629 Xgboost Jobs - Page 3

Silverpush is at the forefront of AI-powered video advertising, delivering sophisticated video ad solutions that empower brands to achieve impactful campaigns within a privacy-centric environment. Operating across 30+ countries, we specialize in creating contextually relevant advertising experiences that drive genuine engagement and conversion. Silverpush's commitment to innovation and technological advancement enables us to navigate the evolving digital landscape, providing our partners with the tools necessary to connect with audiences on a global scale. We are dedicated to fostering a culture of creativity and excellence, driving the future of ad tech with integrity and foresight. For more information about Silverpush’s innovative advertising solutions, please visit www.silverpush.co. Responsibilities: ● Analyze complex datasets to identify trends, patterns, and correlations, and extract actionable insights that can inform strategic decisions. ● Design and build predictive models using statistical and machine learning techniques (e.g., regression, classification, XGBoost, clustering). ● Research and develop analyses and forecasting and optimization methods across ads performance, content performance modeling, and live experiments. ● Research and prototype using cutting-edge LLM technologies and generative AI to unlock new opportunities in personalization, targeting, and automation. Ideal Candidate Profile ● 3+ years of experience in Data Science, ideally in advertising or media-related domains. ● Degree in a quantitative discipline (e.g., Statistics, Computer Science, Mathematics, Masters in DS). ● Deep experience working with large-scale structured and unstructured data. ● Strong foundation in machine learning and statistical modeling. ● Familiar with building and deploying models in production (basic MLOps knowledge). ● Comfortable with NLP and computer vision, and interested in applying LLMs to real-world use cases. ● Excellent communication skills, with the ability to explain complex concepts to non-technical stakeholders. Technical Skills ● Languages & Tools: Python, PySpark, SQL ● ML Techniques: Regression, Classification, Clustering, Decision Trees, Random Forests, XGBoost, SVM ● LLM Tech: Familiarity with tools like OpenAI, Hugging Face, LangChain, and prompt engineering ● Data Infrastructure: ETL tools, Postgres, BigQuery/Snowflake, S3/GCP ● Statistical Analysis: A/B testing, experiment design, causal inference

Join our fast-paced Corporate Oversight and Governance Technology AI/ML team at J.P. Morgan, where your skills and passion will drive innovation and make a significant impact. We offer unparalleled opportunities for career growth and a collaborative environment where you can thrive and contribute to meaningful projects. As an Applied AI ML Lead within the Corporate Oversight and Governance Technology team, you will solve challenging and impactful problems across a wide range of Corporate functions. You will study complex business problems and apply advanced algorithms to develop, test, and evaluate AI/ML applications or models. Working with the firm's rich data pool using Python/Spark via AWS, you will derive business insights and present them to non-technical audiences, contributing to stronger business programs and improved efficiency. Proactively develop an understanding of key business problems and processes. Execute tasks throughout a model development process including data wrangling/analysis, model training, testing, and selection. Implement optimization strategies to fine-tune generative models for specific NLP use cases, ensuring high-quality outputs in summarization and text generation. Conduct thorough evaluations of generative models (e.g., GPT-4), iterate on model architectures, and implement improvements to enhance overall performance in NLP applications. Implement monitoring mechanisms to track model performance in real-time and ensure model reliability. Communicate AI/ML/LLM/GenAI capabilities and results to both technical and non-technical audiences. Generate structured and meaningful insights from data analysis and modeling exercises and present them in an appropriate format according to the audience. Collaborate with other data scientists and machine learning engineers to deploy machine learning solutions. Carry out ad-hoc and periodic analysis as required by the business stakeholder, model risk function, and other groups. Required Qualifications, Capabilities, and Skills: - Formal training or certification in applied AI/ML concepts and 5+ years of applied experience. - Proficiency in programming languages like Python for model development, experimentation, and integration with OpenAI API. - Experience with machine learning frameworks, libraries, and APIs, such as TensorFlow, PyTorch, Scikit-learn, and OpenAI API. - Experience in building AI/ML models on structured and unstructured data along with model explainability and model monitoring. - Solid understanding of fundamentals of statistics, machine learning (e.g., classification, regression, time series, deep learning, reinforcement learning), and generative model architectures, particularly GANs, VAEs. - Experience with a broad range of analytical toolkits, such as SQL, Spark, Scikit-Learn, and XGBoost. - Experience with graph analytics and neural networks (PyTorch). - Excellent problem-solving, communication (verbal and written), and teamwork skills. Preferred Qualifications, Capabilities, and Skills: - Expertise in building AI/ML models on structured and unstructured data along with model explainability and model monitoring. - Expertise in designing and implementing pipelines using Retrieval-Augmented Generation (RAG). - Familiarity with the financial services industry.,

Red & White Education Pvt Ltd , founded in 2008, is Gujarat's leading educational institute. Accredited by NSDC and ISO, we focus on Integrity, Student-Centricity, Innovation, and Unity. Our goal is to equip students with industry-relevant skills and ensure they are employable globally. Join us for a successful career path. Job Description: Faculties guide students, deliver course materials, conduct lectures, assess performance, and provide mentorship. Strong communication skills and a commitment to supporting students are essential. Key Responsibilities: Deliver high-quality lectures on AI, Machine Learning, and Data Science . Design and update course materials, assignments, and projects. Guide students on hands-on projects, real-world applications, and research work. Provide mentorship and support for student learning and career development. Stay updated with the latest trends and advancements in AI/ML and Data Science. Conduct assessments, evaluate student progress, and provide feedback. Participate in curriculum development and improvements. Skills & Tools: Core Skills: ML, Deep Learning, NLP, Computer Vision, Business Intelligence, AI Model Development, Business Analysis. Programming: Python, SQL (Must), Pandas, NumPy, Excel. ML & AI Tools: Scikit-learn (Must), XGBoost, LightGBM, TensorFlow, PyTorch (Must), Keras, Hugging Face. Data Visualization: Tableau, Power BI (Must), Matplotlib, Seaborn, Plotly. NLP & CV: Transformers, BERT, GPT, OpenCV, YOLO, Detectron2. Advanced AI: Transfer Learning, Generative AI, Business Case Studies. Education & Experience Requirements: Bachelor's/Master’s/Ph.D. in Computer Science, AI, Data Science, or a related field. Minimum 1+ years of teaching or industry experience in AI/ML and Data Science. Hands-on experience with Python, SQL, TensorFlow, PyTorch, and other AI/ML tools. Practical exposure to real-world AI applications, model deployment, and business analytics. Additional Skills: Confident body language and clear communication. Strong classroom management and discipline skills. Punctual, prepared, and passionate about teaching. Open to learning and professional development. Proficient in verbal and written communication. Strong problem-solving, leadership, and decision-making abilities. Positive attitude and ability to work independently. For further information, please feel free to contact 7862813693 us via email at career@rnwmultimedia.edu.in Job Types: Full-time, Permanent Pay: ₹30,000.00 - ₹40,000.00 per month Benefits: Cell phone reimbursement Flexible schedule Leave encashment Paid sick time Paid time off Schedule: Day shift Morning shift Supplemental Pay: Performance bonus Yearly bonus Application Question(s): Current Salary? Experience: Teaching / Mentoring: 1 year (Required) AI: 1 year (Required) ML: 1 year (Required) Data science: 1 year (Required) Location: Ahmedabad, Gujarat (Required) Work Location: In person

As the leader of the data analytics and AI team, you will play a crucial role in driving our organization towards a data-first and data-driven approach. Your primary responsibility will be to deliver and maintain smart data-driven solutions that are essential for our growth and daily operations. By accelerating the adoption of AI solutions, you will enhance efficiency, foster innovation, and gain a competitive advantage for the company. Your role will involve overseeing all aspects of new data and AI projects, from their inception to delivery, with a strong emphasis on assessing business value, ROI, and cost reduction. Your key responsibilities will include leading and developing a robust data analytics and AI team, establishing best practices and methodologies for data analytics and responsible AI initiatives, managing and overseeing AI and LLM projects, building relationships with business process owners, collaborating with internal and external stakeholders, developing advanced models and algorithms, addressing data mining performance issues, and staying updated on the latest advancements in AI and LLM technologies to improve project outcomes. Preferred skills for this role include proficiency in programming languages such as Python, R, or similar, understanding of algorithms like linear regression, logistic regression, decision trees, random forest, boosting algorithms (e.g., XGBoost), clustering techniques, and principal component analysis. Additionally, familiarity with data science concepts including statistics, probability, data transformation, visualization, storytelling, and deep learning, as well as expertise in statistical and mathematical methods and data & AI technologies/tools like ML Ops, ETL, data lakes, graph databases, NLK, and data optimization will be beneficial for success in this position.,

Job Location : Noida Job Role : Sr. AI/ML/ Data Scientist Overview We are seeking a highly skilled and experienced AI/ML Expert to spearhead the design, development, and deployment of advanced artificial intelligence and machine learning models. This role requires a strategic thinker with a deep understanding of ML algorithms, model optimization, and production-level AI systems. You will guide cross-functional teams, mentor junior data scientists, and help shape the AI roadmap to drive innovation and business impact. This role involves statistical analysis, data modeling, and interpreting large sets of data. An AI/ML expert with experience in creating AI models for data intelligence companies who specializes in developing and deploying artificial intelligence and machine learning solutions tailored for data-driven businesses. This expert should possess a strong background in data analysis, statistics, programming, and machine learning algorithms, enabling them to design innovative AI models that can extract valuable insights and patterns from vast amounts of data. About The Role The design and development of a cutting-edge application powered by large language models (LLMs). This tool will provide market analysis and generate high-quality, data-driven periodic insights. You will play a critical role in building a scalable and intelligent system that integrates structured data, NLP capabilities, and domain-specific knowledge to produce analyst-grade content. Key Responsibilities Design and develop LLM-based systems for automated market analysis. Build data pipelines to ingest, clean, and structure data from multiple sources (e.g., market feeds, news articles, technical reports, internal datasets). Fine-tune or prompt-engineer LLMs (e.g., GPT-4.5, Llama, Mistral) to generate concise, insightful reports. Collaborate closely with domain experts to integrate industry-specific context and validation into model outputs. Implement robust evaluation metrics and monitoring systems to ensure quality, relevance, and accuracy of generated insights. Develop and maintain APIs and/or user interfaces to enable analysts or clients to interact with the LLM system. Stay up to date with advancements in the GenAI ecosystem and recommend relevant improvements or integrations. Participate in code reviews, experimentation pipelines, and collaborative research Required : Strong fundamentals in machine learning, deep learning, and natural language processing (NLP). Proficiency in Python, with hands-on experience using libraries such as NumPy, Pandas, and Matplotlib/Seaborn for data analysis and visualization. Experience developing applications using LLMs (both closedand open-source models). Familiarity with frameworks like Hugging Face Transformers, LangChain, LlamaIndex, etc. Experience building ML models (e.g., Random Forest, XGBoost, LightGBM, SVMs), along with familiarity in training and validating models. Practical understanding of deep learning frameworks: TensorFlow or PyTorch. Knowledge of prompt engineering, Retrieval-Augmented Generation (RAG), and LLM evaluation strategies. Experience working with REST APIs, data ingestion pipelines, and automation workflows. Strong analytical thinking, problem-solving skills, and the ability to convert complex technical work into business-relevant insights. Preferred Familiarity with the chemical or energy industry, or prior experience in market research/analyst workflows. Exposure to frameworks such as OpenAI Agentic SDK, CrewAI, AutoGen, SmolAgent, etc. Experience deploying ML/LLM solutions to production environments (Docker, CI/CD). Hands-on experience with vector databases such as FAISS, Weaviate, Pinecone, or ChromaDB. Experience with dashboarding tools and visualization libraries (e.g., Streamlit, Plotly, Dash, or Tableau). Exposure to cloud platforms (AWS, GCP, or Azure), including usage of GPU instances and model hosting services. About ChemAnalyst ChemAnalyst is a digital platform, which keeps a real-time eye on the chemicals and petrochemicals market fluctuations, thus, enabling its customers to make wise business decisions. With over 450 chemical products traded globally, we bring detailed market information and pricing data at your fingertips. Our real-time pricing and commentary updates enable users to stay acquainted with new commercial opportunities. Each day, we flash the major happenings around the globe in our news section. Our market analysis section takes it a step further, offering an in-depth evaluation of over 15 parameters including capacity, production, supply, demand gap, company share and among others. Our team of experts analyse the factors influencing the market and forecast the market data for up to the next 10 years. We are a trusted source of information for our international clients, ensuring user-friendly and customized deliveries on time. (ref:hirist.tech)

We are looking for an experienced Data Scientist with a strong background in Retail & E-commerce Analytics , particularly in integrating offline store data into analytics solutions. The ideal candidate will leverage General Analytics , AI/ML , and other advanced data science techniques to bridge the gap between online and offline retail data, enabling smarter business decisions and enhancing customer experiences across both channels. Responsibilities: Offline Store Data Analytics : Analyze and integrate offline store data (sales, foot traffic, inventory, etc.) with online data to provide a holistic view of customer behavior and sales trends. Use AI/ML models to optimize offline store performance by forecasting demand, inventory needs, and staffing levels based on historical data. Analyze the impact of offline marketing campaigns and promotions on in-store foot traffic and sales, using predictive analytics and machine learning. Develop models to predict store performance, taking into account various factors like location, weather, local events, and other external variables. Retail & E-commerce Analytics : Use machine learning algorithms and statistical analysis to understand and predict consumer behavior, both in-store and online. Build and maintain models for customer segmentation , personalized marketing , and sales forecasting for both e-commerce and brick-and-mortar stores. Identify key metrics for store performance and customer satisfaction, helping management teams optimize strategies for in-store and online experiences. AI/ML Implementation For Retail Optimization : Apply AI/ML techniques (e.g., classification , regression , clustering , time series forecasting ) to retail data, enabling actionable insights for improving product assortment, pricing, and promotions both online and offline. Develop demand forecasting models for offline stores , ensuring optimal stock levels based on predicted customer needs and sales trends. Use machine learning to enhance inventory management in offline stores by predicting inventory shortages and surplus. Data Integration & Visualization : Work with large datasets from both offline and online sources to clean, integrate, and analyze the data, ensuring data accuracy and consistency. Develop dashboards and visualizations using tools like Tableau , Power BI , or Google Data Studio to communicate key findings and business insights to stakeholders. Create reports that combine insights from offline and online channels, providing a unified view of retail operations. Campaign Performance Analysis : Use data science techniques to analyze the effectiveness of offline marketing campaigns and promotions on both in-store and online traffic, conversion rates, and sales. Evaluate customer engagement with offline campaigns, offering insights into how online and offline channels influence each other. Collaboration With Cross-Functional Teams : Work closely with retail managers, marketing teams, and IT teams to implement data-driven solutions that improve customer experience and business performance. Collaborate with product, marketing, and supply chain teams to optimize the omnichannel strategy , including aligning online and offline inventories and promotions. Key Technical Skills: Machine Learning & AI : Proficiency in Python or R for building and deploying AI/ML models such as random forests , XGBoost , SVM , and neural networks . Strong experience in applying predictive modeling , regression analysis , and time series forecasting to retail data, including demand forecasting and sales prediction. Familiarity with deep learning techniques (e.g., RNNs , LSTMs ) for more complex data patterns, if relevant. Retail & E-commerce Analytics : Experience in analyzing point-of-sale (POS) data , foot traffic data , and customer journey data for offline retail stores. Understanding of e-commerce KPIs and how they integrate with offline store performance metrics. Strong knowledge of inventory optimization , supply chain management , and how they relate to both online and offline retail operations. Big Data & Data Integration : Proficiency in handling and analyzing large datasets from multiple sources (online and offline) using SQL , NoSQL , and cloud platforms like AWS , GCP , or Azure . Ability to work with ETL processes to integrate data from multiple systems, ensuring high-quality data for analysis. Data Visualization & Reporting : Experience with Tableau , Power BI , Google Data Studio , or other visualization tools to present insights and actionable business recommendations. Strong communication skills to present complex findings to both technical and non-technical stakeholders. Statistical Analysis : Proficiency in statistical methods for hypothesis testing, segmentation analysis, and measuring the effectiveness of retail strategies and campaigns. Familiarity with advanced statistical techniques, including Bayesian methods , Monte Carlo simulations , and multivariate testing . Desired Qualifications: Bachelor’s or Master’s degree in Computer Science , Data Science , Statistics , Engineering , or a related field. 5+ years of experience in data science or analytics in the retail or e-commerce industry, with a focus on offline store performance . Proven experience in applying AI/ML models to solve real-world business problems, including demand forecasting, personalization, and campaign optimization. Familiarity with offline store data (sales, foot traffic, inventory) and how it integrates with e-commerce platforms . Strong understanding of the retail industry, particularly in optimizing performance across omnichannel environments (online and offline).

Choosing Capgemini means choosing a company where you will be empowered to shape your career in the way you'd like, where you'll be supported and inspired by a collaborative community of colleagues around the world, and where you'll be able to reimagine what's possible. Join us and help the world's leading organizations unlock the value of technology and build a more sustainable, more inclusive world. Must have experience with Machine Learning Model Development. Expert Level Proficiency in Data Handling (SQL). Hands-on with Model Engineering and Improvement. Strong experience in Model Deployment and Productionalization. Extensive experience in developing and implementing machine learning, Deep Learning, NLP models across various domains. Strong proficiency in Python, including relevant libraries and frameworks for machine learning, such as scikit-learn, XGBoost, and Keras. Ability to write efficient, clean, and scalable code for model development and evaluation. Proven experience in enhancing model accuracy through engineering techniques, such as feature engineering, feature selection, and data augmentation. Ability to analyze model samples in relation to model scores, identify patterns, and iteratively refine models for improved performance. Strong expertise in deploying machine learning models to production systems. Familiarity with the end-to-end process of model deployment, including data preprocessing, model training, optimization, and integration into production environments. We recognise the significance of flexible work arrangements to provide support in a hybrid mode, you will get an environment to maintain a healthy work-life balance. Our focus will be your career growth & professional development to support you in exploring the world of opportunities. Equip yourself with valuable certifications & training programmes in the latest technologies such as AIML, Machine Learning. Capgemini is a global business and technology transformation partner, helping organizations to accelerate their dual transition to a digital and sustainable world, while creating tangible impact for enterprises and society. It is a responsible and diverse group of 340,000 team members in more than 50 countries. With its strong over 55-year heritage, Capgemini is trusted by its clients to unlock the value of technology to address the entire breadth of their business needs. It delivers end-to-end services and solutions leveraging strengths from strategy and design to engineering, all fueled by its market-leading capabilities in AI, generative AI, cloud and data, combined with its deep industry expertise and partner ecosystem.,

We are seeking a skilled and driven AI Developer to create, implement, and launch advanced machine learning models and artificial intelligence solutions. The ideal candidate will possess strong programming abilities, a profound comprehension of machine learning algorithms, and proficiency in model deployment and refinement. Your primary responsibilities will include crafting and executing ML models and AI solutions utilizing suitable algorithms, examining extensive datasets to extract valuable patterns for business decisions, and refining machine learning models to ensure optimal performance. You will also be involved in constructing pipelines for data preprocessing, model training, testing, and deployment, as well as integrating ML models into production through REST APIs, Docker, or cloud services (e.g., AWS SageMaker, GCP AI Platform, Azure ML). Monitoring and enhancing model accuracy, scalability, and dependability post-deployment will also be part of your duties. Collaboration with cross-functional teams comprising product, engineering, and data science professionals to incorporate ML solutions into existing systems is crucial. You will be expected to research and implement new AI methodologies while staying abreast of the latest trends in the field. The ideal candidate should hold a Bachelors or Masters degree in Computer Science, Artificial Intelligence, Data Science, or a related field. Proficiency in Python and libraries like TensorFlow, PyTorch, and Scikit-learn is essential. A solid grasp of supervised, unsupervised, and reinforcement learning techniques is required, along with experience in NLP, computer vision, or time-series forecasting projects. Familiarity with data processing tools such as Pandas, NumPy, and SQL is expected, as well as knowledge of statistics, linear algebra, and probability theory. Experience in deploying models using Flask/FastAPI, Docker, and CI/CD pipelines is preferred. Familiarity with cloud platforms like AWS, GCP, or Azure, as well as proficiency in version control systems (Git) and collaborative tools like JIRA and Confluence, are advantageous. Hands-on experience with MLOps practices, model monitoring tools, Hugging Face Transformers, OpenCV, YOLO, and similar tools will be beneficial. Participation in Kaggle competitions, published papers, or GitHub AI/ML projects is considered a strong advantage. This is a full-time position located in Nagpur with a salary as per market standards. The ideal candidate should have 2-4 years of experience and be below 35 years old. Educational requirements include a Bachelors or Masters degree or equivalent in a relevant field. Proficiency in English and Hindi is required. Please note that there are no specific perks and benefits mentioned for this position.,

As an AI/ML Developer at our Gurugram location, you will be responsible for designing and implementing end-to-end machine learning models using Python for various tasks such as regression, classification, clustering, NLP, and deep learning. Your expertise in developing AI applications based on Machine Learning and Large Language Model (LLM) using tools like LangChain, RAG pipelines, vector databases, and more will be crucial in driving AI innovation. You will work on building and deploying AI applications leveraging technologies such as Retrieval Augmented Generation (RAG), LangChain, LLMs (OpenAI, Huggingface Transformers), and Vector Databases (FAISS, Pinecone, Milvus). Your role will involve developing robust pipelines for semantic search and retrieval chains in real-world production systems, writing clean and efficient Python code, and collaborating with cross-functional teams to deliver scalable AI/ML solutions. If you have front-end skills in React, it would be considered a big plus as you may also contribute to UI components for interactive AI applications. To be successful in this role, you should have at least 5 years of hands-on experience in AI/ML development using Python and a strong knowledge of ML algorithms such as XGBoost, SVM, Random Forests, Logistic Regression, as well as deep learning models like CNNs, RNNs, Transformers (BERT, GPT), and unsupervised learning techniques including K-Means and PCA. Experience with RAG architecture, LangChain, advanced prompt engineering, vector search techniques, and Python libraries like scikit-learn, TensorFlow, PyTorch, and Huggingface Transformers is essential. Proficiency in working with cloud environments such as AWS, Azure, or GCP is also required. It would be nice to have front-end development experience using React.js, familiarity with MLOps tools like MLflow, Kubeflow, Airflow, and knowledge of self-supervised or contrastive learning methods such as SimCLR and CLIP. In this role, you will have the opportunity to work on cutting-edge AI/ML technologies, collaborate in a fast-paced and innovative environment, contribute to impactful production-level AI solutions, and enjoy competitive compensation and benefits.,

Job description Out of the box thinker to build innovative AI/ML models : 1. Understand and analyze requirements requiring Machine Learning Models from Product Owners, Customers, and Other Stakeholders 2. Analyze and verify data quality and features 3. Design solutions by choosing the right algorithms, features, and hyperparameters 4. Manage the full lifecycle of ML Models: Data Acquisition, Feature Engineering, Model Development, Training, Verification, Optimization, Deployment, Versioning 5. Augment Enterprise data with publicly available datasets to enrich models features 6. Create strategies for integrating Whiz.AI platform with external enterprise data sources like Databases, Data Warehouses, Analytical Stores, External ML Systems/Algorithms, Hadoop and ERP/CRM systems. Qualifications Technical 5+ years of experience in implementing Machine Learning and Deep Learning models applied to traditional as well as NLP problems Machine Learning-based models: ANN, SVM, Logistic Regression, Gradient Boosting Time Series Anomaly Detections Methods, Hierarchical or Grouped Time Series Forecasting Knowledge of BERT, LSTMs, RNNs, and HMMs applied to Text classification and Text Generation problems Understanding of ML Data processing frameworks like TensorFlow or PyTorch, XGBoost, SciPy, Scikit-Learn, Apache Spark SQL and handling Big Data, databases Excellent knowledge of Python Programming, NumPy, Pandas, and processing JSON, XML, CSV files Non-Technical Good communication analytical skills Self-driven with a strong sense of ownership urgency Preferred Qualifications Preference will be given to the hands-on Deep Learning and NLP application experience Knowledge of Analytical/OLAP/Columnar, Hadoop Ecosystem and NoSQL databases Deep Learning, GANs, Reinforcement Learning R programming, Matlab Knowledge of Lifesciences or Pharmaceutical Industry dataset Interested candidate can share resume at shwetachouhan@valere.io Job Type: Full-time Pay: From ₹1,500,000.00 per year Benefits: Health insurance Paid sick time Paid time off Provident Fund Education: Bachelor's (Preferred) Experience: software development: 1 year (Preferred) HTML5: 1 year (Preferred) total work: 5 years (Preferred) Work Location: In person

About Firstsource Firstsource is a specialized global business process management partner. We provide transformational solutions and services spanning the customer lifecycle across Healthcare, Banking and Financial Services, Communications, Media and Technology, and other diverse industries.With an established presence in the US, the UK, India, Mexico, Australia, and the Philippines, we act as a trusted growth partner for leading global brands, including several Fortune 500 and FTSE 100 companies. Key Responsibilities Perform data analysis to uncover patterns, trends, and insights to support decision-making. Build, validate, and optimize machine learning models for business use cases in EdTech, Healthcare, BFS and Media. Develop scalable ETL pipelines to preprocess and manage large datasets. Communicate actionable insights through visualizations and reports to stakeholders. Collaborate with engineering teams to implement and deploy models in production (good to have). Core Skills Data Analysis: Expert in Python (Pandas, NumPy), SQL, R, and exploratory data analysis (EDA). Machine Learning: Skilled in Scikit-learn, TensorFlow, PyTorch, and XGBoost for predictive modeling. Statistics: Strong understanding of regression, classification, hypothesis testing, and time-series analysis. Visualization: Proficient in Tableau, Power BI, Matplotlib, and Seaborn. ML Engineering (Good to Have): Experience with model deployment using AWS SageMaker, GCP AI, or Docker. Big Data (Good to Have): Familiarity with Spark, Hadoop, and distributed computing frameworks. ⚠️ Disclaimer: Firstsource follows a fair, transparent, and merit-based hiring process. We never ask for money at any stage. Beware of fraudulent offers and always verify through our official channels or @firstsource.com email addresses.

Job Description: Forecasting Specialist with Expertise in Inventory Management We are looking for a Forecasting Specialist with a strong background in inventory management and data-driven demand forecasting . This role is focused on optimizing inventory levels and enhancing supply chain efficiency through advanced forecasting models and analytical tools. The ideal candidate will bring expertise in statistical forecasting, data analysis, and technical systems to improve retail inventory operations. Responsibilities Statistical Demand Forecasting : Utilize advanced statistical techniques (e.g., ARIMA , exponential smoothing , seasonal decomposition , regression models ) to create accurate demand forecasts and inventory plans. Inventory Optimization : Apply mathematical models like EOQ (Economic Order Quantity) , Safety Stock Calculation , and Replenishment Algorithms to optimize inventory levels and minimize holding costs. Data Analysis & Reporting : Extract and analyze large datasets from various sources, utilizing SQL and advanced analytics tools to forecast trends, detect anomalies, and ensure inventory alignment with demand. Forecasting Model Development : Continuously develop, refine, and evaluate statistical models to improve forecasting accuracy and adapt to changing consumer behavior. System Integration : Work with ERP systems (e.g., SAP , Oracle ) and integrate them with forecasting platforms (e.g., Demand Works , Forecast Pro ) to streamline inventory management processes and ensure real-time data synchronization. Automation and Scripting : Write Python or R scripts to automate data extraction, cleaning, analysis, and forecasting tasks. Data Visualization & Communication : Leverage tools like Power BI , Tableau , or Google Data Studio to build dashboards that present inventory insights and forecasting accuracy to stakeholders in an actionable format. Continuous Improvement : Apply machine learning techniques (e.g., regression models , decision trees , ensemble methods ) to enhance forecasting models and adapt to new retail trends. Key Technical Skills Statistical Tools & Forecasting : Expertise in R or Python for statistical analysis and time series forecasting. In-depth knowledge of forecasting techniques (ARIMA, Holt-Winters, Exponential Smoothing). Understanding of advanced regression and machine learning algorithms applied to demand prediction and trend analysis. SQL & Database Management Proficiency in writing complex SQL queries to extract and manipulate data from inventory and sales databases (MySQL, PostgreSQL, etc.). Experience working with relational databases and cloud-based solutions for inventory data management. Inventory Optimization Algorithms Advanced understanding of inventory models such as ABC Classification , Just-In-Time (JIT) , Reorder Point (ROP) , Safety Stock Optimization , and Vendor-Managed Inventory (VMI) . Ability to apply algorithms to dynamically adjust reorder quantities based on fluctuating demand. Data Visualization & Business Intelligence Expertise in data visualization tools like Power BI to present key performance metrics and inventory analytics to non-technical stakeholders. Ability to create interactive dashboards that display key inventory KPIs (e.g., stock levels, turnover rates, and demand forecasts). Automation & Scripting Proficient in Python (pandas, NumPy) or R for scripting and automating inventory analysis and forecasting processes. Experience with Jupyter Notebooks or RStudio for developing reproducible analysis workflows. Additional Skills Machine Learning (ML) : Knowledge of machine learning algorithms (e.g., XGBoost , Random Forests , Neural Networks ) for improving predictive accuracy in demand forecasting. Desired Qualifications Bachelor's degree in Statistics , Computer Science , Supply Chain Management , or a related field. Proven experience in a similar technical forecasting or inventory management role, preferably in a retail or e-commerce setting. Strong problem-solving skills and a keen attention to detail in data quality and accuracy. This is a high-impact, technical role where you will leverage your expertise in statistical forecasting , data analysis , and inventory optimization to drive significant improvements in retail inventory management systems. If you are passionate about using advanced data science techniques to solve complex supply chain problems, we encourage you to apply.

Salary : 25 to 40 LPA Exp: 4 to 8 years Location :/Gurugram/Bangalore/Hyderabad Notice: Immediate to 30 days..!! Roles & responsibilities: 3+ years exp on Python , ML and Banking model development Interact with the client to understand their requirements and communicate / brainstorm solutions, model Development: Design, build, and implement credit risk model. Contribute to how analytical approach is structured for specification of analysis Contribute insights from conclusions of analysis that integrate with initial hypothesis and business objective. Independently address complex problems 3+ years exp on ML/Python (predictive modelling) . Design, implement, test, deploy and maintain innovative data and machine learning solutions to accelerate our business. Create experiments and prototype implementations of new learning algorithms and prediction techniques Collaborate with product managers, and stockholders to design and implement software solutions for science problems Use machine learning best practices to ensure a high standard of quality for all of the team deliverables Has experience working on unstructured data ( text ): Text cleaning, TFIDF, text vectorization Hands-on experience with IFRS 9 models and regulations. Data Analysis: Analyze large datasets to identify trends and risk factors, ensuring data quality and integrity. Statistical Analysis: Utilize advanced statistical methods to build robust models, leveraging expertise in R programming. Collaboration: Work closely with data scientists, business analysts, and other stakeholders to align models with business needs. Continuous Improvement: Stay updated with the latest methodologies and tools in credit risk modeling and R programming.

Salary : 20 to 35 LPA Exp: 3 to 8 years Location :/Gurugram/Bangalore/Hyderabad Notice: Immediate to 30 days..!! Roles & responsibilities: 3+ years exp on Python , ML and Banking model development Interact with the client to understand their requirements and communicate / brainstorm solutions, model Development: Design, build, and implement credit risk model. Contribute to how analytical approach is structured for specification of analysis Contribute insights from conclusions of analysis that integrate with initial hypothesis and business objective. Independently address complex problems 3+ years exp on ML/Python (predictive modelling) . Design, implement, test, deploy and maintain innovative data and machine learning solutions to accelerate our business. Create experiments and prototype implementations of new learning algorithms and prediction techniques Collaborate with product managers, and stockholders to design and implement software solutions for science problems Use machine learning best practices to ensure a high standard of quality for all of the team deliverables Has experience working on unstructured data ( text ): Text cleaning, TFIDF, text vectorization Hands-on experience with IFRS 9 models and regulations. Data Analysis: Analyze large datasets to identify trends and risk factors, ensuring data quality and integrity. Statistical Analysis: Utilize advanced statistical methods to build robust models, leveraging expertise in R programming. Collaboration: Work closely with data scientists, business analysts, and other stakeholders to align models with business needs. Continuous Improvement: Stay updated with the latest methodologies and tools in credit risk modeling and R programming.

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 Analyst, Inclusive Innovation & Analytics, Center for Inclusive Growth 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. The Center for Inclusive Growth is the social impact hub at Mastercard. The organization seeks to ensure that the benefits of an expanding economy accrue to all segments of society. Through actionable research, impact data science, programmatic grants, stakeholder engagement and global partnerships, the Center advances equitable and sustainable economic growth and financial inclusion around the world. The Center’s work is at the heart of Mastercard’s objective to be a force for good in the world. Reporting to Vice President, Inclusive Innovation & Analytics, the Analyst, will 1) create and/or scale data, data science, and AI solutions, methodologies, products, and tools to advance inclusive growth and the field of impact data science, 2) work on the execution and implementation of key priorities to advance external and internal data for social strategies, and 3) manage the operations to ensure operational excellence across the Inclusive Innovation & Analytics team. Key Responsibilities Data Analysis & Insight Generation Design, develop, and scale data science and AI solutions, tools, and methodologies to support inclusive growth and impact data science. Analyze structured and unstructured datasets to uncover trends, patterns, and actionable insights related to economic inclusion, public policy, and social equity. Translate analytical findings into insights through compelling visualizations and dashboards that inform policy, program design, and strategic decision-making. Create dashboards, reports, and visualizations that communicate findings to both technical and non-technical audiences. Provide data-driven support for convenings involving philanthropy, government, private sector, and civil society partners. Data Integration & Operationalization Assist in building and maintaining data pipelines for ingesting and processing diverse data sources (e.g., open data, text, survey data). Ensure data quality, consistency, and compliance with privacy and ethical standards. Collaborate with data engineers and AI developers to support backend infrastructure and model deployment. Team Operations Manage team operations, meeting agendas, project management, and strategic follow-ups to ensure alignment with organizational goals. Lead internal reporting processes, including the preparation of dashboards, performance metrics, and impact reports. Support team budgeting, financial tracking, and process optimization. Support grantees and grants management as needed Develop briefs, talking points, and presentation materials for leadership and external engagements. Translate strategic objectives into actionable data initiatives and track progress against milestones. Coordinate key activities and priorities in the portfolio, working across teams at the Center and the business as applicable to facilitate collaboration and information sharing Support the revamp of the Measurement, Evaluation, and Learning frameworks and workstreams at the Center Provide administrative support as needed Manage ad-hoc projects, events organization Qualifications Bachelor’s degree in Data Science, Statistics, Computer Science, Public Policy, or a related field. 2–4 years of experience in data analysis, preferably in a mission-driven or interdisciplinary setting. Strong proficiency in Python and SQL; experience with data visualization tools (e.g., Tableau, Power BI, Looker, Plotly, Seaborn, D3.js). Familiarity with unstructured data processing and robust machine learning concepts. Excellent communication skills and ability to work across technical and non-technical teams. Technical Skills & Tools Data Wrangling & Processing Data cleaning, transformation, and normalization techniques Pandas, NumPy, Dask, Polars Regular expressions, JSON/XML parsing, web scraping (e.g., BeautifulSoup, Scrapy) Machine Learning & Modeling Scikit-learn, XGBoost, LightGBM Proficiency in supervised/unsupervised learning, clustering, classification, regression Familiarity with LLM workflows and tools like Hugging Face Transformers, LangChain (a plus) Visualization & Reporting Power BI, Tableau, Looker Python libraries: Matplotlib, Seaborn, Plotly, Altair Dashboarding tools: Streamlit, Dash Storytelling with data and stakeholder-ready reporting Cloud & Collaboration Tools Google Cloud Platform (BigQuery, Vertex AI), Microsoft Azure Git/GitHub, Jupyter Notebooks, VS Code Experience with APIs and data integration tools (e.g., Airflow, dbt) Ideal Candidate You are a curious and collaborative analyst who believes in the power of data to drive social change. You’re excited to work with cutting-edge tools while staying grounded in the real-world needs of communities and stakeholders. 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. R-253034

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 Analyst, Inclusive Innovation & Analytics, Center for Inclusive Growth 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. The Center for Inclusive Growth is the social impact hub at Mastercard. The organization seeks to ensure that the benefits of an expanding economy accrue to all segments of society. Through actionable research, impact data science, programmatic grants, stakeholder engagement and global partnerships, the Center advances equitable and sustainable economic growth and financial inclusion around the world. The Center’s work is at the heart of Mastercard’s objective to be a force for good in the world. Reporting to Vice President, Inclusive Innovation & Analytics, the Analyst, will 1) create and/or scale data, data science, and AI solutions, methodologies, products, and tools to advance inclusive growth and the field of impact data science, 2) work on the execution and implementation of key priorities to advance external and internal data for social strategies, and 3) manage the operations to ensure operational excellence across the Inclusive Innovation & Analytics team. Key Responsibilities Data Analysis & Insight Generation Design, develop, and scale data science and AI solutions, tools, and methodologies to support inclusive growth and impact data science. Analyze structured and unstructured datasets to uncover trends, patterns, and actionable insights related to economic inclusion, public policy, and social equity. Translate analytical findings into insights through compelling visualizations and dashboards that inform policy, program design, and strategic decision-making. Create dashboards, reports, and visualizations that communicate findings to both technical and non-technical audiences. Provide data-driven support for convenings involving philanthropy, government, private sector, and civil society partners. Data Integration & Operationalization Assist in building and maintaining data pipelines for ingesting and processing diverse data sources (e.g., open data, text, survey data). Ensure data quality, consistency, and compliance with privacy and ethical standards. Collaborate with data engineers and AI developers to support backend infrastructure and model deployment. Team Operations Manage team operations, meeting agendas, project management, and strategic follow-ups to ensure alignment with organizational goals. Lead internal reporting processes, including the preparation of dashboards, performance metrics, and impact reports. Support team budgeting, financial tracking, and process optimization. Support grantees and grants management as needed Develop briefs, talking points, and presentation materials for leadership and external engagements. Translate strategic objectives into actionable data initiatives and track progress against milestones. Coordinate key activities and priorities in the portfolio, working across teams at the Center and the business as applicable to facilitate collaboration and information sharing Support the revamp of the Measurement, Evaluation, and Learning frameworks and workstreams at the Center Provide administrative support as needed Manage ad-hoc projects, events organization Qualifications Bachelor’s degree in Data Science, Statistics, Computer Science, Public Policy, or a related field. 2–4 years of experience in data analysis, preferably in a mission-driven or interdisciplinary setting. Strong proficiency in Python and SQL; experience with data visualization tools (e.g., Tableau, Power BI, Looker, Plotly, Seaborn, D3.js). Familiarity with unstructured data processing and robust machine learning concepts. Excellent communication skills and ability to work across technical and non-technical teams. Technical Skills & Tools Data Wrangling & Processing Data cleaning, transformation, and normalization techniques Pandas, NumPy, Dask, Polars Regular expressions, JSON/XML parsing, web scraping (e.g., BeautifulSoup, Scrapy) Machine Learning & Modeling Scikit-learn, XGBoost, LightGBM Proficiency in supervised/unsupervised learning, clustering, classification, regression Familiarity with LLM workflows and tools like Hugging Face Transformers, LangChain (a plus) Visualization & Reporting Power BI, Tableau, Looker Python libraries: Matplotlib, Seaborn, Plotly, Altair Dashboarding tools: Streamlit, Dash Storytelling with data and stakeholder-ready reporting Cloud & Collaboration Tools Google Cloud Platform (BigQuery, Vertex AI), Microsoft Azure Git/GitHub, Jupyter Notebooks, VS Code Experience with APIs and data integration tools (e.g., Airflow, dbt) Ideal Candidate You are a curious and collaborative analyst who believes in the power of data to drive social change. You’re excited to work with cutting-edge tools while staying grounded in the real-world needs of communities and stakeholders. 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. R-253034

Job Requirements Minimum Qualifications: Master's degree in Computer Science, Data Science, or a related field. Ph.D. preferred. 8-12 years of experience in a Data Scientist or equivalent role, with at least 4 years of specialized experience in Generative AI, including experience leading technical development and mentoring teams. Working with financial data and applying NLP techniques, refining prompt engineering strategies for LLMs, collaborating with stakeholders to understand their needs, developing and testing Python code for GenAI solutions, integrating with vector databases, monitoring MLOps pipelines, researching emerging GenAI technologies, and participating in team meetings. Troubleshooting and debugging GenAI models in production. This often requires quickly identifying and resolving issues that arise in real-world deployments. Staying up-to-date with the rapidly evolving GenAI landscape. Continuous learning and exploration of new tools and techniques are essential. Communicating technical concepts clearly to non-technical stakeholders. This involves translating complex AI/ML jargon into understandable business terms. Candidates must possess demonstrable experience in the full lifecycle of real-world, production-level GenAI project implementation. This includes not just developing models but also deploying, monitoring, and maintaining them in a live environment. Proof-of-concept work alone is insufficient. Look for candidates who can articulate the challenges and successes of deploying GenAI solutions at scale. Data structures (lists, dictionaries, sets), algorithms, object-oriented programming, file handling, exception handling. Scientific Computing: NumPy, Pandas, SciPy. Machine Learning: Scikit-learn, XGBoost, LightGBM. Deep Learning: TensorFlow, PyTorch. GenAI: Transformers, LangChain. GenAI Specific Skills, LLM architectures, RAG, Advanced Chatbot Architecturesm Prompt Engineeringm, Fine-tuning LLMs, API Development Expert-level Python skills are mandatory. This includes deep familiarity with core Python, as well as proficiency in key libraries for AI/ML and GenAI applications: Proven ability to design, develop, and deploy complex GenAI projects, from initial concept to production and maintenance. Deep understanding of LLMs, RAG, and advanced chatbot architectures, with practical experience building and deploying robust solutions. Expert-level programming skills in Python, including extensive experience using relevant libraries like TensorFlow, PyTorch, Transformers, and LangChain. Experience designing and implementing scalable API architectures for GenAI applications. Extensive knowledge of Machine Learning concepts, including advanced modeling techniques, model evaluation, and deployment strategies. Expertise in prompt engineering, fine-tuning LLMs, and optimizing performance for specific use cases. Strong technical leadership and mentorship skills, with a demonstrated ability to guide and support other data scientists. Excellent communication and collaboration skills, both written and verbal, with the ability to effectively convey technical concepts to diverse audiences. Preferred Qualifications: Experience with MLOps and building robust AI pipelines. Deep understanding of cloud computing platforms and their application in GenAI. Experience with developing and deploying conversational AI solutions in production environments. Contributions to research and publications in the field of Generative AI. Experience building and managing large datasets for training GenAI models. 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.

Welcome to Warner Bros. Discovery… the stuff dreams are made of. Who We Are… When we say, “the stuff dreams are made of,” we’re not just referring to the world of wizards, dragons and superheroes, or even to the wonders of Planet Earth. Behind WBD’s vast portfolio of iconic content and beloved brands, are the storytellers bringing our characters to life, the creators bringing them to your living rooms and the dreamers creating what’s next… From brilliant creatives, to technology trailblazers, across the globe, WBD offers career defining opportunities, thoughtfully curated benefits, and the tools to explore and grow into your best selves. Here you are supported, here you are celebrated, here you can thrive. Sr. Data Scientist – Job description Meet our team: The Data & Analytics organization is at the forefront of developing and maintaining frameworks, tools, and data products vital to WBD, including flagship streaming product Max and non-streaming products such as Films Group, Sports, News and overall WBD eco-system. Our mission is to foster unified analytics and drive data-driven use cases by leveraging a robust multi-tenant platform and semantic layer. We are committed to delivering innovative solutions that empower teams across the company to catalyze subscriber growth, amplify engagement, and execute timely, informed decisions, ensuring our continued success in an ever-evolving digital landscape. Roles & Responsibilities: The role will focus on building out machine learning solutions for WBD’s Data and Analytics organization. Primary focus will be on unlocking machine learning opportunities and building foundational machine learning training and inference pipelines at scale. You have a deep understanding of different types of data, metrics and KPIs. You will lead by example and define the best practices, will set high standards for the entire team and for the rest of the organization. You have a successful track record for ambitious projects across cross-functional teams. You are passionate and results oriented. You strive for technical excellence and are very hands-on. Your co-workers love working with you. You have built respect in your career through concrete accomplishments. Build cutting-edge capabilities utilizing machine learning and data science (e.g., large language models, computer vision models, advanced ad & content targeting, etc.) Lead data science and model development techniques for the team. Leverage industry best practices and tools to continually improve teams' ability to build machine learning models. What to Bring: BA/BS in statistics, mathematics, economics, industrial engineering, or other quantitative discipline is required. Masters/PhD is a plus 5+ years of experience building data science/statistical models (Multivariate regression, Time Series Model, XGBoost, Causal inference etc.) Strong understanding of modern ML approaches (GBDT, CNN, LSTM, GRU, HRNN, transformers, siamese neural networks, variational auto-encoders, ...). Experience with Deep Learning, NLP, LLMs, Reinforcement Learning, Causal Inference. Good knowledge of ML tools and frameworks (TensorFlow, Keras, pyTorch, scikit-learn, Spark,...). Proficiency in programming languages such as Python or R. Familiarity with real-world ML systems (configuration, data collection, data verification, feature extraction, resource and process management, analytics, training, serving, validation, experimentation, monitoring). Good understanding of operating machine learning solutions at scale, covering the end-to-end ML workflow. Strong interpersonal skills with the ability to motivate, collaborate and influence Ability to deliver on multiple projects and meet tight deadlines Ability to effectively influence and communicate cross-functionally with all level How We Get Things Done… This last bit is probably the most important! Here at WBD, our guiding principles are the core values by which we operate and are central to how we get things done. You can find them at www.wbd.com/guiding-principles/ along with some insights from the team on what they mean and how they show up in their day to day. We hope they resonate with you and look forward to discussing them during your interview. Championing Inclusion at WBD Warner Bros. Discovery embraces the opportunity to build a workforce that reflects a wide array of perspectives, backgrounds and experiences. Being an equal opportunity employer means that we take seriously our responsibility to consider qualified candidates on the basis of merit, regardless of sex, gender identity, ethnicity, age, sexual orientation, religion or belief, marital status, pregnancy, parenthood, disability or any other category protected by law. If you’re a qualified candidate with a disability and you require adjustments or accommodations during the job application and/or recruitment process, please visit our accessibility page for instructions to submit your request.

Job Title: ML Engineer/Data Scientist Duration: 12 Months Location: PAN INDIA Timings: Full Time (As per company timings) Notice Period: within 15 days or immediate joiner Experience: 0- 2 years About The Job We are seeking a highly motivated and experienced ML Engineer/Data Scientist to join our growing ML/GenAI team. You will play a key role in designing, developing ML applications by evaluating models, training and/or fine tuning them. You will play a crucial role in developing Gen AI based solutions for our customers. As a senior member of the team, you will take ownership of projects, collaborating with engineers and stakeholders to ensure successful project delivery. What We're Looking For At least 1-2 years of experience in designing & building AI applications for customer and deploying them into production At least 1-2 years of Software engineering experience in building Secure, scalable and performant applications for customers. Experience with Document extraction using AI, Conversational AI, Vision AI, NLP or Gen AI. Design, develop, and operationalize existing ML models by fine tuning, personalizing it. Evaluate machine learning models and perform necessary tuning. Develop prompts that instruct LLM to generate relevant and accurate responses. Collaborate with data scientists and engineers to analyze and preprocess datasets for prompt development, including data cleaning, transformation, and augmentation. Conduct thorough analysis to evaluate LLM responses, iteratively modify prompts to improve LLM performance. Hands on customer experience with RAG solution or fine tuning of LLM model. Build and deploy scalable machine learning pipelines on GCP or any equivalent cloud platform involving data warehouses, machine learning platforms, dashboards or CRM tools. Experience working with the end-to-end steps involving but not limited to data cleaning, exploratory data analysis, dealing outliers, handling imbalances, analyzing data distributions (univariate, bivariate, multivariate), transforming numerical and categorical data into features, feature selection, model selection, model training and deployment. Proven experience building and deploying machine learning models in production environments for real life applications Good understanding of natural language processing, computer vision or other deep learning techniques. Expertise in Python, Numpy, Pandas and various ML libraries (e.g., XGboost, TensorFlow, PyTorch, Scikit-learn, LangChain). Familiarity with Google Cloud or any other Cloud Platform and its machine learning services. Excellent communication, collaboration, and problem-solving skills. Good to Have Google Cloud Certified Professional Machine Learning or TensorFlow Certified Developer certifications or equivalent. Experience of working with one or more public cloud platforms - namely GCP, AWS or Azure. Experience with Amazon Lex or Google DialogFlow CX or Microsoft Copilot studio for CCAI Agent workflows Experience with AutoML and vision techniques. Master’s degree in statistics, machine learning or related fields.

Job Title: Senior AI Engineer Location: Pune Job Type: Full-Time Experience Required: 4 to 6 years Key Responsibilities: · Design, develop, and deploy scalable AI/ML solutions for real-world problems. · Build and train models using machine learning and deep learning frameworks (TensorFlow, PyTorch, etc.). · Collaborate with cross-functional teams to understand business needs and translate them into technical solutions. · Optimize and fine-tune models for performance and accuracy. · Maintain and monitor deployed models and continuously improve them based on feedback and data. · Conduct research and stay updated with the latest trends in AI and machine learning. · Mentor junior engineers and contribute to best practices in AI development. Requirements: · Strong programming skills in Python ; familiarity with R, Java , or Scala is a plus. · Experience with machine learning libraries (Scikit-learn, XGBoost, LightGBM). · Hands-on experience in deep learning frameworks like TensorFlow, PyTorch , or Keras . · Solid understanding of data preprocessing, feature engineering, model evaluation , and MLOps practices . · Experience with cloud platforms such as AWS, GCP or Azure . · Familiarity with NLP, computer vision or generative AI models is a strong advantage. · Proficiency in using SQL and working with large-scale datasets. Preferred Qualifications : · Bachelor’s or Master’s degree in Computer Science, Data Science, Artificial Intelligence, or related field. · Experience in deploying AI models to production environments. · Knowledge of containerization tools like Docker and orchestration frameworks like Kubernetes . · Experience working in Agile/Scrum development processes. Job Type: Full-time Pay: ₹1,000,000.00 - ₹1,500,000.00 per year Benefits: Provident Fund Ability to commute/relocate: Pune, Maharashtra: Reliably commute or planning to relocate before starting work (Required) Application Question(s): What is your CTC? What is your Expected CTC? What is Your Notice Period? Education: Bachelor's (Preferred) Experience: AI : 4 years (Required) Work Location: In person

Gen AI Lead Engineer JD (5-8 years) Job Description We are seeking a hands-on and forward-thinking Gen AI Lead Engineer with 5-8 years of experience to lead the development of cutting-edge GenAI solutions. You'll work on taking modern large language models (LLMs) from prototype to production, orchestrating multi-agent workflows using advanced frameworks like LlamaIndex Workflows , LangGraph , and structured function calling. An ideal candidate has a strong foundation in classical ML (e.g., XGBoost), deep learning with transformer-based architectures (such as LLaMA and Qwen-family models ), and hands-on experience building Retrieval-Augmented Generation (RAG) pipelines. This role is perfect for someone who thrives at the intersection of research, engineering, and real-world application—owning everything from system design to scalable deployment. Key Responsibilities Design, build, and deploy ML/DL models for: Tabular data (e.g., XGBoost) NLP and GenAI (e.g., RAG, tool/function calling) Fine-tune and serve LLMs using Hugging Face , PyTorch , and efficient-tuning techniques like LoRA , QLoRA , and PEFT . Architect and implement agent-based LLM solutions with tools like LlamaIndex , LangGraph , or LangChain Agents . Design multi-step tool-calling workflows and structured function-calling strategies for complex tasks. Orchestrate agent memory, state management, and contextual conversations. Develop and maintain FastAPI microservices for low-latency GenAI inference, streaming, and secure system integration. Deploy ML pipelines and training jobs in the cloud (preferably Azure , also AWS ). Handle end-to-end MLOps: CI/CD, containerization (Docker), GPU/ACI deployment, observability, and cost governance. Collaborate cross-functionally with product, data, and frontend teams to translate abstract ideas into tangible outcomes. Required Skills & Qualifications Strong Python programming skills; experience with FastAPI and/or Java is a plus. Proven experience with: XGBoost or similar ML models for tabular data. YOLO , OCR , and PyTorch for vision and text extraction tasks. Deep knowledge in NLP / GenAI: LLM fine-tuning, prompt engineering, and RAG design. Proficiency with Hugging Face Transformers , PEFT , and vector databases. Implementation of agent frameworks like LlamaIndex , LangGraph , or LangChain Agents . MLOps & Deployment: Experience with Docker, CI/CD pipelines, experiment tracking, model versioning, and rollback mechanisms. Cloud Proficiency: Azure ML , Azure Functions, AKS (preferred) or AWS SageMaker , Lambda. Bonus : experience with Triton / vLLM, streaming websockets, or GPU cost-optimization. Benefits of Working with Us: Best of Both Worlds: Enjoy the enthusiasm and learning curve of a startup combined with the deliveries and performance of an enterprise service provider. Flexible Working Hours: We offer a delivery-oriented approach with flexible working hours to help you maintain a healthy work-life balance. Limitless Growth Opportunities: The sky is not the limit when it comes to learning, growth, and sharing ideas. We encourage continuous learning and personal development. Flat Organizational Structure: We don't follow the typical corporate hierarchy ladder, fostering an open and collaborative work environment where everyone's voice is heard. As part of our dedication to an inclusive and diverse workforce, TechChefz Digital is committed to Equal Employment Opportunity without regard to race, color, national origin, ethnicity, gender, protected veteran status, disability, sexual orientation, gender identity, or religion. If you need assistance, you may contact us at joinus@techchefz.com

Location: Cyber Towers, Hyderabad & Vijayawada 🏢 Company: Datavalley India Private Limited 📅 Type: Full-Time (Immediate Joiner) 🎓 Education: B.Tech in Computer Science, Data Science, Artificial Intelligence, or related branches 🧪 Experience: 1 - 5 Years About Datavalley.ai: Datavalley.ai is a forward-thinking AI company revolutionizing industries through advanced Machine Learning and Deep Learning solutions. Based in Hyderabad’s tech core, Cyber Towers, we engineer scalable AI systems that transform raw data into powerful business intelligence. At Datavalley.ai, we train fresh minds into AI professionals who build with impact. Roles & Responsibilities: Design and implement Machine Learning and Deep Learning algorithms. Work on data preprocessing, feature engineering, and model evaluation. Build and deploy models using: - Machine Learning: Linear Regression, Logistic Regression, Decision Trees, Random Forest, XGBoost, SVM, K-Means, PCA - Deep Learning: ANN, CNN, RNN, LSTM, Transfer Learning (ResNet, VGG, BERT) - AI Applications: NLP, Computer Vision, Recommendation Systems Use Python and tools like Scikit-learn, TensorFlow, Keras, PyTorch. Collaborate with teams to deploy models using Flask, FastAPI, Streamlit. Skills Required: Strong programming skills in Python Experience with NumPy, Pandas, Matplotlib, Seaborn Knowledge of Scikit-learn, TensorFlow, Keras, PyTorch Understanding of model evaluation metrics (Accuracy, Precision, Recall, F1-score) Familiarity with SQL, basic knowledge of NoSQL (MongoDB) Comfortable with Jupyter/Colab, Git, and version control Basic exposure to Flask/FastAPI for deployment Qualifications: B.Tech in Computer Science, AI & ML, Data Science, or related disciplines Strong foundation in algorithms, mathematics, and statistics Ability to build, train, and evaluate ML/DL models Project or internship in AI/ML is preferred 📩 To Apply: Send your resume to [ artishukla@datavalley.ai ]

Hello, Hope you are doing well. We are Hiring for the role of Sr. AI/ML/ Data Scientist role. Please revert me back with your updated resume at astha.jaiswal@techsciresearch.com if you are interested. Below are the details: Job Location: Noida Job Role: S r. AI/ML/ Data Scientist Overview: We are seeking a highly skilled and experienced AI/ML Expert to spearhead the design, development, and deployment of advanced artificial intelligence and machine learning models. This role requires a strategic thinker with a deep understanding of ML algorithms, model optimization, and production-level AI systems. You will guide cross-functional teams, mentor junior data scientists, and help shape the AI roadmap to drive innovation and business impact. This role involves statistical analysis, data modeling, and interpreting large sets of data. An AI/ML expert with experience in creating AI models for data intelligence companies who specializes in developing and deploying artificial intelligence and machine learning solutions tailored for data-driven businesses. This expert should possess a strong background in data analysis, statistics, programming, and machine learning algorithms, enabling them to design innovative AI models that can extract valuable insights and patterns from vast amounts of data. About the Role The design and development of a cutting-edge application powered by large language models (LLMs). This tool will provide market analysis and generate high-quality, data-driven periodic insights. You will play a critical role in building a scalable and intelligent system that integrates structured data, NLP capabilities, and domain-specific knowledge to produce analyst-grade content. Key Responsibilities Design and develop LLM-based systems for automated market analysis. Build data pipelines to ingest, clean, and structure data from multiple sources (e.g., market feeds, news articles, technical reports, internal datasets). Fine-tune or prompt-engineer LLMs (e.g., GPT-4.5, Llama, Mistral) to generate concise, insightful reports. Collaborate closely with domain experts to integrate industry-specific context and validation into model outputs. Implement robust evaluation metrics and monitoring systems to ensure quality, relevance, and accuracy of generated insights. Develop and maintain APIs and/or user interfaces to enable analysts or clients to interact with the LLM system. Stay up to date with advancements in the GenAI ecosystem and recommend relevant improvements or integrations. Participate in code reviews, experimentation pipelines, and collaborative research discussions. Qualifications Required: Strong fundamentals in machine learning, deep learning, and natural language processing (NLP) . Proficiency in Python , with hands-on experience using libraries such as NumPy, Pandas, and Matplotlib/Seaborn for data analysis and visualization. Experience developing applications using LLMs (both closed- and open-source models) . Familiarity with frameworks like Hugging Face Transformers, LangChain, LlamaIndex , etc. Experience building ML models (e.g., Random Forest, XGBoost, LightGBM, SVMs ), along with familiarity in training and validating models. Practical understanding of deep learning frameworks: TensorFlow or PyTorch . Knowledge of prompt engineering , Retrieval-Augmented Generation (RAG) , and LLM evaluation strategies. Experience working with REST APIs , data ingestion pipelines, and automation workflows. Strong analytical thinking, problem-solving skills, and the ability to convert complex technical work into business-relevant insights. Preferred: Familiarity with the chemical or energy industry , or prior experience in market research/analyst workflows . Exposure to frameworks such as OpenAI Agentic SDK, CrewAI, AutoGen, SmolAgent, etc. Experience deploying ML/LLM solutions to production environments (Docker, CI/CD) . Hands-on experience with vector databases such as FAISS, Weaviate, Pinecone , or ChromaDB . Experience with dashboarding tools and visualization libraries (e.g., Streamlit, Plotly, Dash, or Tableau). Exposure to cloud platforms (AWS, GCP, or Azure), including usage of GPU instances and model hosting services. About ChemAnalyst : ChemAnalyst is a digital platform, which keeps a real-time eye on the chemicals and petrochemicals market fluctuations, thus, enabling its customers to make wise business decisions. With over 450 chemical products traded globally, we bring detailed market information and pricing data at your fingertips. Our real-time pricing and commentary updates enable users to stay acquainted with new commercial opportunities. Each day, we flash the major happenings around the globe in our news section. Our market analysis section takes it a step further, offering an in-depth evaluation of over 15 parameters including capacity, production, supply, demand gap, company share and among others. Our team of experts analyse the factors influencing the market and forecast the market data for up to the next 10 years. We are a trusted source of information for our international clients, ensuring user-friendly and customized deliveries on time. Website : https://www.chemanalyst.com/

House of Shipping is seeking a high-caliber Data Science Lead to join their team in Hyderabad. With a background of 15-18 years in data science, including at least 5 years in leadership roles, the ideal candidate will have a proven track record in building and scaling data science teams in logistics, e-commerce, or manufacturing. Strong expertise in statistical learning, ML architecture, productionizing models, and impact tracking is essential for this role. As the Data Science Lead, you will be responsible for leading enterprise-scale data science initiatives in supply chain optimization, forecasting, network analytics, and predictive maintenance. This position requires a blend of technical leadership and strategic alignment with various business units to deliver measurable business impact. Key responsibilities include defining and driving the data science roadmap across forecasting, route optimization, warehouse simulation, inventory management, and fraud detection. You will work closely with engineering teams to architect end-to-end pipelines, from data ingestion to API deployment. Proficiency in Python and MLOps tools like Scikit-Learn, XGBoost, PyTorch, MLflow, Vertex AI, or AWS SageMaker is crucial for success in this role. Collaboration with operations, product, and technology teams to prioritize AI use cases and define business metrics will be a key aspect of the job. Additionally, you will be responsible for managing experimentation frameworks, mentoring team members, ensuring model validation, and contributing to organizational data maturity. The ideal candidate will possess a Bachelor's, Master's, or Ph.D. degree in Computer Science, Mathematics, Statistics, or Operations Research. Certifications in Cloud ML stacks, MLOps, or Applied AI are preferred. To excel in this role, you should have a strategic vision in AI applications across the supply chain, strong team mentorship skills, expertise in statistical and ML frameworks, and experience in MLOps pipeline management. Excellent business alignment and executive communication skills are also essential for this position. If you are a data science leader looking to make a significant impact in the logistics industry, we encourage you to apply for this exciting opportunity with House of Shipping.,

About Info Edge InfoEdge’s mission is to create world-class platforms that transform lives by continuously innovating. Our products and services are built keeping our customers in mind. We always delight our customers by delivering superior value through enhanced offerings on the internet and other platforms. Through our continuous investment across various businesses, especially in cutting-edge technology, machine learning and artificial intelligence (AI), we have built a robust system that constantly increases our predictive powers on customer behavior, and optimizes and improves our systems. Our various teams tirelessly work together to solve problems, innovate, and create something to empower our customers. At Info Edge, people are our core competitive advantage and we will continue doing all that is needed to attract and retain the best available talent. About BU: Corporate Function – Data Science Designation: AI Scientist Desired Experience: 0-3 Year Required Educational Qualification : PhD/ M.Tech / B.Tech with relevant experience from Tier 1 Campus As AI Scientist you will: Develop algorithms and build systems to extract seemingly unseen trends and information from user content such as resumes, job description and profile information available through various sources and in different modalities such as numeric, structure and unstructured texts and images. Identify potential new business problems that can be solved through machine learning. Ideate, formulate, create metrics and execute on such problems and get buy in from business. Identify potential data-driven machine learning solutions to improve user experience through personalization and prediction of user preferences. Build intelligent systems to capture and model the vast amount of behavior data to enrich the content understanding with behavioral information. Identify the appropriate and cutting edge machine learning tools for various supervised and unsupervised tasks in the NLP, deep learning, semantic search, LTR space for building highly accurate and scalable recommendation systems and information retrieval solutions. Design solutions for scalable and real-time performance on a significantly large data set. Use big data technologies to optimally use infrastructure and improve performance. Participate in external forums /discussions, publish research papers, keep up-to-date on latest publications and build external/internal networks. Required Skills: Strong fundamental understanding and research experience in machine learning/Deep Learning/NLP/Information Retrieval/Artificial Intelligence areas. Strong applied knowledge of machine learning in solving real-world business problems with a significantly broad number of algorithms covering the landscape of classification, regression; discriminative, generative; supervised, unsupervised, semi-supervised; linear and non-linear dimensionality reduction, feature-extraction, feature selection, feature-learning. Industry experience in applying a variety of machine learning solutions to real-world large-scale data to build intelligent systems. An excellent problem solving skills with a research oriented approach. Ability to capture, manage, create pipelines and process Big Data Desired Skills: Ability to understand Business challenges and define solutions aligned to the needs. Why Join us: This is a unique opportunity to work on innovative and disruptive technologies that are shaping the future of the industry. We are looking for candidates who are willing to work passionately in a fast- paced environment and are ready to enhance their skills by learning something new. Being a part of the InfoEdge team, you will be engaged in innovations, product development, integration with mobile and social media, technology, research and development, quality assurance, sales and marketing. To learn more about Info Edge visit http://www.infoedge.in/