648 Xgboost Jobs - Page 13

About Us We are a fast-growing company dedicated to providing innovative solutions for telecom providers. Our skilled engineering team delivers impactful products that empower businesses to thrive in a competitive industry. To support our growth, we are seeking a dedicated and proactive AI Engineer to ensure the smooth operation, reliability, and performance of our production systems. Job Summary: We are seeking an experienced AI Engineer to design, develop, and optimize AI-driven solutions for networking and telecom environments. This role focuses on multi-stage data processing, AI model development, and real-time AI deployment to enhance automation, network intelligence, and decision-making. Key Responsibilities: AI System Design & Development Architect and implement AI-driven data processing and decision models for telecom applications. Develop probabilistic modeling, rule-based AI, and adaptive learning for network intelligence. Optimize AI models for scoring, anomaly detection, and predictive maintenance. Data Engineering & Processing Build and maintain high-performance data pipelines for network data ingestion, transformation, and storage. Work with telecom datasets (network logs, CDRs, telemetry) to enable AI-driven insights. Ensure data consistency, governance, and real-time processing efficiency. Model Training & Deployment Train and fine-tune machine learning models for network monitoring and fault prediction. Deploy AI models using open-source MLOps frameworks (Docker, Kubernetes, CI/CD). Implement real-time inference and automated remediation solutions. Performance Optimization & AI Governance Optimize AI solutions for scalability, accuracy, and high availability in telecom networks. Establish monitoring, compliance, and governance frameworks for AI deployment. Continuously improve models using adaptive learning and feedback loops. Requirements: 5+ years of experience in AI/ML development and deployment. Strong expertise in open-source AI frameworks (TensorFlow, PyTorch, Scikit-learn). Experience in data engineering, model training, and real-time inference. Hands-on experience with containerized AI deployment (Docker, Kubernetes). Networking & Telecom knowledge is a plus, with experience in ISP or Telco environments being an advantage. Proficiency in Python, SQL and cloud-based AI solutions. Familiarity with OSS/BSS, network monitoring tools, and telecom architectures is a plus. Core Skill Sets: AI/ML Frameworks: XGBoost (Apache 2.0) Programming Languages: Python Data Storage & Processing: Apache Kafka, Apache Spark Infrastructure & Orchestration: Apache Airflow Integration Points: Apache NiFi Model Versioning & Tracking: MLflow Deployment Tools: KServe, ONNX Runtime, BentoML How to Apply If you are a passionate AI Engineer with a knack for simplifying complex technical concepts, wed love to hear from you! Please send your resume , portfolio , and a cover letter detailing why you are a great fit for this role to tr1india-hr@tieroneoss.com Perks and Benefits Designation: AI Engineer Location: Chennai Job Type: Full-Time Application Deadline : N/A Apply here: tr1india-hr@tieroneoss.com

Data Scientist Full-time Company Description About Sopra Steria Sopra Steria, a major Tech player in Europe with 50,000 employees in nearly 30 countries, is recognised for its consulting, digital services and solutions. It helps its clients drive their digital transformation and obtain tangible and sustainable benefits. The Group provides end-to-end solutions to make large companies and organisations more competitive by combining in-depth knowledge of a wide range of business sectors and innovative technologies with a collaborative approach. Sopra Steria places people at the heart of everything it does and is committed to putting digital to work for its clients in order to build a positive future for all. In 2024, the Group generated revenues of €5.8 billion. The world is how we shape it. Job Description Data Scientist : Robust knowledge of machine learning model development , including strong familiarity with classical ML techniques, both supervised and unsupervised approaches. Proficiency in Python , with a solid understanding of key data science packages such as scikit-learn, pandas, NumPy, xgboost, LightGBM, and nltk. Strong knowledge of SQL , ideally with experience in Snowflake’s SQL flavour. Familiarity with agile methodologies . Knowledge of version control and git-based workflows . Experience with Spark , particularly PySpark. Familiarity with cloud-based environments , with a focus on AWS, especially SageMaker. Total Experience Expected: 08-10 years Qualifications Professional Degree with Data Science experience Additional Information At our organization, we are committed to fighting against all forms of discrimination. We foster a work environment that is inclusive and respectful of all differences. All of our positions are open to people with disabilities.

Position: Sr. and Mid. Python Developer – AI/ML Experience : 5+ years in Python, 3+ years in AI/ML Location: Sector V ,Salt lake , Kolkata Joining Timeline: Immediate to 30 Days Key Responsibilities: Design and deploy machine learning models using Python Develop AI-powered features and APIs with frameworks like FastAPI/Flask Conduct EDA, feature engineering, and model optimization Handle data pipelines, model deployment, and monitoring Collaborate with product and engineering teams to deliver scalable solutions Core Skillset: Python (Expert) : OOP, APIs, async programming AI/ML : Scikit-learn, XGBoost, NLP, Computer Vision Deep Learning : PyTorch, TensorFlow, Keras Data Engineering : Pandas, SQL/NoSQL, ETL pipelines DevOps/MLOps : Docker, Kubernetes, MLFlow, CI/CD Bonus : Hands-on with Zapier , Make.com , or other automation platforms Interested Candidate can apply at hr18@webskitters.com / 7908290216 (Only WhatsApp)

Senior Data and Applied Scientist - Advertising Join Pattern's innovative Data Science team as a Senior Data and Applied Scientist, where you'll leverage your expertise to optimize advertising spend on ecommerce platforms. Pattern is a leading ecommerce company that helps brands grow their business on platforms like Amazon. What Youll Do : Design, build, and maintain machine learning and statistical models to optimize advertising campaigns, enhancing search visibility and conversion rates on ecommerce platforms. Continuously improve the quality of our machine learning models, focusing on key metrics like search ranking, keyword bidding, CTR, and conversion rate estimation. Conduct research to integrate new data sources, innovate in feature engineering, fine-tune algorithms, and enhance data pipelines for robust model performance. Analyze large datasets to extract actionable insights that guide advertising decisions. Collaborate closely with teams across different regions (US and India) to ensure seamless collaboration and knowledge sharing. Dedicate 20% of your time to MLOps for efficient, reliable model deployment and operations. What Were Looking For: Bachelor’s or Master’s in Data Science, Computer Science, Statistics, or a related field. 3-6 years of industry experience in building and deploying machine learning solutions. Strong data manipulation and programming skills in Python and SQL, with hands-on experience using libraries such as Pandas, Numpy, Scikit-Learn, and XGBoost. Strong problem-solving skills and the ability to analyze complex data. In-depth expertise in a range of machine learning and statistical techniques, such as linear and tree-based models, along with an understanding of model evaluation metrics. Experience with Git, AWS, Docker, and MLFlow is advantageous. Additional Pluses: Portfolio: An active Kaggle or GitHub profile showcasing relevant projects. Domain Knowledge: Familiarity with advertising and ecommerce concepts, which would help in tailoring models to business needs. Explore more about Pattern and our innovative approach to ecommerce here.

Job Title: Senior ML Engineer Minimum 4 to 8+ years of experience in ML development in Product Based Company Location: Bangalore (Onsite) Why should you choose us? Rakuten Symphony is a Rakuten Group company, that provides global B2B services for the mobile telco industry and enables next-generation, cloud-based, international mobile services. Building on the technology Rakuten used to launch Japan’s newest mobile network, we are taking our mobile offering global. To support our ambitions to provide an innovative cloud-native telco platform for our customers, Rakuten Symphony is looking to recruit and develop top talent from around the globe. We are looking for individuals to join our team across all functional areas of our business – from sales to engineering, support functions to product development. Let’s build the future of mobile telecommunications together! Required Skills and Expertise: Candidate Must have exp. Working in Product Based Company. Should be able to Build, train, and optimize deep learning models with TensorFlow, Keras, PyTorch, and Transformers. Should have exp. In Manipulate and analyse large-scale datasets using Python, Pandas, Numpy, Dask Apply advanced fine-tuning techniques (Full Fine-Tuning, PEFT) and strategies to large language and vision models. Implement and evaluate classical machine learning algorithms using scikit-learn, statsmodels, XGBoost etc. Develop and deploy scalable APIs for ML models using FastAPI. Should have exp. In performing data visualization and exploratory data analysis with Matplotlib, Seaborn, Plotly, and Bokeh. Collaborate with cross-functional teams to deliver end-to-end ML solutions. Deploy machine learning models for diverse business applications over the cloud native and on-premise Hands-on experience with Docker for containerization and Kubernetes for orchestration and scalable deployment of ML models. Familiarity with CI/CD pipelines and best practices for deploying and monitoring ML models in production. Stay current with the latest advancements in machine learning, deep learning, and AI. Our commitment to you: - Rakuten Group’s mission is to contribute to society by creating value through innovation and entrepreneurship. By providing high-quality services that help our users and partners grow, - We aim to advance and enrich society. - To fulfill our role as a Global Innovation Company, we are committed to maximizing both corporate and shareholder value. RAKUTEN SHUGI PRINCIPLES: Our worldwide practices describe specific behaviours that make Rakuten unique and united across the world. We expect Rakuten employees to model these 5 Shugi Principles of Success. Always improve, always advance . Only be satisfied with complete success - Kaizen. Be passionately professional . Take an uncompromising approach to your work and be determined to be the best. Hypothesize - Practice - Validate - Shikumika. Use the Rakuten Cycle to success in unknown territory. Maximize Customer Satisfaction . The greatest satisfaction for workers in a service industry is to see their customers smile. Speed!! Speed!! Speed!! Always be conscious of time. Take charge, set clear goals, and engage your team.

Key Responsibilities: 1. Machine Learning Development Design, build, and evaluate supervised and unsupervised ML models (e.g., regression, classification, clustering, recommendation systems). Perform feature engineering, model tuning, and validation using cross-validation and performance metrics. 2. Data Preparation & Analysis Clean, preprocess, and transform large datasets from various sources. Conduct exploratory data analysis (EDA) to uncover patterns and insights. 3. Model Deployment & Monitoring Deploy ML models into production using tools like Flask, FastAPI, or cloud-native services. Monitor model performance and retrain/update models as needed. 4. Collaboration & Communication Work closely with data engineers, product managers, and business stakeholders to understand requirements and deliver impactful solutions. Present findings and model outcomes in a clear, actionable manner. 5. Tools & Technologies Use Python and libraries such as scikit-learn, XGBoost, TensorFlow, or PyTorch. Leverage version control (Git), Jupyter notebooks, and ML lifecycle tools (MLflow, DVC). Preferred Qualifications: Bachelor’s or master’s degree in computer science, Data Science, Statistics, or a related field. 2–3 years of experience in building and deploying ML models. Strong programming skills in Python; familiarity with SQL. Solid understanding of ML concepts, model evaluation, and statistical techniques. Exposure to cloud platforms (AWS, GCP, or Azure) and MLOps practices is a plus. Excellent problem-solving and communication skills.

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. 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. Qualifications Bachelor’s or Master’s degree in Computer Science, Statistics, Applied Mathematics, Data Science, or a related quantitative field 6+ 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 Microsoft is an equal opportunity employer. Consistent with applicable law, 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.

Greetings From Straive!!! We have an immediate opportunity for Data Scientist!!! !! Immediate to 15 days joiners preferrable!! JD: Role & responsibilities Design, develop, and deploy machine learning models to detect and prevent fraudulent activities, such as Merchant Fraud, transactional fraud, account takeover, and identity theft Work with large datasets to identify patterns, trends, and anomalies that may indicate fraudulent activity Utilize data analytics tools and methodologies to conduct in-depth assessments and generate Fraud rules and reports on fraud trends (including first-party and third-party fraud). Collaborate with cross-functional teams, including risk management, operations, and compliance, to enhance fraud prevention measures. Monitor industry trends, regulatory changes, and best practices to continually enhance fraud prevention strategies. Preferred candidate profile Bachelor's degree in engineering, technology, computer science or related field. 3+ years of proven data analytics experience in fraud prevention, risk management, or a related field Familiarity with fraud detection software, risk assessment methodologies, and regulatory compliance. Strong experience in SQL or Python Excellent communication and presentation skills with the ability to convey complex information clearly and concisely. Detail-oriented with a proactive mindset toward problem-solving and risk mitigation. Ability to work collaboratively in a cross-functional team environment. Thanks & Regards Human Resources Straive

Job Description We are looking f or a Data Scienti st-II to join our Data Science & Analytics (DSA) Team. You will get to work with other data scientists, analysts, data engineers, PMs and business teams on some of the toughest and most interesting problems in our industry. Our work spans across areas of inventory forecasting, order predictions, marketing spend optimization, delivery time prediction, personalization, customer insighting, product recommendations, supply chain planning, capacity optimization, and more. The role will involve understanding business problems, designing relevant ML solutions, building & deploying new models, maintaining & enhancing existing models, and automating performance measurement of the same. We are looking for someone who is excited to work in a fast-growing industry, has a spirit of ownership & collaboration, and loves seeing the impact of what they have built at scale! What our team owns At Rebel, the Data Science & Analytics team builds and maintains all ML models, rule-based intelligence, automated reports and dashboards used by the organization. We are on a mission to drive business impact via ML and Data Science and grow adoption of these areas at Rebel. We also want to enable the organization to better understand and effectively use ML and DS. We interact with teams across every business area such as Supply, Operations, Demand Generation, D2C, Finance, Brands, Customer Delight, Central Planning and many more. We are never short of interesting challenges and we balance delivering continuous impact and great CX, while building strong foundations to drive sustainable ML returns overtime. Specific Qualifications Strong working knowledge of a variety of machine learning techniques (Regression, Classification,Clustering, Decision Tree, Probability Networks, Neural Networks, Bayesian models etc.) Proficient in Python, SQL, and machine learning libraries (e.g., TensorFlow, scikit-learn). Experience in working with varied data types (structured and unstructured) and databases Experience with Machine Learning and related technologies such as Python, Tensorflow, Amazon SageMaker Excellent problem-solving skills with a demonstrated ability to think analytically and strategically. Good-to-have Experience solving NLP-based problems or working with LLMs / prompt engineering Working with non-tech stakeholders and explaining ML performance in simple language A love of food (Yes, we have regular tasting sessions at office!)

Job Title: Advanced Machine Learning Tutor Location: Fully Remote Type: Part-Time (Weekend Only) Salary: ₹40,000 – ₹50,000 per month Role Overview We are seeking a skilled and passionate Advanced Machine Learning Tutor to teach learners who have already completed foundational ML topics. You will conduct remote weekend classes , mentor students through hands-on projects, and explain the real-world use of advanced algorithms and techniques. This role is perfect for ML professionals who love teaching, enjoy simplifying complex ideas, and want to make a real impact on career-oriented learners. Key Responsibilities Deliver live weekend sessions on advanced ML concepts, such as: Ensemble Methods (Bagging, Boosting, Stacking) Feature Engineering and Selection Techniques Model Evaluation & Validation (Cross-Validation, ROC-AUC, etc.) Unsupervised Learning (PCA, Clustering techniques like K-Means, DBSCAN) Time Series Forecasting (ARIMA, Prophet, LSTM basics) Hyperparameter Tuning (GridSearchCV, RandomizedSearch, Bayesian Optimization) Introduction to Deep Learning (optional, depending on scope) Guide students through project-based learning using real-world datasets. Support students with doubts, debugging, and tool usage (like scikit-learn, XGBoost, LightGBM). Collaborate on curriculum refinement and improve content delivery. Keep updated with current trends in ML and bring them into your teaching. Required Qualifications Strong experience in Machine Learning beyond basic models Proficient with Python, NumPy, pandas, scikit-learn, XGBoost, etc. Familiar with advanced concepts like model selection, bias-variance tradeoff, overfitting/underfitting solutions Ability to explain and mentor real-world ML projects Previous teaching, tutoring, or mentoring experience (preferred) Excellent communication and presentation skills Nice to Have Familiarity with MLOps basics and tools (like MLflow) Experience with real-time or production ML systems Exposure to research papers or Kaggle competitions Understanding of Time Series and basic DL models like LSTMs Prior educational or ed-tech experience Students Will Learn To: Build and fine-tune complex ML models Evaluate model performance using advanced techniques Work with imbalanced datasets and noise Engineer features for better accuracy Solve real-world problems (credit risk, fraud detection, forecasting, etc.)

Company Description About Sopra Steria Sopra Steria, a major Tech player in Europe with 50,000 employees in nearly 30 countries, is recognised for its consulting, digital services and solutions. It helps its clients drive their digital transformation and obtain tangible and sustainable benefits. The Group provides end-to-end solutions to make large companies and organisations more competitive by combining in-depth knowledge of a wide range of business sectors and innovative technologies with a collaborative approach. Sopra Steria places people at the heart of everything it does and is committed to putting digital to work for its clients in order to build a positive future for all. In 2024, the Group generated revenues of €5.8 billion. The world is how we shape it. Job Description Data Scientist : Robust knowledge of machine learning model development , including strong familiarity with classical ML techniques, both supervised and unsupervised approaches. Proficiency in Python , with a solid understanding of key data science packages such as scikit-learn, pandas, NumPy, xgboost, LightGBM, and nltk. Strong knowledge of SQL , ideally with experience in Snowflake’s SQL flavour. Familiarity with agile methodologies . Knowledge of version control and git-based workflows . Experience with Spark , particularly PySpark. Familiarity with cloud-based environments , with a focus on AWS, especially SageMaker. Total Experience Expected: 08-10 years Qualifications Professional Degree with Data Science experience Additional Information At our organization, we are committed to fighting against all forms of discrimination. We foster a work environment that is inclusive and respectful of all differences. All of our positions are open to people with disabilities.

AI/ML Engineer/Manager: Location – Pune Experience: 6+ 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.

Department: Data Science / AI Job Type: Full-time Job Summary: We are looking for a skilled and results-driven Machine Learning Engineer to join our team. The ideal candidate will be responsible for designing, building, and deploying scalable machine learning models and pipelines that solve real-world problems and drive business value. Key Responsibilities: · Design and implement machine learning models for classification, regression, recommendation, NLP, or computer vision tasks. · Build and deploy ML pipelines using tools like TensorFlow, PyTorch, Scikit-learn, or MLflow. · Collaborate with data scientists, data engineers, and product teams to integrate models into production systems. · Analyze large, complex datasets to derive actionable insights and drive model development. · Conduct experiments, tune hyperparameters, and evaluate model performance using industry-standard metrics. · Ensure robustness, fairness, and scalability of machine learning systems. · Monitor and maintain deployed models, including retraining and updating as needed. Required Skills & Qualifications: · Bachelor's or Master’s degree in Computer Science, Artificial Intelligence, Data Science, or related field. · 3+ years of experience in machine learning, data science, or applied AI roles. · Proficiency in Python and ML libraries (Scikit-learn, TensorFlow, PyTorch, XGBoost, etc.). · Experience with data manipulation tools (Pandas, NumPy) and SQL. · Hands-on experience in deploying ML models into production (using REST APIs, Docker, Kubernetes, etc.). · Solid understanding of ML algorithms, model evaluation, and overfitting/underfitting concepts. · Familiarity with cloud platforms (AWS, GCP, Azure) is a plus. Preferred Qualifications: · Experience with NLP (e.g., BERT, GPT), computer vision (e.g., CNNs, OpenCV), or time-series forecasting. · Exposure to MLOps tools and practices (e.g., MLflow, DVC, Kubeflow). · Understanding of data engineering practices and pipeline automation.

Your Role and Responsibilities • 3+ years of experience in a Data Science, machine learning or a related field. • Strong hands-on experience in Machine Learning and Statistics focusing on structured and unstructured data problems. • Practical experience in several of the following areas: time series forecasting, clustering and classification techniques, regression, boosting algorithms, optimization techniques, NLP, recommendation systems, ElasticNet Excellent programming skills preferably in Python/Py spark and SQL • Understanding of developing, implementing, deploying machine learning models on the cloud platforms(Azure, AWS, GCP) by using AWS/Azure Machine Learning, Data bricks, or other relevant cloud services • Integrate machine learning models into existing systems and applications, ensuring seamless functionality and data flow • Understanding of developing and maintaining MLOps pipelines for automated model training, testing, deployment, and monitoring • Understanding of monitoring and analysing model performance, providing reports and insights to stakeholders as needed • Familiarity with data processing and storage tools, such as SQL, Hadoop, or Spark Advanced engineering abilities to deliver flexible and scalable end-to-end machine learning solutions. • Exposure to data visualization software and packages (Power BI, Tableau, matplotlib, d3) Understands challenges in business area, applicability of relevant data science disciplines, and system interactions. • Excellent written and verbal communication skills, confidence in presenting ideas and findings to stakeholders, and ability to do so at the right level of detail. Required Technical and Professional Expertise • Engineering Graduate from a reputed institute and/or Masters in Statistics, MBA • 3+ years of Data science experience • Strong expertise and deep understanding of machine learning. • Strong understanding of SQL & Python. Knowledge of Power BI or Tableau is a plus • Exposure to Industry specific (CPG, Manufacturing) use cases is required • Strong client-facing skills • Must be organized and detail oriented. • Excellent communication and interpersonal skills Preferred Technical and Professional Experience • Strong foundation in Supervised and Unsupervised Learning (Regression, Classification, Clustering, etc.). • Proficiency in Ensemble Learning (Random Forest, Gradient Boosting, XGBoost, LightGBM, etc.). • Experience in fine-tuning Large Language Models (LLMs) and working with open-source models (Llama, GPT, BERT, etc.). • Familiarity with Prompt Engineering, RAG (Retrieval-Augmented Generation), and Fine-tuning techniques. • Hands-on experience with Cloud Platforms (AWS, GCP, Azure) for ML model deployment. Familiarity with MLOps and Model Deployment using Kubernetes, Docker, and MLflow. About Polestar: As a data analytics and enterprise planning powerhouse, Polestar Solutions helps its customers bring out the most sophisticated insights from their data in a value-oriented manner. From analytics foundation to analytics innovation initiatives, we offer a comprehensive range of services that help businesses succeed with data. We have a geographic presence in the United States (Dallas, Manhattan, New York, Delaware), UK(London) & India (Delhi-NCR, Mumbai, Bangalore & Kolkata) and have 600+ people strong world-class team. We are growing at a rapid pace and plan to double our growth each year. This provides immense growth and learning opportunities to those who are choosing to work with Polestar. We hire from most of the Premier Undergrad and MBA institutes. We are serving customers across 20+ countries. Our expertise and deep passion for what we do has brought us many accolades. The list includes: - • Recognized as the Top 50 Companies for Data Scientists in 2023 by AIM. • Financial Times awarded Polestar as High-Growth Companies across Asia-Pacific for a 5th time in a row in 2023. • Featured on the Economic Times India's Growth Champions in FY2023. • Polestar Solutions Selected as a 2022 Red Herring Global Companies. • Top Data Science Providers in India 2023: Penetration and Maturity (PeMa) Quadrant. • India’s most promising data science companies in 2022 by Analytics Insight. • Featured on Forrester's Now Tech: Customer Analytics Service Providers Report Q2, 2021. • Recognized as Anaplan's India RSI Partner of the Year FY21. • Elite Qlik Partner and a member of the ‘Qlik Partner Advisory Council’ & Microsoft Gold Partners for Data & Cloud Platforms Culture at Polestar. We have one of the most progressive people’s practices which are all aimed at enabling fast paced growth for those who deserve it.

Job Information Date Opened 07/02/2025 Industry Technology Job Type Full time State/Province Karnataka Zip/Postal Code 560048 City Bangalore Country India About Us At Innover, we endeavor to see our clients become connected, insight-driven businesses. Our integrated Digital Experiences, Data & Insights and Digital Operations studios help clients embrace digital transformation and drive unique outstanding experiences that apply to the entire customer lifecycle. Our connected studios work in tandem to reimagine the convergence of innovation, technology, people, and business agility to deliver impressive returns on investments. We help organizations capitalize on current trends and game-changing technologies molding them into future-ready enterprises. Take a look at how each of our studios represents deep pockets of expertise and delivers on the promise of data-driven, connected enterprises. Job Description About the Role: Seeking a Senior Data Scientist who is equally comfortable building predictive models and architecting intelligent systems with Generative AI. This role is ideal for someone who thrives on solving complex business problems with the power of data, machine learning, and cutting-edge AI techniques — including large language models (LLMs), RAG pipelines, and prompt engineering. You’ll be at the forefront of innovation, driving the design and deployment of scalable AI solutions that power intelligent products, enhance automation, and enable smarter decision-making across the organization. Key Responsibilities: Generative AI & LLMs - Fine-tune and apply large language models (LLMs) for summarization, classification, generation, and dialogue use cases. Design and implement retrieval-augmented generation (RAG) pipelines using vector databases. Develop intelligent agents, agentic workflows and chat-based interfaces that translate natural language into actions or insights. Build multi-agent orchestration frameworks using tools such as LangGraph, AutoGen, or similar for enterprise-grade use cases. Create reusable prompt templates and evaluation strategies to ensure output quality and relevance. Machine Learning & Predictive Analytics - Develop robust ML models for classification, regression, clustering, and time-series forecasting. Apply advanced feature engineering, model evaluation, and explainability techniques. Collaborate with stakeholders to define data-driven solutions aligned with business KPIs. Deployment & MLOps - Lead the full model lifecycle from experimentation to deployment preferably using Azure, Databricks, or equivalent platforms. Monitor model performance, automate retraining, and ensure reliability through MLOps best practices. Data Strategy & Collaboration - Work with data engineers to transform raw data into ML-ready datasets. Collaborate cross-functionally with product managers, developers, and business teams to turn use cases into scalable AI solutions. Mentor junior team members and contribute to AI/ML best practices across the org. Required Skills & Qualifications: 4+ years of experience in data science or machine learning roles. Bachelor's, Master's degree, or Ph.D. in Computer Science, Data Science, Statistics, or a related field. Strong machine learning skills and 3+ years of experience productionizing machine learning models (Sklearn, XGBoost, or Deep Learning) Hands-on experience with Gen AI-related tech stack, including Azure cognitive search, Langchain, HuggingFace, vector DBs and agent frameworks like Autogen. Experience in fine-tuning open-source models like Llama etc. is a bonus. Strong programming skills in advanced python, with experience in SQL and cloud-based data platforms (Azure preferred). Understanding of model governance, versioning, monitoring, and evaluation. Ability to translate business problems into analytical frameworks and actionable models. Strong problem-solving mindset and ability to work in ambiguous, fast-paced environments. Strong storytelling and stakeholder communication skills.

What We Are Looking For Data Scientist preferably from financial services, large banks/MNCs. Strong background in business analysis (consumer/business strategy, financial products, pricing, etc.) with very strong data analysis (Sql, excel, etc,) experience Strong understanding of how to structure analysis and to solve real world business problems. Ability to identify key drivers of business and create KPIs/modeling solutions for the same, Expertise in end-to-end model development and model lifecycle management (develop, deploy, monitor) is preferred Exposure/Experience in developing Machine Learning models using various algorithms (logistic/linear, Random Forest. Xgboost ,etc) Hands on experience in R or Python is must Exposure to unstructured data analytics and big data handling is a plus Good business understanding of fintech/personal lending space is preferred Responsibilities You will work closely with the Product and Risk Team to : Define, design and deliver solutions using data science/analytics in fast paced environment Evaluate and apply machine learning algorithms to build variety of data science models particularly in credit risk/unsecured lending domain but not limited to Complete ownership including but not limited to identifying model development approaches, building ML models, evaluation, cost benefit analysis, exploration of new data sources, implementation and monitoring of developed models. Working closely with the engineering team for deployment of models and infrastructure development. (ref:hirist.tech)

Data Scientist We are seeking a Data Scientist with strong expertise in classical machine learning and experience working with automotive datasets. The role focuses on building predictive models, marketing mix analysis, and end-to-end data pipeline development. Experience in marketing analytics is essential. Exposure to Generative AI is a plus, not a Responsibilities : Develop and deploy ML models (classification, regression, forecasting) for business use cases in the automotive domain. Analyze customer and vehicle data to derive insights for campaigns, retention, and personalization. Implement NLP techniques and marketing mix models for campaign optimization. Build data pipelines to ensure clean and real-time data processing. Collaborate with cross-functional teams to translate insights into : Bachelors/Masters in Computer Science, Data Science, or related field. 3-5 years of experience in ML and marketing analytics. Strong in Python, R, SQL, Azure; experience with scikit-learn, XGBoost, TensorFlow, or PyTorch. Automotive domain experience is mandatory. Familiarity with GenAI tools (OpenAI, LangChain, etc.) is a bonus. (ref:hirist.tech)

TransUnion's Job Applicant Privacy Notice What We'll Bring Experienced data scientist with extensive mathematical programming and theoretical foundation and advanced software development skills to support development of state-of-the-art homegrown analytic platforms. Requirements What You'll Bring: Master’s or PhD degree in statistics, applied mathematics, financial mathematics, computer science, engineering, operations research, or other highly quantitative field; or a Bachelor’s degree in a quantitative field with at least seven (7) years of relevant professional experience. In either case, the candidate will demonstrate a consistent track record of academic excellence. Advanced C++ programming skills, preferably in scientific computing applications. Experience designing and implementing advanced numerical algorithms. Experience with integrating popular machine learning frameworks (XGBoost, LightGBM, H2O). Proficiency with statistical languages such as R or machine learning packages for Python; experience with other programming languages (Scala, Java) and HPC environments (Slurm, Univa, SGE, Torque). Advanced SQL programming skills and experience with big data platforms (Hadoop, Spark, Hive); knowledge of Apache Arrow is a plus. Experience engineering connections between big data frameworks and front end applications (Shiny, Streamlit, Dash, Tableau). Demonstrate interest in industries served by TransUnion, such as financial services, insurance, fraud, and digital marketing. Ability to apply strong project and time management skills to lead multiple projects simultaneously with limited supervision in a collaborative and fast-paced environment. Evidence of strong analytical, critical, and creative thinking and willingness to take initiative in problem-solving. Versatile interpersonal skills with the ability to effectively communicate at multiple levels within and outside the organization Proven ability to operate effectively in a complex and dynamic, matrixed environment. Good verbal and written communication skills. Proven ability to translate technical concepts into actionable recommendations in a manner that is suitable to influence business partners and decision-makers inside and outside the organization towards desired outcomes. Ability to travel 10-20% of the time. Impact You'll Make You will partner with internal and external cross-functional teams to drive the setup and ongoing success of new data science environments in multiple markets. Tasks will include – among others – the development of effective data science workflows, the localization of global tools, and liaising with global SMEs in data science and technology. Lead the development of analytic solutions using languages such as C++, R, Python, SQL, Hive and Spark, formalizing some of these efforts into repeatable process improvements. Assist Global Technology with maintenance of the tools and frameworks used by analysts on the high-performance computing (HPC) cluster and be a lead representative of the Data Science Development team in projects led by Global Technology as a subject matter expert on machine learning and scientific computing. Own data science consulting responsibilities for a variety of regions, working to identify strategies and opportunities to test and adopt TransUnion’s analytic products and services. In this capacity, you will interact directly with TransUnion’s matrix partners and provide an analytic perspective and general support as needed. Contribute to research and innovation initiatives in collaboration with other DSA peers and may lead small analytic research teams or manage research interns on a project basis, as needed. Participate in interviewing and evaluation of new talent, mentoring and training of junior colleagues, fostering a high-performance culture, and cultivating an environment that promotes excellence and reflects the TransUnion brand. has context menu This is a hybrid position and involves regular performance of job responsibilities virtually as well as in-person at an assigned TU office location for a minimum of two days a week. TransUnion Job Title Sr Consultant, Data Science and Analytics

Your Role 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 Productionlization Your Profile 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. What you will love about working here We recognise the significance of flexible work arrangements to provide support in hybrid mode, you will get an environment to maintain 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 The role is applicable for women candidates only. D&I Disclaimer: We are committed to fostering a diverse and inclusive workplace that values and celebrates differences. We believe that diversity in all its forms enriches our organization, promotes innovation, and drives success. We are dedicated to providing equal opportunities for all individuals, regardless of discrimination of any kind, including but not limited to race, color, religion, gender, gender identity or expression, sexual orientation, national origin, genetics, disability, age, neurodiversity, or veteran status. Our commitment extends to embracing all forms of diversity. We actively encourage candidates from diverse backgrounds to apply and join us in shaping a more inclusive future together

Company Description It all started in sunny San Diego, California in 2004 when a visionary engineer, Fred Luddy, saw the potential to transform how we work. Fast forward to today — ServiceNow stands as a global market leader, bringing innovative AI-enhanced technology to over 8,100 customers, including 85% of the Fortune 500®. Our intelligent cloud-based platform seamlessly connects people, systems, and processes to empower organizations to find smarter, faster, and better ways to work. But this is just the beginning of our journey. Join us as we pursue our purpose to make the world work better for everyone. Job Description The Connected Customer Experience (CCX) team creates consumer-grade digital experiences and products that help our customers and partners be successful and realize the value of their ServiceNow investment. Leveraging the latest technologies, and built on ServiceNow’s intelligent platform, we deliver a seamless, personalized experience at every step of our customers’ journey. The products we build power digital business for ServiceNow and can even become commercially available. As a Staff AI/ML Software Engineer within CCX you will build data pipeline, ML Models, secure code that's scalable and reusable. Grow our business by bringing internal products to the world and find new ways to personalize with AI/ML and simplify how employees and customers work. Implement software that empowers internal customers to extend what it can do to meet their specific needs, as our own "customer zero." What you get to do in this role: Design and build scalable search ranking, indexing and personalization systems. Develop real-time and batch ML models using embeddings, collaborative filtering, and deep learning. Integrate user behavior signals, session data, and content metadata to optimize relevance. Experience working with LLM technologies, including developing generative and embedding techniques, modern model architectures, retrieval-augmented generation (RAG), fine tuning / pre-training LLM (including parameter efficient fine-tuning), Deep reinforcement learning and evaluation benchmarks Collaborate cross-functionally with product, data, and infra teams to deploy experiments and measure impact. Optimize retrieval, filtering, and ranking algorithms in production search pipelines. Real-time Personalization using query Embeddings for Search Ranking Monitor model performance and continuously iterate using A/B testing and offline evaluation metrics Experience in MLOps and model governance Strong analytical and quantitative problem-solving ability Deep expertise in distributed computing strategies in Azure, AWS or GCP Cluster, enhancing the parallel processing capabilities Qualifications To be successful in this role you have: Experience in leveraging or critically thinking about how to integrate AI into work processes, decision-making, or problem-solving. This may include using AI-powered tools, automating workflows, analyzing AI-driven insights, or exploring AI's potential impact on the function or industry. 8+ years of full software development life cycle, including coding standards, code reviews, source control management, build processes, testing, and operations experience 3+ years experience building ML-powered search or recommendation systems. Strong programming skills in Python, Java, SpringBoot or Scala. Experience with ML frameworks like TensorFlow, PyTorch, XGBoost, TensorFlow or LightGBM. Knowledge of embedding models, user/item vectorization, or session-based personalization. Experience with large-scale distributed systems (e.g., Spark, Kafka, Kubernetes). Hands-on experience with real-time ML systems. Background in NLP, graph neural networks, or sequence modeling. Experience with A/B testing frameworks and metrics like NDCG, MAP, or CTR. Hands-on experience working on AI search (text, vector and hybrid search) FD21 Additional Information Work Personas We approach our distributed world of work with flexibility and trust. Work personas (flexible, remote, or required in office) are categories that are assigned to ServiceNow employees depending on the nature of their work and their assigned work location. Learn more here. To determine eligibility for a work persona, ServiceNow may confirm the distance between your primary residence and the closest ServiceNow office using a third-party service. Equal Opportunity Employer ServiceNow is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, creed, religion, sex, sexual orientation, national origin or nationality, ancestry, age, disability, gender identity or expression, marital status, veteran status, or any other category protected by law. In addition, all qualified applicants with arrest or conviction records will be considered for employment in accordance with legal requirements. Accommodations We strive to create an accessible and inclusive experience for all candidates. If you require a reasonable accommodation to complete any part of the application process, or are unable to use this online application and need an alternative method to apply, please contact globaltalentss@servicenow.com for assistance. Export Control Regulations For positions requiring access to controlled technology subject to export control regulations, including the U.S. Export Administration Regulations (EAR), ServiceNow may be required to obtain export control approval from government authorities for certain individuals. All employment is contingent upon ServiceNow obtaining any export license or other approval that may be required by relevant export control authorities. From Fortune. ©2025 Fortune Media IP Limited. All rights reserved. Used under license.

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. Your Role 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 Productionlization Your Profile 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. What You Will Love About Working Here We recognise the significance of flexible work arrangements to provide support in hybrid mode, you will get an environment to maintain 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 highly motivated and experienced ML Engineer/Data Scientist to join our growing ML/GenAI team. You will play a key role in designing, developing and productionalizing 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 3 years of experience in designing & building AI applications for customer and deploying them into production At least 5 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.

Master's degree in Computer Science, Statistics, Mathematics, or a related field. 7+ years of experience in data science and machine learning with a strong focus on model development and deployment. Expert-level knowledge of statistics, including probability theory, hypothesis testing, and statistical inference. In-depth knowledge of machine learning algorithms, including linear regression, logistic regression, decision trees, random forests, xgboost, and ensemble learning. Evaluate the performance of machine learning models and refine them to improve accuracy andgeneralizability. Communicate data insights to stakeholders in a clear and concise manner, using data visualization techniques and storytelling. collaborate with data engineers, software developers, and business stakeholders to integrate data science solutions into products and services. Stay up-to-date with the latest trends and developments in data science, machine learning, and artificial intelligence. Experience with Natural Language Processing (NLP) and Computer Vision (CV) techniques. Knowledge of DevOps methodologies and practices for continuous integration/continuous delivery (CI/CD). Experience with data warehousing and data lakes solutions like BigQuery or Snowflake. Familiarity with real-time data processing and streaming analytics. Passion for learning and staying at the forefront of data science and machine learning advancements.

Core Technology: Machine Learning Level: 6+ Years Primary Skills: Google Vertex AI, Python Secondary Skills: ML Models, Gcp Open Positions: 2 Job Location: Hyderabad Work Mode: Remote Deployment Type: Full Time Job Description Primary Skills Required: Strong understanding of MLOps practices Hands-on experience in deploying and productionizing ML models Proficient in Python Experience with Google Vertex AI Solid knowledge of machine learning algorithms such as: XGBoost Classification models BigQuery ML (BQML) Key Responsibilities: Design, build, and maintain ML infrastructure on GCP using tools such as Vertex AI, GKE, Dataflow, BigQuery, and Cloud Functions. Develop and automate ML pipelines for model training, validation, deployment, and monitoring using tools like Kubeflow Pipelines, TFX, or Vertex AI Pipelines. Work with Data Scientists to productionize ML models and support experimentation workflows. Implement model monitoring and alerting for drift, performance degradation, and data quality issues. Manage and scale containerized ML workloads using Kubernetes (GKE) and Docker. Set up CI/CD workflows for ML using tools like Cloud Build, Bitbucket, Jenkins, or similar. Ensure proper security, versioning, and compliance across the ML lifecycle. Maintain documentation, artifacts, and reusable templates for reproducibility and auditability. Having GCP MLE Certification is Plus. Job Types: Full-time, Permanent, Fresher Schedule: Day shift Morning shift Application Question(s): Do you have the Hands-on experience in deploying and productionizing ML models? Are you proficient in python? Do you have experience with Google Vertex AI? Do you have Solid knowledge of machine learning algorithms such as: XGBoost Classification models BigQuery ML (BQML) ? Work Location: In person

Company Overview Docusign brings agreements to life. Over 1.5 million customers and more than a billion people in over 180 countries use Docusign solutions to accelerate the process of doing business and simplify people’s lives. With intelligent agreement management, Docusign unleashes business-critical data that is trapped inside of documents. Until now, these were disconnected from business systems of record, costing businesses time, money, and opportunity. Using Docusign’s Intelligent Agreement Management platform, companies can create, commit, and manage agreements with solutions created by the #1 company in e-signature and contract lifecycle management (CLM). What You'll Do You will play an important role in applying and implementing effective machine learning solutions, with a significant focus on Generative AI. You will work with product and engineering teams to contribute to data-driven product strategies, explore and implement GenAI applications, and deliver impactful insights. This positionis an individual contributor role reporting to the Senior Manager, Data Science. Responsibility Experiment with, apply, and implement DL/ML models, with a strong emphasis on Large Language Models (LLMs), Agentic Frameworks, and other Generative AI techniques to predict user behavior, enhance product features, and improve automation Utilize and adapt various GenAI techniques (e.g., prompt engineering, RAG, fine-tuning existing models) to derive actionable insights, generate content, or create novel user experiences Collaborate with product, engineering, and other teams (e.g., Sales, Marketing, Customer Success) to build Agentic system to run campaigns at-scale Conduct in-depth analysis of customer data, market trends, and user insights to inform the development and improvement of GenAI-powered solutions Partner with product teams to design, administer, and analyze the results of A/B and multivariate tests, particularly for GenAI-driven features Leverage data to develop actionable analytical insights & present findings, including the performance and potential of GenAI models, to stakeholders and team members Communicate models, frameworks (especially those related to GenAI), analysis, and insights effectively with stakeholders and business partners Stay updated on the latest advancements in Generative AI and propose their application to relevant business problems Complete assignments with a sense of urgency and purpose, identify and help resolve roadblocks, and collaborate with cross-functional team members on GenAI initiatives Job Designation Hybrid: Employee divides their time between in-office and remote work. Access to an office location is required. (Frequency: Minimum 2 days per week; may vary by team but will be weekly in-office expectation) Positions at Docusign are assigned a job designation of either In Office, Hybrid or Remote and are specific to the role/job. Preferred job designations are not guaranteed when changing positions within Docusign. Docusign reserves the right to change a position's job designation depending on business needs and as permitted by local law. What You Bring Basic Bachelor's or Master's degree in Computer Science, Physics, Mathematics, Statistics, or a related field 3+ years of hands-on experience in building data science applications and machine learning pipelines, with demonstrable experience in Generative AI projects Experience with Python for research and software development purposes, including common GenAI libraries and frameworks Experience with or exposure to prompt engineering, and utilizing pre-trained LLMs (e.g., via APIs or open-source models) Experience with large datasets, distributed computing, and cloud computing platforms (e.g., AWS, Azure, GCP) Proficiency with relational databases (e.g., SQL) Experience in training, evaluating, and deploying machine learning models in production environments, with an interest in MLOps for GenAI Proven track record in contributing to ML/GenAI projects from ideation through to deployment and iteration Experience using machine learning and deep learning algorithms like CatBoost, XGBoost, LGBM, Feed Forward Networks for classification, regression, and clustering problems, and an understanding of how these can complement GenAI solutions Experience as a Data Scientist, ideally in the SaaS domain with some focus on AI-driven product features Preferred PhD in Statistics, Computer Science, or Engineering with specialization in machine learning, AI, or Statistics, with research or projects in Generative AI 5+ years of prior industry experience, with at least 1-2 years focused on GenAI applications Previous experience applying data science and GenAI techniques to customer success, product development, or user experience optimization Hands-on experience with fine-tuning LLMs or working with RAG methodologies Experience with or knowledge of experimentation platforms (like DataRobot) and other AI related ones (like CrewAI) Experience with or knowledge of the software development lifecycle/agile methodology, particularly in AI product development Experience with or knowledge of Github, JIRA/Confluence Contributions to open-source GenAI projects or a portfolio of GenAI related work Programming Languages like Python, SQL; familiarity with R Strong knowledge of common machine learning, deep learning, and statistics frameworks and concepts, with a specific understanding of Large Language Models (LLMs), transformer architectures, and their applications Ability to break down complex technical concepts (including GenAI) into simple terms to present to diverse, technical, and non-technical audiences Life At Docusign Working here Docusign is committed to building trust and making the world more agreeable for our employees, customers and the communities in which we live and work. You can count on us to listen, be honest, and try our best to do what’s right, every day. At Docusign, everything is equal. We each have a responsibility to ensure every team member has an equal opportunity to succeed, to be heard, to exchange ideas openly, to build lasting relationships, and to do the work of their life. Best of all, you will be able to feel deep pride in the work you do, because your contribution helps us make the world better than we found it. And for that, you’ll be loved by us, our customers, and the world in which we live. Accommodation Docusign is committed to providing reasonable accommodations for qualified individuals with disabilities in our job application procedures. If you need such an accommodation, or a religious accommodation, during the application process, please contact us at accommodations@docusign.com. If you experience any issues, concerns, or technical difficulties during the application process please get in touch with our Talent organization at taops@docusign.com for assistance. Our global benefits Paid time off Take time to unwind with earned days off, plus paid company holidays based on your region. Paid parental leave Take up to six months off with your child after birth, adoption or foster care placement. Full health benefits Options for 100% employer-paid health plans from day one of employment. Retirement plans Select retirement and pension programs with potential for employer contributions. Learning & development Grow your career with coaching, online courses and education reimbursements. Compassionate care leave Paid time off following the loss of a loved one and other life-changing events.