you the training, opportunities, and creative freedom to make things better. Whenever you join, however long you stay, the exceptional EY experience lasts a lifetime. And with a commitment to hiring and developing the most passionate people, we’ll make our ambition to be the best employer by 2020 a reality. If you can confidently demonstrate that you meet the criteria above, please contact us as soon as possible. Join us in building a better working world. Apply now EY provides equal employment opportunities to applicants and employees without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, protected veteran status, or disability status. EY | Building a better working world EY exists to build a better working world, helping to create long-term value for clients, people and society and build trust in the capital markets. Enabled by data and technology, diverse EY teams in over 150 countries provide trust through assurance and help clients grow, transform and operate. Working across assurance, consulting, law, strategy, tax and transactions, EY teams ask better questions to find new answers for the complex issues facing our world today.

Responsibilities : · Develop and deploy machine learning models to optimize HVAC setpoints, energy consumption, and operational performance. · Design algorithms for predictive maintenance, fault detection, and dynamic thresholding specific to chillers, pumps, cooling towers, and air handling units. · Work with domain experts and controls engineers to integrate data-driven solutions into existing BMS, SCADA, or edge computing platforms. · Analyze historical and real-time sensor data (temperature, pressure, flow, energy) to identify patterns, anomalies, and optimization opportunities. · Build scalable pipelines for data ingestion, cleaning, normalization, and feature engineering using time-series data from HVAC systems. · Conduct what-if analyses and energy simulations to validate model outputs and savings estimates. · Create visualizations, dashboards, and reports that clearly communicate insights and recommendations to technical and non-technical stakeholders. · Collaborate with software engineers to productize algorithms within cloud or on-prem solutions. Requirements : · Bachelor’s or Master’s degree in Data Science, Computer Science, Mechanical Engineering, Energy Systems, or related field. · 3+ years experience applying data science techniques for industrial systems, preferably with HVAC or energy optimization projects. · Strong skills in Python / R / SQL, with libraries such as pandas, scikit-learn, TensorFlow/PyTorch, XGBoost, Neural Network and RL model development. · Proven experience with time-series analysis, forecasting, and anomaly detection. · Knowledge of HVAC equipment, control strategies, and energy efficiency principles. · Hands-on experience with BMS/SCADA/OPC/Modbus/OPC UA data integration. · Familiarity with cloud platforms (AWS, GCP, Azure) and/or edge computing frameworks. · Excellent problem-solving skills, with ability to translate operational challenges into data science solutions. Job Type: Full-time Pay: ₹700,000.00 - ₹900,000.00 per year Schedule: Day shift Application Question(s): What is your expected CTC and notice period? Experience: Total: 3 years (Required) Python: 2 years (Required) SQL: 1 year (Required) Work Location: In person

What you’ll do: Analyze large and complex datasets to discover trends, patterns, and insights. Apply statistical methods and machine learning techniques to extract valuable information from data. Develop and implement machine learning algorithms and models for predictive and prescriptive analysis. Utilize deep learning techniques for complex data analysis tasks. Utilize Python programming language and libraries such as numpy and pandas to manipulate data, conduct analysis, and develop machine learning models. Identify relevant features and perform feature engineering to enhance the performance of machine learning models. Evaluate the performance of machine learning models using appropriate metrics. Fine-tune models for optimal results. Collaborate with cross-functional teams, including data engineers, analysts, and business stakeholders, to understand business requirements and provide data-driven solutions. Maintain detailed documentation of data analysis processes, algorithms, and models. Ensure that documentation is clear, concise, and accessible to relevant team members. What you’ll need: Strong in Python and experience with Jupyter notebooks, Python packages like polars, pandas, numpy, scikit-learn, matplotlib, etc. Experience with machine learning lifecycle, including data preparation, training, evaluation, and deployment Hands-on experience with GCP services for ML & data science Experience with Vector Search and Hybrid Search techniques Experience with embeddings generation using models like BERT, Sentence Transformers, or custom models Experience in embedding indexing and retrieval (e.g., Elastic, FAISS, ScaNN, Annoy) Experience with LLMs and use cases like RAG (Retrieval-Augmented Generation) Understanding of semantic vs lexical search paradigms Experience with Learning to Rank (LTR) techniques and libraries (e.g., XGBoost, LightGBM with LTR support) Should be proficient in SQL and BigQuery for analytics and feature generation Should have experience with Dataproc clusters for distributed data processing using Apache Spark or PySpark Should have experience deploying models and services using Vertex AI, Cloud Run, or Cloud Functions Should be comfortable working with BM25 ranking (via Elasticsearch or OpenSearch) and blending with vector-based approaches Familiarity with Vertex AI Matching Engine for scalable vector retrieval Familiarity with TensorFlow Hub, Hugging Face, or other model repositories Experience with prompt engineering, context windowing, and embedding optimization for LLM-based systems Should understand how to build end-to-end ML pipelines for search and ranking applications Awareness of evaluation metrics for search relevance (e.g., precision@k, recall, nDCG, MRR) Should have exposure to CI/CD pipelines and model versioning practices GCP Tools Experience: ML & AI: Vertex AI, Vertex AI Matching Engine, AutoML, AI Platform Storage: BigQuery, Cloud Storage, Firestore Ingestion: Pub/Sub, Cloud Functions, Cloud Run Search: Vector Databases (e.g., Matching Engine, Qdrant on GKE), Elasticsearch/OpenSearch Compute: Cloud Run, Cloud Functions, Vertex Pipelines, Cloud Dataproc (Spark/PySpark) CI/CD & IaC: GitLab/GitHub Actions Life at Next: At our core, we're driven by the mission of tailoring growth for our customers by enabling them to transform their aspirations into tangible outcomes. We're dedicated to empowering them to shape their futures and achieve ambitious goals. To fulfil this commitment, we foster a culture defined by agility, innovation, and an unwavering commitment to progress. Our organizational framework is both streamlined and vibrant, characterized by a hands-on leadership style that prioritizes results and fosters growth. Perks of working with us: Clear objectives to ensure alignment with our mission, fostering your meaningful contribution. Abundant opportunities for engagement with customers, product managers, and leadership. You'll be guided by progressive paths while receiving insightful guidance from managers through ongoing feedforward sessions. Cultivate and leverage robust connections within diverse communities of interest. Choose your mentor to navigate your current endeavors and steer your future trajectory. Embrace continuous learning and upskilling opportunities through Nexversity. Enjoy the flexibility to explore various functions, develop new skills, and adapt to emerging technologies. Embrace a hybrid work model promoting work-life balance. Access comprehensive family health insurance coverage, prioritizing the well-being of your loved ones. Embark on accelerated career paths to actualize your professional aspirations. Who we are? We enable high growth enterprises build hyper personalized solutions to transform their vision into reality. With a keen eye for detail, we apply creativity, embrace new technology and harness the power of data and AI to co-create solutions tailored made to meet unique needs for our customers. Join our passionate team and tailor your growth with us!

Position Profile: Full-Stack Developer – Investment Analytics Platform We’re building a next-generation investment analysis system — where historical data, sector intelligence, macro signals, and holding trends can be queried using natural language and interpreted through charts, models, and narratives. We are looking for a hands-on developer with experience in: • Structuring scalable databases • Integrating LLMs (like GPT-4) into analytical workflows • Building interactive front ends • Supporting data science-driven discovery and analysis You will work closely with the founders and be part of a small, focused team creating a high-impact internal tool Company : ITUS Capital– an Asset Management firm. (https://ituscapital.com/about-us/ ) Role : Full-Stack Developer – Investment Analytics Platform Reporting to : The Founding Team Location : Chennai Skillset · Experience with Python/Streamlit, PostgreSQL and/or vector databases · 4+ years of experience applying machine‑learning or statistical models (financial markets experience is a plus) · Comfort working with time‑series and cross‑sectional data · Proven ability to design experiments and iterate rapidly on model ideas · Clear communicator who can translate technical insights for non‑technical stakeholders · Exposure to the full ML workflow: feature engineering, validation, tuning, and deployment Relevant work experience in yrs · Candidates should have 4–8 years of hands-on development experience, with a demonstrated track record of: Designing and maintaining data pipelines and time-series databases, preferably in financial or economic domains · Building full-stack analytical applications using Python (FastAPI, Pandas) and React or Streamlit · Working with structured (SQL) and unstructured data (PDFs, text, CSV) for research and analytics · Integrating LLM APIs (e.g., OpenAI, Cohere, Claude) to extract in-sights, generate summaries, or translate queries into code · Implementing retrieval-augmented generation (RAG) flows using vector databases Background industry preference: Finance, Research, Data Science, Technology Responsibilities · Build and maintain a unified data warehouse (20+ years of financial & macro data) · Create data pipelines to ingest returns, fundamentals, macro, and holdings · Develop APIs that connect LLMs to structured data (RAG, SQL → Natural Language) · Integrate ML models (XGBoost, clustering, time-series analytics) into backend · Design front-end interface for interactive querying, pattern discovery, and visualizations · Implement pattern logging, summarization, and export modules · Optimize for performance, security, and modularity

AI/ML Manager: Location – Pune Experience: 8+ years Notice period – Immediate to 30 days. Key Responsibilities: Lead the development of machine learning PoCs and demos using structured/tabular data for use cases such as forecasting, risk scoring, churn prediction, and optimization. Collaborate with sales engineering teams to understand client needs and present ML solutions during pre-sales calls and technical workshops. Build ML workflows using tools such as SageMaker, Azure ML, or Databricks ML and manage training, tuning, evaluation, and model packaging. Apply supervised, unsupervised, and semi-supervised techniques such as XGBoost, CatBoost, k-Means, PCA, time-series models, and more. Work with data engineering teams to define data ingestion, preprocessing, and feature engineering pipelines using Python, Spark, and cloud-native tools. Package and document ML assets so they can be scaled or transitioned into delivery teams post-demo. Stay current with best practices in ML explainability, model performance monitoring, and MLOps practices. Participate in internal knowledge sharing, tooling evaluation, and continuous improvement of lab processes. Qualifications: 8+ years of experience developing and deploying classical machine learning models in production or PoC environments. Strong hands-on experience with Python, pandas, scikit-learn, and ML libraries such as XGBoost, CatBoost, LightGBM, etc. Familiarity with cloud-based ML environments such as AWS SageMaker, Azure ML, or Databricks. Solid understanding of feature engineering, model tuning, cross-validation, and error analysis. Experience with unsupervised learning, clustering, anomaly detection, and dimensionality reduction techniques. Comfortable presenting models and insights to technical and non-technical stakeholders during pre-sales engagements. Working knowledge of MLOps concepts, including model versioning, deployment automation, and drift detection. Interested candidates shall apply or share resumes at kanika.garg@austere.co.in.

About Us Thoucentric is the Consulting arm of Xoriant, a prominent digital engineering services company with 5000 employees. We are headquartered in Bangalore with presence across multiple locations in India, US, UK, Singapore & Australia Globally. As the Consulting business of Xoriant, we help clients with Business Consulting, Program & Project Management, Digital Transformation, Product Management, Process & Technology Solutioning and Execution including Analytics & Emerging Tech areas cutting across functional areas such as Supply Chain, Finance & HR, Sales & Distribution across US, UK, Singapore and Australia. Our unique consulting framework allows us to focus on execution rather than pure advisory. We are working closely with marquee names in the global consumer & packaged goods (CPG) industry, new age tech and start-up ecosystem. Xoriant (Parent entity) started in 1990 and is a Sunnyvale, CA headquartered digital engineering firm with offices in the USA, Europe, and Asia. Xoriant is backed by ChrysCapital, a leading private equity firm. Our strengths are now combined with Xoriants capabilities in AI & Data, cloud, security and operations services proven for 30 years. We have been certified as "Great Place to Work" by AIM and have been ranked as "50 Best Firms for Data Scientists to Work For." We have an experienced consulting team of over 450 world-class business and technology consultants based across six global locations, supporting clients through their expert insights, entrepreneurial approach and focus on delivery excellence. We have also built point solutions and products through Thoucentric labs using AI/ML in the supply chain space. Job Title: Data Scientist (3-5 Years Experience) Location: Bangalore About Us: Thoucentric is a forward-thinking organization at the forefront of leveraging data-driven insights to solve complex business challenges. We are seeking a passionate and skilled Data Scientist to join our dynamic team and help us drive innovation through advanced analytics and machine learning. Key Responsibilities: Develop and implement machine learning and deep learning models for various business problems, with a strong focus on time series forecasting. Analyze large, complex datasets to extract actionable insights and identify trends, patterns, and opportunities for improvement. Design, build, and validate predictive models using state-of-the-art techniques, ensuring scalability and robustness. Collaborate with cross-functional teams (Product, Engineering, Business) to translate business requirements into data science solutions. Communicate findings and recommendations clearly to both technical and non-technical stakeholders. Stay updated with the latest research and advancements in machine learning, deep learning, and time series analysis, and proactively apply new techniques as appropriate. Mentor junior team members and contribute to a culture of continuous learning and innovation. Requirements Required Skills & Qualifications: 3-5 years of hands-on experience in data science, machine learning, and statistical modeling. Strong expertise in time series forecasting (ARIMA, XGBoost, RandomForest, TFT, NHITS, etc.) and familiarity with deep learning frameworks (TensorFlow, PyTorch). Excellent programming skills in Python (preferred), with proficiency in libraries such as NumPy, Pandas, scikit-learn, and visualization tools (Matplotlib, Seaborn, Plotly). Solid conceptual understanding of machine learning algorithms, deep learning architectures, and statistical methods. Experience with data preprocessing, feature engineering, and model evaluation. Ability to learn quickly and adapt to new technologies, tools, and methodologies. Strong problem-solving skills and a keen attention to detail. Excellent communication and presentation skills. Preferred Qualifications: Experience with cloud platforms and MLOps tools. Exposure to big data technologies (Spark, Hadoop) is a plus. Masters degree in Computer Science, Statistics, Mathematics, or a related field. Benefits What a Consulting role at Thoucentric will offer you? Opportunity to define your career path and not as enforced by a manager A great consulting environment with a chance to work with Fortune 500 companies and startups alike. A dynamic but relaxed and supportive working environment that encourages personal development. Be part of One Extended Family. We bond beyond work - sports, get-togethers, common interests etc. Work in a very enriching environment with Open Culture, Flat Organization and Excellent Peer Group. Be part of the exciting Growth Story of Thoucentric! I'm interested Locations: Bangalore North, India | Posted on: 05/02/2025

Job Title: Senior Data Scientist (Advanced Modeling & Machine Learning) Location: Remote Location Preference: We are specifically looking to hire talented individuals from Tier 2 and Tier 3 cities for this opportunity. Job Type: Full-time About the role We are seeking a highly motivated and experienced Senior Data Scientist with a strong background in statistical modeling, machine learning, and natural language processing (NLP). This individual will work on advanced attribution models and predictive algorithms that power strategic decision-making across the business. The ideal candidate will have a Master’s degree in a quantitative field, 4–6 years of hands-on experience, and demonstrated expertise in building models from linear regression to cutting-edge deep learning and large language models (LLMs). A Ph.D. is strongly preferred. Responsibilities Responsible for analyzing the data, identifying patterns, and do a detailed EDA. Build and refine predictive models using techniques such as linear/logistic regression, XGBoost, and neural networks. Leverage machine learning and NLP methods to analyze large-scale structured and unstructured datasets. Apply LLMs and transformers to develop solutions in content understanding, summarization, classification, and retrieval. Collaborate with data engineers and product teams to deploy scalable data pipelines and model production systems. Interpret model results, generate actionable insights, and present findings to technical and non-technical stakeholders. Stay abreast of the latest research and integrate cutting-edge techniques into ongoing projects Required Qualifications Master’s degree in Computer Science, Statistics, Applied Mathematics, or a related field. 4–6 years of industry experience in data science or machine learning roles. Strong statistical foundation, with practical experience in regression modeling, hypothesis testing, and A/B testing. Hands-on knowledge of: > Programming languages : Python (primary), SQL, R (optional) > Libraries : pandas, NumPy, scikit-learn, TensorFlow, PyTorch, XGBoost, LightGBM, spaCy, Hugging Face Transformers > Distributed computing : PySpark, Dask > Big Data and Cloud Platforms : Databricks, AWS Sagemaker, Google Vertex AI, Azure ML > Data Engineering Tools : Apache Spark, Delta Lake, Airflow > ML Workflow & Visualization : MLflow, Weights & Biases, Plotly, Seaborn, Matplotlib > Version control and collaboration : Git, GitHub, Jupyter, VSCode Preferred Qualifications Masters or Ph.D. in a quantitative or technical field. Experience with deploying machine learning pipelines in production using CI/CD tools. Familiarity with containerization (Docker) and orchestration (Kubernetes) in ML workloads. Understanding of MLOps and model lifecycle management best practices. Experience in real-time data processing (Kafka, Flink) and high-throughput ML systems. What We Offer Competitive salary and performance bonuses Flexible working hours and remote options Opportunities for continued learning and research Collaborative, high-impact team environment Access to cutting-edge technology and compute resources To apply, send your resume to jobs@megovation.io to be part of a team pushing the boundaries of data-driven innovation.

The Applications Development Intermediate Programmer Analyst is an intermediate level position responsible for participation in the establishment and implementation of new or revised application systems and programs in coordination with the Technology team. The overall objective of this role is to contribute to applications systems analysis and programming activities. Responsibilities: Utilize knowledge of applications development procedures and concepts, and basic knowledge of other technical areas to identify and define necessary system enhancements, including using script tools and analyzing/interpreting code Consult with users, clients, and other technology groups on issues, and recommend programming solutions, install, and support customer exposure systems Apply fundamental knowledge of programming languages for design specifications. Analyze applications to identify vulnerabilities and security issues, as well as conduct testing and debugging Serve as advisor or coach to new or lower level analysts Identify problems, analyze information, and make evaluative judgements to recommend and implement solutions Resolve issues by identifying and selecting solutions through the applications of acquired technical experience and guided by precedents Has the ability to operate with a limited level of direct supervision. Can exercise independence of judgement and autonomy. Acts as SME to senior stakeholders and /or other team members. Appropriately assess risk when business decisions are made, demonstrating particular consideration for the firm's reputation and safeguarding Citigroup, its clients and assets, by driving compliance with applicable laws, rules and regulations, adhering to Policy, applying sound ethical judgment regarding personal behavior, conduct and business practices, and escalating, managing and reporting control issues with transparency. Key Responsibilities: Design and implement ETL pipelines using PySpark and Big Data tools on platforms like Hadoop, Hive, HDFS etc. Write scalable Python code for Machine Learning preprocessing tasks and work with libraries such as pandas, Scikit-learn etc. Develop data pipelines to support model training, evaluation and inference. Skills: Proficiency in Python programming with experience in PySpark for large-scale data processing. Hands-on experience in Big Data technologies: Hadoop, Hive HDFS etc. Exposure to machine learning workflows, model lifecycle and data preparation. Experience with ML libraries: Scikit-learn, XGBoost, Tensorflow, PyTorch etc. Exposure to cloud platforms (AWS/GCP) for data and AI workloads. Qualifications: 4-8 years of relevant experience in the Financial Service industry Intermediate level experience in Applications Development role Consistently demonstrates clear and concise written and verbal communication Demonstrated problem-solving and decision-making skills Ability to work under pressure and manage deadlines or unexpected changes in expectations or requirements Education: Bachelor’s degree/University degree or equivalent experience This job description provides a high-level review of the types of work performed. Other job-related duties may be assigned as required. - Job Family Group: Technology - Job Family: Applications Development - Time Type: Full time - Most Relevant Skills Please see the requirements listed above. - Other Relevant Skills For complementary skills, please see above and/or contact the recruiter. - Citi is an equal opportunity employer, and qualified candidates will receive consideration without regard to their race, color, religion, sex, sexual orientation, gender identity, national origin, disability, status as a protected veteran, or any other characteristic protected by law. If you are a person with a disability and need a reasonable accommodation to use our search tools and/or apply for a career opportunity review Accessibility at Citi . View Citi’s EEO Policy Statement and the Know Your Rights poster.

Enterprise Technology Group 1003 Job Description Job Title: Head – Data and AI , Enterprise Technology Group Purpose: To lead and build a strong data analytics and AI team that aims to drive the company towards becoming a data-first and data-driven organization by delivering and maintaining smart data-driven solutions crucial for growth and operations. The individual will accelerate the adoption and implementation of AI solutions to enhance efficiency, innovation, and competitive advantage. The position also involves managing all aspects of new data and AI projects from inception to delivery, as well as day-to-day operations, with a strong focus on assessing business value, ROI and reduce cost. Education: Bachelor's or Master's degree in Computer Science, Math / Quantitative Methods / Econometrics / Information Systems Experience and Proficiency : 10+ years of overall technology experience with years in data and years in AI/data science Preferred Skills: Programming languages: Python, R or likes Understanding of algorithms like linear regression, logistic regression, decision and regression trees, random forest, boosting algorithms (e.g., XGBoost), k-means, hierarchical clustering, and principal component analysis Understanding of data science concepts: Statistics, probability, data transformation, visualization, storytelling, deep learning Statistical and Mathematical Methods: Application of statistics and prominent statistical models Good understanding of Data & AI technologies/tools: ML Ops, ETL, data lake, graph databases, NLK, Data Optimization Location: Mumbai – Full-Time work from Office Reporting Relationship: Head – Enterprise Technology Group Business/Channel/Function: Enterprise Technology Group Key Responsibilities: Lead and build a strong data analytics and AI team over time and this should become possible organically by being able to demonstrate value Provide guidance and establish best practices and methodologies for data analytics and responsible AI initiatives. Manage and oversee stages of AI and LLM Projects, from initial assessment to implementation. Build and maintain close working relationships with the Business and Functions Process Owners to gather specific requirements and define the scope of work. Collaborate closely with internal staff, users, and third parties to ensure success. Develop and implement advanced models and algorithms to solve complex business problems. Respond to and resolve data mining performance issues. Monitor data mining system performance and implement efficiency improvements. Stay updated with the latest advancements in AI and LLM technologies and apply them to enhance project outcomes Behavioural Strengths: Excellent analytical, problem-solving, and decision-making skills. Proven ability to lead and inspire teams, driving innovation and achieving results. Exceptional communication and collaboration skills, with the ability to work effectively with diverse stakeholders. Why join us? CulverMax Entertainment Pvt Ltd (Formerly known as Sony Pictures Networks India) is home to some of India’s leading entertainment channels such as SET, SAB, MAX, PAL, PIX, Sony BBC Earth, Yay!, Sony Marathi, Sony SIX, Sony TEN, SONY TEN1, SONY Ten2, SONY TEN3, SONY TEN4, to name a few! Our foray into the OTT space with one of the most promising streaming platforms, Sony LIV brings us one step closer to being a progressive digitally led content powerhouse. Our independent production venture- Studio Next has already made its mark with original content and IPs for TV and Digital Media. But our quest to Go Beyond doesn’t end there. Neither does our search to find people who can take us there. We focus on creating an inclusive and equitable workplace where we celebrate diversity with our Bring Your Own Self Philosophy. We strive to remain an ‘Employer of Choice’ and have been recognized as: India’s Best Companies to Work For 2021 by the Great Place to Work® Institute. - 100 Best Companies for Women in India by AVTAR & Seramount for years in a row - UN Women Empowerment Principles Award 2022 for Gender Responsive Marketplace and Community Engagement & Partnership ET Human Capital Awards 2023 for Excellence in HR Business Partnership & Team Building Engagement ET Future Skills Awards 2022 for Best Learning Culture in an Organization and Best D&I Learning Initiative. The biggest award of course is the thrill our employees feel when they can Tell Stories Beyond the Ordinary!

To lead and build a strong data analytics and AI team that aims to drive the company towards becoming a data-first and data-driven organization by delivering and maintaining smart data-driven solutions crucial for growth and operations. The individual will accelerate the adoption and implementation of AI solutions to enhance efficiency, innovation, and competitive advantage. The position also involves managing all aspects of new data and AI projects from inception to delivery, as well as day-to-day operations, with a strong focus on assessing business value, ROI and reduce cost. Key Responsibilities: Lead and build a strong data analytics and AI team over time and this should become possible organically by being able to demonstrate value Provide guidance and establish best practices and methodologies for data analytics and responsible AI initiatives. Manage and oversee stages of AI and LLM Projects, from initial assessment to implementation. Build and maintain close working relationships with the Business and Functions Process Owners to gather specific requirements and define the scope of work. Collaborate closely with internal staff, users, and third parties to ensure success. Develop and implement advanced models and algorithms to solve complex business problems. Respond to and resolve data mining performance issues. Monitor data mining system performance and implement efficiency improvements. Stay updated with the latest advancements in AI and LLM technologies and apply them to enhance project outcomes Preferred Skills: Programming languages: Python, R or likes Understanding of algorithms like linear regression, logistic regression, decision and regression trees, random forest, boosting algorithms (e.g., XGBoost), k-means, hierarchical clustering, and principal component analysis Understanding of data science concepts: Statistics, probability, data transformation, visualization, storytelling, deep learning Statistical and Mathematical Methods: Application of statistics and prominent statistical models Good understanding of Data & AI technologies/tools: ML Ops, ETL, data lake, graph databases, NLK, Data Optimization

At PwC, our people in data and analytics focus on leveraging data to drive insights and make informed business decisions. They utilise advanced analytics techniques to help clients optimise their operations and achieve their strategic goals. In data analysis at PwC, you will focus on utilising advanced analytical techniques to extract insights from large datasets and drive data-driven decision-making. You will leverage skills in data manipulation, visualisation, and statistical modelling to support clients in solving complex business problems. Driven by curiosity, you are a reliable, contributing member of a team. In our fast-paced environment, you are expected to adapt to working with a variety of clients and team members, each presenting varying challenges and scope. Every experience is an opportunity to learn and grow. You are expected to take ownership and consistently deliver quality work that drives value for our clients and success as a team. As you navigate through the Firm, you build a brand for yourself, opening doors to more opportunities. Skills Examples of the skills, knowledge, and experiences you need to lead and deliver value at this level include but are not limited to: Apply a learning mindset and take ownership for your own development. Appreciate diverse perspectives, needs, and feelings of others. Adopt habits to sustain high performance and develop your potential. Actively listen, ask questions to check understanding, and clearly express ideas. Seek, reflect, act on, and give feedback. Gather information from a range of sources to analyse facts and discern patterns. Commit to understanding how the business works and building commercial awareness. Learn and apply professional and technical standards (e.g. refer to specific PwC tax and audit guidance), uphold the Firm's code of conduct and independence requirements. AI/ML & Credit Risk Analytics Professional – Job Specification Candidate would be responsible for developing, validating, auditing, and maintaining AI/ML-powered credit risk models. Candidates would be expected to support financial institutions in meeting jurisdictional regulatory requirements and their broader risk management initiatives. Multiple positions required; Experience level: 2–6 years of relevant experience Location: Bangalore Role Overview We are looking for high-caliber professionals with strong foundations in credit risk modeling and hands-on experience in AI/ML techniques. The ideal candidate will contribute to the development and validation of regulatory and strategic risk models, while also applying machine learning and generative AI techniques to enhance model accuracy, efficiency, and interpretability. Key Responsibilities Develop, validate, and document credit risk models (PD, LGD, EAD) for retail and wholesale portfolios across regulatory (CECL, IFRS 9, Basel) and business-use contexts. Apply AI/ML algorithms (e.g., LightGBM, XGBoost, Random Forest, Neural Networks) to improve prediction power and model performance beyond traditional approaches. Implement Generative AI and LLM-based applications using RAG pipelines, document intelligence, and model documentation automation. Experience with agentic frameworks like Autogen, LangChain, or similar would be helpful. Experience of development and deployment of models in cloud-based platforms such as Azure, AWS, GCP etc. Design explainable AI solutions by incorporating techniques like SHAP, LIME, and feature attribution methods to enhance transparency in high-stakes modeling environments. Partner with cross-functional teams, including business stakeholders, technology teams, and model governance, to ensure model alignment with business objectives and regulatory expectations. Contribute to innovation initiatives and support proposal development, thought leadership, and solution architecture in the AI/ML space. Required Skills & Experience 2–6 years of total experience, with minimum 2 years in AI/ML or GenAI model development or validation. Strong understanding of credit risk modeling frameworks, scorecard development, and risk metrics (e.g., RWA, Expected Loss, Economic Capital). Proficient in Python and SQL, with hands-on experience using ML libraries such as scikit-learn, Tensorflow, Pytorch and transformer-based LLM packages Familiarity with regulatory standards such as CECL, IFRS 9, CCAR/DFAST, Basel II/III, SR 11-7, and model governance best practices. Exposure to cloud environments (Azure preferred), version control (Git), and workflow automation tools. Experience with credit bureau data, vendor models (e.g., FICO, Moody’s, S&P), and financial benchmarking is a plus. Ability to clearly communicate complex technical content to non-technical stakeholders through reports, dashboards, and presentations. Education & Certifications Master’s degree or higher in Statistics, Mathematics, Economics, Data Science, Engineering, or Finance. Professional certifications such as FRM, CFA, CQF, or in product management equivalent are preferred. Contributions to opensource AI / ML projects and competitions is preferred

At PwC, our people in data and analytics focus on leveraging data to drive insights and make informed business decisions. They utilise advanced analytics techniques to help clients optimise their operations and achieve their strategic goals. In data analysis at PwC, you will focus on utilising advanced analytical techniques to extract insights from large datasets and drive data-driven decision-making. You will leverage skills in data manipulation, visualisation, and statistical modelling to support clients in solving complex business problems. Focused on relationships, you are building meaningful client connections, and learning how to manage and inspire others. Navigating increasingly complex situations, you are growing your personal brand, deepening technical expertise and awareness of your strengths. You are expected to anticipate the needs of your teams and clients, and to deliver quality. Embracing increased ambiguity, you are comfortable when the path forward isn’t clear, you ask questions, and you use these moments as opportunities to grow. AI/ML & Credit Risk Analytics Professional – Job Specification Candidate would be responsible for developing, validating, auditing, and maintaining AI/ML-powered credit risk models. Candidates would be expected to support financial institutions in meeting jurisdictional regulatory requirements and their broader risk management initiatives. Multiple positions required; Experience level: 2–6 years of relevant experience Location: Bangalore Role Overview We are looking for high-caliber professionals with strong foundations in credit risk modeling and hands-on experience in AI/ML techniques. The ideal candidate will contribute to the development and validation of regulatory and strategic risk models, while also applying machine learning and generative AI techniques to enhance model accuracy, efficiency, and interpretability. Key Responsibilities Develop, validate, and document credit risk models (PD, LGD, EAD) for retail and wholesale portfolios across regulatory (CECL, IFRS 9, Basel) and business-use contexts. Apply AI/ML algorithms (e.g., LightGBM, XGBoost, Random Forest, Neural Networks) to improve prediction power and model performance beyond traditional approaches. Implement Generative AI and LLM-based applications using RAG pipelines, document intelligence, and model documentation automation. Experience with agentic frameworks like Autogen, LangChain, or similar would be helpful. Experience of development and deployment of models in cloud-based platforms such as Azure, AWS, GCP etc. Design explainable AI solutions by incorporating techniques like SHAP, LIME, and feature attribution methods to enhance transparency in high-stakes modeling environments. Partner with cross-functional teams, including business stakeholders, technology teams, and model governance, to ensure model alignment with business objectives and regulatory expectations. Contribute to innovation initiatives and support proposal development, thought leadership, and solution architecture in the AI/ML space. Required Skills & Experience 2–6 years of total experience, with minimum 2 years in AI/ML or GenAI model development or validation. Strong understanding of credit risk modeling frameworks, scorecard development, and risk metrics (e.g., RWA, Expected Loss, Economic Capital). Proficient in Python and SQL, with hands-on experience using ML libraries such as scikit-learn, Tensorflow, Pytorch and transformer-based LLM packages Familiarity with regulatory standards such as CECL, IFRS 9, CCAR/DFAST, Basel II/III, SR 11-7, and model governance best practices. Exposure to cloud environments (Azure preferred), version control (Git), and workflow automation tools. Experience with credit bureau data, vendor models (e.g., FICO, Moody’s, S&P), and financial benchmarking is a plus. Ability to clearly communicate complex technical content to non-technical stakeholders through reports, dashboards, and presentations. Education & Certifications Master’s degree or higher in Statistics, Mathematics, Economics, Data Science, Engineering, or Finance. Professional certifications such as FRM, CFA, CQF, or in product management equivalent are preferred. Contributions to opensource AI / ML projects and competitions is preferred

As an experienced Machine Learning Engineer with 5 to 7 years of experience in Pune, you will play a crucial role in developing, training, and fine-tuning Machine Learning models for AI/ML applications. Your responsibilities will include designing and implementing data pipelines for data processing, model training, and inference. You will be tasked with deploying models using MLOps and integrating them with cloud infrastructure. Collaboration with product managers and designers to conceptualize AI-driven features will be an essential part of your role. Additionally, you will be expected to research and implement various ML and AI techniques to improve performance. To excel in this position, you should have proficiency in Python and ML frameworks such as Scikit-learn, XGBoost, TensorFlow, and PyTorch. Experience with SQL and ETL data pipelines, including data processing and feature engineering, is required. Familiarity with Docker and container-based deployments for creating cloud-agnostic products is essential. A strong understanding of AI and Machine Learning concepts, including Supervised Learning, Unsupervised Learning, Deep Learning, and Reinforcement Learning, is crucial. Knowledge of at least one cloud platform (AWS, Azure, GCP) and ML deployment strategies, preferably Azure, is expected. Exposure to LLMs (e.g., OpenAI, Hugging Face, Mistral) and foundation models will be beneficial, along with an understanding of various Statistical models.,

As part of ACL Digital, an ALTEN Group Company, you will be contributing to digital product innovation and engineering by assisting clients in designing and developing cutting-edge products, content and commerce platforms, and digital experiences. Our focus lies in leveraging AI, Cloud, and Mobile technologies to create solutions that drive digital transformation through a design-led approach. By combining strategic design, engineering expertise, and industry knowledge, we empower our clients to navigate the digital landscape and accelerate their growth. With our headquarters in Silicon Valley, ACL Digital is a prominent player in design-led digital experiences, innovation, enterprise modernization, and product engineering services tailored for the Technology, Media & Telecom sectors. With over 50,000 employees worldwide and a presence in more than 30 countries, ALTEN Group fosters a multicultural work environment that values collaboration and knowledge sharing. In India, we operate from various locations including Bangalore, Chennai, Pune, Panjim, Hyderabad, Noida, and Ahmedabad, while in the USA, we have established offices in California, Atlanta, Philadelphia, and Washington states. As a potential candidate for the position, you are expected to possess the following technical skills and competencies: - 4-5 years of relevant experience in the field - Preferred training/certification in Data Science/Machine Learning - Ability to collaborate effectively with technical leads - Strong communication skills with the capability to synthesize conclusions - Proficiency in Data Science concepts and Machine Learning algorithms using tools like Scikit-learn, Numpy, Pandas, Stattools, Tensorflow, PyTorch, XGBoost - Experience in Machine Learning Training and Deployment pipelines - Familiarity with FastAPI/Falsk framework, Docker, Virtual Environment, and Database Operations - Strong analytical and problem-solving abilities - Capacity to excel in a dynamic environment with varying degrees of ambiguity Your role will involve the following responsibilities and competencies: - Applying data mining, quantitative analysis, and statistical techniques to conduct experiments and derive meaningful insights from data - Understanding business use-cases and collecting annotated datasets from various sources to address specific problems - Possessing a robust academic background with analytical skills and exposure to machine learning and information retrieval technologies - Strong programming skills, particularly in languages like Python, C/C++ - Extracting data from primary and secondary sources, performing data tagging, filtering, and cleaning based on business requirements - Managing a well-defined, structured, and clean database - Utilizing data labeling tools to annotate data for machine learning models - Analyzing data using statistical techniques, conducting exploratory analysis, and interpreting results effectively If you are someone who thrives in a fast-paced environment, enjoys solving complex problems, and has a passion for leveraging data to drive innovation, we welcome you to explore this opportunity with us. Warm Regards, Komal Narole,

At Lilly, you are part of a global healthcare leader that is committed to uniting caring with discovery to enhance the lives of people worldwide. With our headquarters in Indianapolis, Indiana, our dedicated team of 39,000 employees collaborates to discover and deliver life-changing medicines, enhance disease understanding and management, and contribute to our communities through philanthropy and volunteerism. Our focus is on making a positive impact on people's lives around the world. As part of our ongoing efforts, we are in the process of developing and internalizing a cutting-edge recommendation engine platform. This platform aims to streamline sales and marketing operations by analyzing diverse data sources, implementing advanced personalization models, and seamlessly integrating with other Lilly operations platforms. The goal is to provide tailored recommendations to our sales and marketing teams at the individual doctor level, enabling informed decision-making and enhancing customer experience. Responsibilities: - Utilize deep learning models to optimize Omnichannel Promotional Sequences for sales teams - Analyze large datasets to identify trends and relevant information for modeling decisions - Translate business problems into statistical problem statements and propose solution approaches - Collaborate with stakeholders to effectively communicate analysis findings - Preference for familiarity with pharmaceutical datasets and industry - Experience in code refactoring, model training, deployment, testing, and monitoring for drift - Optimize model hyperparameters and adapt to new ML techniques for business problem-solving Qualifications: - Bachelor's degree in Computer Science, Statistics, or related field (preferred) - 2-6 years of hands-on experience with data analysis, coding, and result interpretation - Proficiency in coding languages like SQL or Python - Prior experience with ML techniques for recommendation engine models in healthcare sectors - Expertise in Feature Engineering, Selection, and Model Validation on Big Data - Familiarity with cloud technology, particularly AWS, and tools like Tableau and Power BI At Lilly, we are committed to promoting workplace diversity and providing equal opportunities for all individuals, including those with disabilities. If you require accommodation during the application process, please complete the accommodation request form on our website. Join us at Lilly and be part of a team dedicated to making a difference in the lives of people worldwide.,

The role within Niro Money, Data and Analytics team involves translating data into actionable insights to enhance marketing ROI, drive business growth, and improve customer experience for various financial products such as personal loan, home loan, credit card, and insurance. The successful candidate will possess a strong background in data analytics and be capable of providing strategic recommendations to key stakeholders and business leaders. You will lead, mentor, and develop a high-performing team of data analysts and data scientists focused on building decision science models and segmentations to predict customer behaviors. Collaborating with the Partnership & Marketing team, you will conduct marketing experiments to enhance funnel conversion rates. Additionally, you will evaluate the effectiveness of marketing campaigns, identify successful strategies, recommend necessary changes, and oversee the implementation of customer journey-related product enhancements. Creating a culture of collaboration, innovation, and data-driven decision-making across various teams is crucial. You will manage multiple analytics projects concurrently, prioritizing them based on potential business impacts and ensuring timely and accurate completion. Project planning, monitoring, and addressing challenges promptly to keep projects on track are essential responsibilities. Collaborating with Data Engineering, Technology, and Product teams, you will develop and implement data capabilities for conducting marketing experiments and delivering actionable insights at scale. Applicants should hold a Master's degree in statistics, mathematics, data science, economics, or a BTech in computer science or engineering. A minimum of 5 years of hands-on experience in decision science analytics and developing data-driven strategies, preferably in the financial services industry, is required. You should also have at least 2 years of experience in managing and leading teams of data analysts and data scientists. Proficiency in statistical model development within financial service industries, including the use of logistic regression/gradient boosting algorithms with Python packages like Scikit-learn, XGBoost, Stats models, or decision tree tools, is essential. Moreover, candidates should have a minimum of 2 years of practical experience in SQL and Python. A proven track record of making data-driven decisions and solving problems based on analytics is necessary. Familiarity with Snowflake, AWS Athena/S3, Redshift, BI Tools like AWS Quicksight is advantageous. An analytical mindset, the ability to assess complex scenarios, and make data-driven decisions are essential qualities. A creative and curious nature, willingness to learn new tools and techniques, and a data-oriented personality are desired traits. Excellent communication and interpersonal skills are crucial for effectively collaborating with diverse stakeholders.,

Our Purpose Mastercard powers economies and empowers people in 200+ countries and territories worldwide. Together with our customers, we’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 Senior Data Scientist We are the global technology company behind the world’s fastest payments processing network. We are a vehicle for commerce, a connection to financial systems for the previously excluded, a technology innovation lab, and the home of Priceless®. We ensure every employee has the opportunity to be a part of something bigger and to change lives. We believe as our company grows, so should you. We believe in connecting everyone to endless, priceless possibilities. The Mastercard Launch program is aimed at early career talent, to help you develop skills and gain cross-functional work experience. Over a period of 18 months, Launch participants will be assigned to a business unit, learn and develop skills, and gain valuable on the job experience. Mastercard has over 2 billion payment cards issued by 25,000+ banks across 190+ countries and territories, amassing over 10 petabytes of data. Millions of transactions are flowing to Mastercard in real-time providing an ideal environment to apply and leverage AI at scale. The AI team is responsible for building and deploying innovative AI solutions for all divisions within Mastercard securing a competitive advantage. Our objectives include achieving operational efficiency, improving customer experience, and ensuring robust value propositions of our core products (Credit, Debit, Prepaid) and services (recommendation engine, anti-money laundering, fraud risk management, cybersecurity) Role: Gather relevant information to define the business problem Creative thinker capable of linking AI methodologies to identified business challenges Develop AI/ML applications leveraging the latest industry and academic advancements Ability to work cross-functionally, and across borders drawing on a broader team of colleagues to effectively execute the AI agenda All About You: :• Demonstrated passion for AI competing in sponsored challenges such as Kaggle Previous experience with or exposure to: Deep Learning algorithm techniques, open source tools and technologies, statistical tools, and programming environments such as Python, R, and SQL • •Big Data platforms such as Hadoop, Hive, Spark, GPU Clusters for deep learning Classical Machine Learning Algorithms like Logistic Regression, Decision trees, Clustering (K-means, •Hierarchical and Self-organizing Maps), TSNE, PCA, Bayesian models, Time Series ARIMA/ARMA, •Recommender Systems - Collaborative Filtering, FPMC, FISM, Fossil •Deep Learning algorithm techniques like Random Forest, GBM, KNN, SVM, Bayesian, Text Mining techniques, Multilayer Perceptron, Neural Networks – Feedforward, CNN, LSTM’s GRU’s is a plus. •Optimization techniques – Activity regularization (L1 and L2), Adam, Adagrad, Adadelta concepts; Cost •Functions in Neural Nets – Contrastive Loss, Hinge Loss, Binary Cross entropy, Categorical Cross entropy; developed applications in KRR, NLP, Speech and Image processing Deep Learning frameworks for Production Systems like Tensorflow, Keras (for RPD and neural net architecture evaluation), PyTorch and Xgboost, Caffe, and Theono is a plus Concentration in Computer Science 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: Abide by Mastercard’s security policies and practices; Ensure the confidentiality and integrity of the information being accessed; Report any suspected information security violation or breach, and Complete all periodic mandatory security trainings in accordance with Mastercard’s guidelines.