1345 Data Scientist Jobs - Page 5

* Strong programming skills in Python, including knowledge of libraries like NumPy, Pandas, Matplotlib, and Seaborn. * Proficiency in AI/ML frameworks: scikit-learn, TensorFlow, Keras, or PyTorch. *LLM

And because our technology is purpose-built for restaurants, by restaurant people, restaurants can trust that well deliver on their needs for today while investing in experiences that will power their restaurant of the future, Breadyto make a change Toast is looking to expand the Data Science team to deliver new Data Science models to meet Toast Capital/Lending increased demands As a Principal Data Scientist, you will bring senior data science technical leadership with domain expertise in lending to the Capital Data Science team An ideal candidate has wealth of experience in banking lending technology or a leading fintech company with substantial depth of expertise and knowledge in lending underwriting, and risk management models, About this Roll*: Lead the development and implementation of advanced predictive models, to assess credit risk, optimize lending growth, and improve overall portfolio performance, Will actively engage in code reviews and comprehensive data quality assessments, ensuring that all development data pipelines and code meet the highest standards of reliability, accuracy, and readiness for seamless production deployment Collaborate closely with cross-functional teams, including Risk Management, Product, Engineering, and Business Strategy, to identify opportunities for leveraging data-driven insights to support growth and risk mitigation initiatives, Design, develop, and maintain innovative credit risk and lending growth strategies that align with the organization's objectives, while ensuring compliance with regulatory requirements and industry best practices, Monitor and analyze the performance of existing models and strategies, identifying areas for improvement and implementing data-driven refinements as needed, Present complex data-driven insights and recommendations to stakeholders in a clear, concise, and actionable manner, while fostering a data-driven culture within the organization, Mentor and guide junior data scientists, fostering a collaborative environment and promoting the growth and development of the data science team, Stay current with the latest trends and developments in data science, fintech, and credit risk management, continually exploring new methods and technologies to enhance the organization's capabilities, Do you have the right ingredients* Advanced degree in quantitative field such as Data Science, Statistics, Mathematics, Financial Engineering or related discipline 10+ years of experience in data science, with a focus on credit risk modeling in retail lending space (consumer or small business) and lending growth strategies, preferably within the fintech lending space, Proficiency in machine learning, AI, and statistical modeling techniques, with a strong track record of developing and deploying successful predictive models in a business setting, Familiarity with the US model risk management policies such as SR 11-7 that govern the lending models is strongly preferred, Strong proficiency in Python and SQL and experience with data science libraries and tools such as: Spark, Scala, scikit-learn, Tensorflow, PyTorch, XGBoost etc Familiarity with standard software engineering practices and tools including object-oriented programming, test-driven development, CI/CD, git, task orchestration (Airflow) and AWS tooling Strong understanding of credit risk management, lending practices, and regulatory requirements within the financial industry, Excellent communication and presentation skills, with the ability to articulate complex data-driven insights to both technical and non-technical stakeholders, Strong leadership skills, with experience mentoring and guiding junior data scientists Bonus ingredients*: Passion for research and curiosity that calls you to go beyond good enough to create something innovative and exciting Self starter who loves to dig into different kinds of data to solve business problems and can communicate their findings to cross-functional stakeholders Work Mode: This role follows a hybrid work model, requiring a minimum of 2 days per week in the office, Diversity, Equity, and Inclusion is Baked into our Recipe for Success At Toast, our employees are our secret ingredientwhen they thrive, we thrive The restaurant industry is one of the most diverse, and we embrace that diversity with authenticity, inclusivity, respect, and humility By embedding these principles into our culture and design, we create equitable opportunities for all and raise the bar in delivering exceptional experiences, We Thrive Together We embrace a hybrid work model that fosters in-person collaboration while valuing individual needs Our goal is to build a strong culture of connection as we work together to empower the restaurant community To learn more about how we work globally and regionally, check out: https://careers toasttab,/locations-toast, Apply today! Toast is committed to creating an accessible and inclusive hiring process As part of this commitment, we strive to provide reasonable accommodations for persons with disabilities to enable them to access the hiring process

We are seeking a Senior Data Scientist with strong engineering skills and hands-on experience in Python , FastAPI , and asynchronous programming , along with a deep understanding of LLM orchestration frameworks like LangChain and LangGraph . The ideal candidate should have proven experience designing and deploying agentic AI systems using frameworks such as A2A and CrewAI . This role combines data science expertise with backend development and generative AI innovations, driving impactful solutions across domains. Key Responsibilities: Design and deploy intelligent applications using LLMs with LangChain and LangGraph. Build and orchestrate agentic workflows using A2A, CrewAI, or similar frameworks. Develop robust, scalable APIs using FastAPI and async programming. Implement end-to-end pipelines that integrate AI agents with external APIs, databases, and tools. Conduct prompt engineering, memory management, retrieval augmentation, and tool integration. Evaluate and improve model performance through experimentation and fine-tuning. Collaborate with ML engineers, product managers, and backend developers to deliver AI-powered features. Stay abreast of the latest advancements in the LLM, agentic AI, and multi-agent system space. Required Skills & Experience: Strong Python programming expertise (6+ years). Experience building REST APIs with FastAPI and handling async/await operations. Deep understanding of LLM frameworks like LangChain , LangGraph , or custom agent frameworks. Experience with multi-agent orchestration frameworks like AutoGen , A2A , CrewAI , etc. Experience in prompt engineering , RAG (retrieval-augmented generation) , and vector DBs (e.g., FAISS, Pinecone). Good grasp of architectural patterns for scalable AI applications. Knowledge of common LLM APIs (e.g., OpenAI, Anthropic, Cohere).

The Lead data Scientist will be responsible for organizing and reporting data related to sales numbers, market research, logistics, linguistics, or other behaviors. They utilize technical expertise to ensure data reported is accurate and high-quality. Data will need to be analysed, designed, and presented in a way that assists individuals, business owners and customer stakeholders to make better decisions. Responsibilities: Cross-Functional Collaboration: Collaborate seamlessly with Engineering, Product, and Operations teams to conceptualise, design, and construct data reporting and analytical systems. Ideation and Analysis: Generate ideas for exploratory analysis, actively shaping the trajectory of future projects. Provide insightful recommendations for strategic actions based on data-driven insights. Rapid Prototyping and Product Discussions: Drive the rapid prototyping of solutions, actively participating in discussions related to product and feature development. Dashboard Creation and Reporting: Develop dashboards and comprehensive documentation to effectively communicate results. Regularly monitor key data metrics, facilitating informed decision-making. Integration with Production Systems: Collaborate closely with software engineers to deploy and integrate data models into production systems. Ensure scalability, reliability, and efficiency of integrated solutions. Business Metrics Identification: Identify and analyze key business metrics, offering strategic insights. Recommend product features based on the identified metrics to enhance overall product functionality. Understand and manage Data Infrastructure: Lead the design and development of scalable, robust, and efficient data architectures. Oversee the development and maintenance of ETL (Extract, Transform, Load) processes to move and transform data from various sources into data warehouses or other storage solutions. Ensure data quality and integrity throughout the data pipeline. Team Leadership: Lead a team of data engineers and data analysts, providing mentorship, guidance, and technical expertise. Coach and manage a team to deliver using Agile processes and ensure high RoI. Participating actively in recruitment and nurturing of engineers as awesome as you. Skills Exceptional quantitative and problem-solving skills - capable of tackling complex data-driven challenges and formulating effective solutions. Proven proficiency - In essential data science libraries, including Pandas, Numpy, SciPy, and Scikit-Learn, for data manipulation, analysis, and modeling. In-depth expertise in Python programming and SQL - Focus on data analysis, model building, and algorithmic implementation. Experience with distributed computing frameworks - Hadoop or Spark, for handling large-scale data processing and machine learning tasks. Data Architecture - Designing and implementing robust data architectures that support the organizations needs. This includes understanding different database systems, data lakes, and data warehouses.

Build and deploy machine learning models that deliver business impact Develop frameworks to monitor and ensure fairness in our AI systems Analyze large, complex datasets to uncover insights and power product decisions Collaborate with cross-functional teams to translate models into production Push the boundaries of applied ML and Responsible AI Experience with Python and ML libraries (eg, scikit-learn, PyTorch, TensorFlow) Experience our comprehensive benefits with family medical, vision and dental coverage, a competitive base salary, and eligibility for equity awards and discretionary bonuses or commissions

You will be contributing towards building Forecasting / Prediction / Root-cause algorithms/AgenticAI/Vision algorithms by closely collaborating across teams and provide solution to business challenges. In most cases the prioritization of business challenges is based on impact and hence your contributions can have direct impact to our businesses. What you'll do: 1. Play a key role to solve complex AI problems, pivotal to Walmart s business and drive actionable insights from terabytes of data 2. Leverage data science tools and techniques, keeping abreast with the latest in the community to solve problems for Walmart at Scale and take them to PROD using best industry standard practices. 3. Develop ideas leveraging GenAI, Agentic AI and take them to PROD 4. Take forward the solutions into Pipelines/APIs into PROD as needed by the business 5. Research, learn/disseminate & adapt new technologies to solve problems & improve upon existing solutions 6. Brainstorm, review and mentor junior associates in providing robust data science solutions What you'll bring: M.Tech with 5+ years of relevant experience in Machine learning / Artificial intelligence Problem solver at heart with experience in taking solutions to PROD Proficiency with Python/Java/PySpark/BiqQuery etc Proficiency with ML libraries sklearn/pytorch/tensorflow etc Good knowledge of commonly used design patterns in data science Cloud friendliness (GCP/Azure etc) to leverage distributed computing/scalability Good communication / influencing / mentoring skills with inclination to high ownership and commitment Minimum Qualifications... Minimum Qualifications:Option 1: Bachelors degree in Statistics, Economics, Analytics, Mathematics, Computer Science, Information Technology or related field and 4 years experience in an analytics related field. Option 2: Masters degree in Statistics, Economics, Analytics, Mathematics, Computer Science, Information Technology or related field and 2 years experience in an analytics related field. Option 3: 6 years experience in an analytics or related field. Preferred Qualifications... Masters degree in Computer Science, Computer Engineering, Computer Information Systems, Software Engineering, or related area and 2 years experience in software engineering or related area

You will be at the forefront of dunnhumby s research data science team where you will be translating a complex business problem into a data science problem and solving that with scalable and state-of-the art AI algorithms. Joining our research data science team, you will be helping identify new opportunities within the Data Science space for future dunnhumby solutions. Learn from experts and grow your career in our organisation What we expect from you Degree or equivalent in a statistical or mathematical subject. 5 to 7 Years of experience in Data Science Good understanding of statistics and mathematical methodologies used - especially forecasting, regression, linear models, time series, hypothesis tests and optimisation Ability to prototype solutions using Python and Spark to facilitate development and testing of algorithms on large data sets Good understanding of machine learning techniques, with applications to classification, prediction and clustering Ability to apply and extend experimental design methodology to conduct rigorous measurement of treatment effects Good working knowledge of databases, including SQL, relational and non-relational data models Experience of using following algorithm at scale: Ancova, linear models with regularization, clustering, random forests, xgboost Research the latest machine learning approaches Good grasp of Object-Oriented Programming Stakeholder Management Ability to quickly learn open-source statistics and machine learning packages - Pandas, SciPy, Scikit - learning, Tensor flow. Experience in developing solutions related to Market Mix Modelling, Causal AI and Generative AI

Job Description About Signify Through bold discovery and cutting-edge innovation, we lead an industry that is vital for the future of our planet: lighting Through our leadership in connected lighting and the Internet of Things, we're breaking new ground in data analytics, AI, and smart solutions for homes, offices, cities, and beyond, At Signify, you can shape tomorrow by building on our incredible 125+ year legacy while working toward even bolder sustainability goals Our culture of continuous learning, creativity, and commitment to diversity and inclusion empowers you to grow your skills and career, Join us, and together, well transform our industry, making a lasting difference for brighter lives and a better world You light the way, More About The Role Were looking for a Data Scientist to work on Deep learning, machine learning, data mining, and statistical modelingfor providing predictive and prescriptive enterprise analytics Successful candidates will be expected to guide a team of Data Scientists, investigate state of the art techniques in advanced machine learning and statistical modeling, and design, develop, and deploy state-of-art, scalable systems for innovative analytics applications across various functional areas (e-g Finance, Sales, Marketing, Supply Chain, etc ) Applicants will be expected to work with a diverse set of data sources, such as time series data, graph data, semi-structured and unstructured data, and build statistical / machine-learning / Deep Learning/Gen AI models in support of on-demand, real-time analytic services The applicant should also have strong skills in explaining the analytic models and outcomes to business stakeholders, Youll be part of the Signifys Enterprise Data & Analytics team, based in Bangalore, More About You Bachelor's or Master's degree in Computer Science, Statistics, Mathematics, or a related field 4+ years of hands-on experience in data science or a related field with demonstrated history of delivering analytics models and solutions Strong programming skills in Python, PySpark or other statistical programming languages Strong foundation in machine learning and deep learning algorithms and expertise in natural language processing (NLP) and computer vision techniques Experience with popular deep learning frameworks such as TensorFlow and PyTorch Research and explore the latest advancements in generative AI, including techniques like natural language processing (NLP), computer vision, and machine learning Develop and implement generative AI models and algorithms to address specific business challenges Train and fine-tune generative AI models using large datasets and industry-specific knowledge to improve accuracy and efficiency Knowledge of cloud platforms like AWS, GCP, or Azure Strong problem-solving skills, communication skills and the ability to think creatively and strategically with a focus on business outco Everything well do for you Opportunity to work on some of the highly complex and challenging business problems across a variety of functional and business domains, Competitive salary depending on experience, Extensive set of tools to drive your career, such as a personalized learning platform, training and coaching You can grow a lasting career here Well encourage you, support you, and challenge you Well help you learn and progress in a way thats right for you, with coaching and mentoring along the way Well listen to you too, because we see and value every one of our 30,000+ people, We believe that a diverse and inclusive workplace fosters creativity, innovation, and a full spectrum of bright ideas With a global workforce representing 99 nationalities, we are dedicated to creating an inclusive environment where every voice is heard and valued, helping us all achieve more together,

Curious about the role ? Generative AI & NLP Development : Design, develop, and deploy advanced applications and solutions using Generative AI models (e.g., GPT, LLaMA, Mistral) and NLP algorithms to solve business challenges and unlock new opportunities for our clients. Model Customization & Fine-Tuning: Apply state-of-the-art techniques like LoRA, PEFT, and fine-tuning of large language models to adapt solutions to specific use cases, ensuring high relevance and impact. Innovative Problem Solving : Leverage advanced AI methodologies to tackle real-world business problems, providing creative and scalable AI-powered solutions that drive measurable results. Data-Driven Insights: Conduct deep analysis of large datasets, uncovering insights and trends that guide decisionmaking, improve operational efficiencies, and fuel innovation. Cross-Functional Collaboration: Work closely with Consulting, Engineering, and other teams to integrate AI solutions into broader business strategies, ensuring the seamless deployment of AI-powered applications. Client Engagement: Collaborate with clients to understand their unique business needs, provide tailored AI solutions, and educate them on the potential of Generative AI to drive business transformation. What do we expect? Generative AI & NLP Expertise: Extensive experience in developing and deploying Generative AI applications and NLP frameworks, with hands-on knowledge of LLM fine-tuning, model customization, and AI-powered automation. Hands-On Data Science Experience: 6+ years of experience in data science, with a proven ability to build and operationalize machine learning and NLP models in real-world environments. AI Innovation: Deep knowledge of the latest developments in Generative AI and NLP, with a passion for experimenting with cutting-edge research and incorporating it into practical solutions. Problem-Solving Mindset: Strong analytical skills and a solution-oriented approach to applying data science techniques to complex business problems. Communication Skills: Exceptional ability to translate technical AI concepts into business insights and recommendations for non-technical stakeholders.

Are you passionate about solving complex logistics challenges? Our Analytics team is at the forefront of enhancing delivery experiences through data-driven solutions and innovative technology. As a Data Scientist, you will join a team dedicated to optimizing our delivery network, ensuring reliable and efficient service to our customers. We are seeking an enthusiastic, customer-centric professional with strong analytical capabilities to drive impactful projects, implement advanced solutions, and develop scalable processes. In this role, you will have immediate ownership of business-critical challenges and the opportunity to make strategic, data-driven decisions that shape the future of our delivery operations. Your work will directly influence customer experience and operational excellence. The ideal candidate will possess both research science capabilities and program management skills, thriving in an environment that requires independent decision-making and comfort with ambiguity. This role offers the opportunity to make a significant impact on our advanced logistics network while working with pioneering technology and data science applications. Basic qualifications 6+ years of building machine learning models for business application experience Knowledge of programming languages such as C/C++, Python, Java or Perl Experience programming in Java, C++, Python or related language Experience with neural deep learning methods and machine learning Preferred qualifications: PhD in engineering, technology, computer science, machine learning, robotics, operations research, statistics, mathematics or equivalent quantitative field 7+ years of extensive relevant research experience Deep expertise in Machine Learning Proficiency in programming Core competency in mathematics and statistics Track record of successful projects in algorithm design and product development Publications at peer-reviewed conferences or journals Prior experience with mentorship and/or management of scientists Strategic thinker with good execution skills Exhibits excellent business judgment Effective verbal and written communication skills Experience working with real-world data sets and building scalable models from big data Experience with modern modeling tools and frameworks such as R, scikit-learn, Spark MLLib, MxNet, Tensorflow Experience with large scale distributed systems 6+ years of building machine learning models for business application experience Knowledge of programming languages such as C/C++, Python, Java or Perl Experience programming in Java, C++, Python or related language Experience with neural deep learning methods and machine learning PhD in engineering, technology, computer science, machine learning, robotics, operations research, statistics, mathematics or equivalent quantitative field 15+ years of relevant, broad research experience Deep expertise in Machine Learning Proficiency in programming core competency in mathematics and statistics. Track record of successful projects in algorithm design and product development. Publications at top-tier peer-reviewed conferences or journals. prior experience with mentorship and/or management of scientists Thinks strategically, but stays on top of tactical execution. Exhibits excellent business judgment; balances business Effective verbal and written communication skills Experience working with real-world data sets and building scalable models from big data. Experience with modeling tools such as R, scikit-learn, Spark MLLib, MxNet, Tensorflow, Experience with large scale distributed systems

Essential Responsibilities: Architecture & Design Define and document the overall data platform architecture in GCP, including ingestion (Pub/Sub, Dataflow), storage (BigQuery, Cloud Storage), and orchestration (Composer, Workflows). Establish data modeling standards (star/snowflake schemas, partitioning, clustering) to optimize performance and cost. Platform Implementation Build scalable, automated ETL/ELT pipelines for IoT telemetry and events. Implement streaming analytics and CDC where required to support real-time dashboards and alerts. Data Products & Exchange Collaborate with data scientists and product managers to package curated datasets and ML feature tables as consumable data products. Architect and enforce a secure, governed data exchange layerleveraging BigQuery Authorized Views, Data Catalog, and IAMto monetize data externally. Cost Management & Optimization Design cost-control measures: table partitioning/clustering, query cost monitoring, budget alerts, and committed-use discounts. Continuously analyze query performance and storage utilization to drive down TCO. Governance & Security Define and enforce data governance policies (cataloging, lineage, access controls) using Cloud Data Catalog and Cloud IAM. Ensure compliance with privacy, security, and regulatory requirements for internal and external data sharing. Stakeholder Enablement Partner with business stakeholders to understand data needs and translate them into platform capabilities and SLAs. Provide documentation, training, and self-service tooling (Data Studio templates, APIs, notebooks) to democratize data access. Mentorship & Leadership Coach and mentor engineers on big data best practices, SQL optimization, and cloud-native architecture patterns. Lead architecture reviews, proof-of-concepts, and pilot projects to evaluate emerging technologies (e.g., BigQuery Omni, Vertex AI). What You'll Bring to Our Team Minimum Qualifications Bachelor’s degree in Computer Science, Engineering, or related field. 8+ years designing and operating large-scale data platforms, with at least 5 years hands-on experience in GCP (BigQuery, Dataflow, Pub/Sub). Deep expertise in BigQuery performance tuning, data partitioning/clustering, and cost-control techniques. Proven track record building streaming and batch pipelines (Apache Beam, Dataflow, Spark). Strong SQL skills and experience with data modeling for analytics. Familiarity with data governance tools: Data Catalog, IAM, VPC Service Controls. Experience with Python or Java for ETL/ELT development. Excellent communication skills, able to translate technical solutions for non-technical stakeholders.

Job Summary As a Data Scientist at Bluphlux, you will play a pivotal role in leveraging advanced data analytics and machine learning techniques to enhance our recruitment processes. You will work closely with our innovative team to develop and implement models that improve the accuracy and efficiency of candidate selection, ensuring that our clients receive the best possible matches for their job openings. Key Responsibilities Develop and implement machine learning models to improve recruitment processes. Analyze large datasets to extract meaningful insights and trends. Collaborate with cross-functional teams to integrate data-driven solutions into our recruitment platform. Continuously evaluate and refine algorithms to enhance performance and accuracy. Stay updated with the latest advancements in data science and machine learning to ensure our solutions remain cutting-edge. Required Qualifications Bachelors or Masters degree in Data Science, Computer Science, Statistics, or a related field. Proven experience as a Data Scientist or similar role. Strong proficiency in programming languages such as Python or R. Experience with machine learning frameworks and libraries. Excellent analytical and problem-solving skills. Preferred Skills Experience in the recruitment or HR tech industry. Familiarity with natural language processing (NLP) techniques. Knowledge of cloud platforms and big data technologies.

Job Title: Senior Data Scientist Location: Bangalore Experience: 8 - 12 Years Job Summary We are seeking a highly skilled and experienced Senior Data Scientist to join our team in Bangalore. The ideal candidate will have a deep understanding of Machine Learning (ML) and Artificial Intelligence (AI), with a strong focus on Azure Fabric within the banking and finance domain. In this role, you will develop and implement advanced data-driven solutions that enhance decision-making, optimise processes, and contribute to the success of our client s financial objectives. Mandatory Skills Proven experience in traditional Machine Learning (ML) and Artificial Intelligence (AI). Strong experience in Azure Fabric and its integration with various banking systems. Expertise in Data Science methodologies, predictive modelling, and statistical analysis. Solid understanding of the Finance domain with a focus on banking processes and challenges. Hands-on experience with big data technologies and cloud platforms (Azure, AWS). Proficiency in Python-related data science libraries (e.g., Pandas, NumPy, Scikit-learn). Experience in data processing, ETL pipelines, and data engineering. Familiarity with SQL and NoSQL databases. Key Responsibilities Design and implement Machine Learning (ML) and Artificial Intelligence (AI) models to solve complex business problems in the finance sector. Work closely with business stakeholders to understand requirements and translate them into data-driven solutions. Develop and deploy ML models on Azure Fabric, ensuring their scalability and efficiency. Analyze large datasets to identify trends, patterns, and insights to support decision-making. Collaborate with cross-functional teams to integrate AI/ML solutions into business processes and banking systems. Maintain and optimise deployed models and ensure their continuous performance. Keep up to date with industry trends, technologies, and best practices in AI and ML, specifically within the finance industry. Qualifications Education: Bachelor s/Master s degree in Computer Science, Data Science, Engineering, or related field. Certifications: Relevant certifications in Data Science, Azure AI, or Machine Learning is a plus. Technical Skills Expertise in Machine Learning (ML) algorithms (Supervised and Unsupervised). Strong experience with Azure Fabric and related Azure cloud services. Proficient in Python, R, and data science libraries (Pandas, Scikit-learn, TensorFlow). Experience in AI and Deep Learning models, including neural networks. Working knowledge of big data technologies such as Spark, Hadoop, and Databricks. Experience with version control systems (Git, GitHub, etc.). Soft Skills Excellent problem-solving and analytical skills. Strong communication skills, with the ability to present complex data insights clearly to non-technical stakeholders. Ability to work effectively in a collaborative, cross-functional environment. Strong attention to detail and ability to manage multiple tasks simultaneously. A passion for continuous learning and staying updated on new technologies. Experience in the banking or financial services industry. Familiarity with DevOps practices for ML/AI model deployment. Knowledge of cloud-native architecture and containerization (Docker, Kubernetes). Familiarity with Deep Learning and Natural Language Processing (NLP) techniques. 8-12 years of experience in Data Science, with hands-on experience in ML, AI, and working within the finance or banking industry. Proven track record of designing and deploying machine learning models and working with Azure Fabric. Experience with client-facing roles and delivering solutions that impact business decision-making. Competitive salary and annual performance-based bonuses Comprehensive health and optional Parental insurance. Retirement savings plans and tax savings plans. Work-Life Balance: Flexible work hours Timely and effective delivery of ML/AI models that solve complex business problems. Continuous improvement and optimisation of deployed models. High-quality insights and data-driven solutions delivered for business stakeholders. Client satisfaction with AI/ML solutions implemented within the banking domain. Number of successful ML/AI models deployed and their performance post-deployment. Model accuracy and predictive capability (based on business goals). Client feedback on AI-driven solutions. Completion time for delivering actionable data-driven insights. Team collaboration and mentoring effectiveness with junior data scientists. Click here to upload your CV / Resume We accept PDF, DOC, DOCX, JPG and PNG files Verification code successfully sent to registered email Invalid Verification Code! Thanks for the verification! Our support team will contact you shortly!.

Data Scientist II With over 140 million users, Junglee Games is a leader in the online skill gaming space. Founded in San Francisco in 2012 and part of the Flutter Entertainment Group, we are revolutionizing how people play games. Our notable games include Howzat, Junglee Rummy, and Junglee Poker. Our team comprises over 1000 talented individuals who have worked on internationally acclaimed AAA titles like Transformers and Star Wars: The Old Republic and contributed to Hollywood hits such as Avatar. Junglee s mission is to build entertainment for millions of people around the world and connect them through games. Junglee Games is not just a gaming company but a blend of innovation, data science, cutting-edge tech, and, most importantly, a values-driven culture that is creating the next set of conscious leaders. Job overview As a Data Scientist II / III, you will be responsible for solving complex business problems using advanced data science techniques. You will lead the design and development of machine learning models, conduct statistical analyses, and collaborate with cross-functional teams to drive actionable insights. Your role will include both technical hands-on work and mentorship of junior data scientists. Job Location : Gurgaon / Bengaluru Key Responsibilities Assist in the development and implementation of machine learning models and algorithms to address business problems, including predictive modeling, classification, regression, clustering, and natural language processing (NLP). Conduct statistical analysis to uncover trends, patterns, and actionable insights from large datasets. Work with senior data scientists and business stakeholders to understand project goals and contribute to data-driven solutions. Support the design and maintenance of data pipelines for data preprocessing, model training, evaluation, and basic deployment. Collaborate with software and data engineering teams to ensure smooth integration of models into production environments. Create dashboards, visualizations, and reports to communicate findings clearly to business users. Contribute to codebase quality and documentation, following best practices for reproducibility and scalability. Keep abreast of industry trends in machine learning and data science tools, and share relevant learnings with the team. Participate in model validation, tuning, and performance monitoring to improve model accuracy and efficiency. Qualifications & skills required 3 - 6 years of experience in data science, machine learning, or a related field, with a strong portfolio of projects. Advanced knowledge of machine learning algorithms (e.g., random forests, gradient boosting, deep learning) and statistical methods. Proficiency in programming languages such as Python, R, and SQL. Hands-on experience with machine learning frameworks and libraries such as TensorFlow, PyTorch, Scikit-learn, and XGBoost.\ Strong experience working with large datasets, data cleaning, and preprocessing. Solid understanding of data visualization tools like Tableau, Power BI, or Matplotlib/Seaborn. Experience with big data technologies (e.g., Hadoop, Spark) and cloud platforms (e.g., AWS, GCP, Azure) is a plus. Strong problem-solving skills and the ability to think critically about data and its implications for business strategy. Excellent communication skills, with the ability to explain complex technical concepts to non-technical stakeholders. Experience in mentoring junior data scientists and leading data science projects is highly preferred. Be a part of Junglee Games to: Value Customers & Data - Prioritize customers, use data-driven decisions, master KPIs, and leverage ideation and A/B testing to drive impactful outcomes. Inspire Extreme Ownership - We embrace ownership, collaborate effectively, and take pride in every detail to ensure every game becomes a smashing success. Lead with Love - We reject micromanagement and fear, fostering open dialogue, mutual growth, and a fearless yet responsible work ethic. Embrace change - Change drives progress and our strength lies in adapting swiftly and recognizing when to evolve to stay ahead. Play the Big Game - We think big, challenge norms, and innovate boldly, driving impactful results through fresh ideas and inventive problem-solving. Avail a comprehensive benefits package that includes paid gift coupons, fitness plans, gadget allowances, fuel costs, family healthcare, and much more. Know more about us Explore the world of Junglee Games through our website, www.jungleegames.com. Get a glimpse of what Life at Junglee Games looks like on LinkedIn. Here is a quick snippet of the Junglee Games Offsite 24 Liked what you saw so far? Be A Junglee

Our Tech Stack: Java, Spring, Rest API, Microservices, Kafka, Spark, NodeJS, AWS, Kubernetes, Terraform, AngularJS What you ll do Identify $ opportunities - think big picture, work with product, tech and customer-facing teams to identify the largest customer problems that can be solved using ML. Build business cases through a combination of market research and internal analytics Stakeholder relationships and strong communication - work closely with a wide variety of stakeholders to build cohesive plans and execute them. Influence senior leadership through a data-driven approach, including but not limited to market research, customer case studies and pilots/experimentation. Technical expertise, simplify complexity - build end to end ML models, be it classification/ unsupervised/ LLMs using a combination of structured and unstructured data. Work with upstream data engineering and software engineering teams to procure, process and transform data into meaningful features. Focus particularly on the data engineering aspect of the model building lifecycle. Always work backwards from the customer, to identify the simplest feasible solutions that can add maximum value. End to end ownership, delivering results - Take models into production and maintain them through effective ML engineering, demonstrate tangible business value, and deliver solutions rather than products. Qualifications- 5+ years of experience in the data science/machine learning domain, preferably with hands-on end-to-end model building experience Strong data engineering background, with ETL experience, building and maintaining pipelines, data modeling, data warehousing concepts, and familiarity with Big Data techniques Curious mind to learn, explore and identify biggest customer opportunities Build strong relationships across both technical and business/product teams, earn trust with leadership Driven towards forming opinions and conclusions through data and experimentation, rather than anecdotes and hearsay Willingness to dive deep into the tech stack as well as hands-on coding Experience in building end to end ML models, across the ML lifecycle Strong communication and leadership presence Technical skills- hands on with scripting required, with knowledge or willingness to learn tools/softwares. Knowledge of R, SQL, Python, Statistical modeling, experience with AWS/Azure/GCP ML suite Experience in the following domains/industries preferred- SaaS, ecommerce, pricing or payments Bachelors/Masters in a technical or natural sciences domain from a top university

Are you passionate about applying machine learning and statistical modeling to revolutionize financial systems that handle billions of dollars in transactions Our team faces a unique challenge: developing intelligent systems to process, analyze, and derive insights from massive financial datasets generated across Amazons global operations. This includes millions of customer transactions, vendor payments, inventory movements, commission calculations, and tax collections across hundreds of jurisdictions worldwide. As an Applied Scientist, you will: Design and implement novel machine learning solutions for complex financial problems Work with large-scale distributed systems and real-time data processing Develop automated decision-making systems for financial workflows Create scalable algorithms that balance accuracy, latency, and computational efficiency Collaborate with software engineers to productionize ML models The ideal candidate will have: Experience in machine learning, statistical modeling, and data analysis Experience with large-scale distributed systems and cloud computing Proven track record of solving complex analytical problems Excellence in scientific programming (Python, R, or similar) communication skills to collaborate with cross-functional teams Passion for mentoring and technical leadership Youll join a team that values innovation and scientific rigor, working alongside world-class engineers and scientists. Youll have the opportunity to influence the architecture of next-generation financial systems while solving novel problems in machine learning and automated decision-making. The ideal candidate will have: Experience in machine learning, statistical modeling, and data analysis Experience with large-scale distributed systems and cloud computing Proven track record of solving complex analytical problems Excellence in scientific programming (Python, R, or similar) Communication skills to collaborate with cross-functional teams Passion for mentoring and technical leadership About the team The Disputes management team manages systems handling vendor billing disputes across Amazons global operations. These disputes arise from invoice matching discrepancies, resulting in short payments due to quantity and price variances, as well as receivables from vendor returns and other deductions. The Dispute Management System enables dispute creation through multiple channels (Vendor Central, FinOps Central), provides automated research and recommendations, and facilitates communication between vendors and FinOps analysts. Our platform streamlines the entire dispute lifecycle, from initial filing through final resolution, ensuring accurate handling of financial claims while maintaining strong vendor relationships. Experience programming in Java, C++, Python or related language Experience in any of the following areas: algorithms and data structures, parsing, numerical optimization, data mining, parallel and distributed computing, high-performance computing B.tech/M.tech/Phd Experience developing and implementing deep learning algorithms, particularly with respect to computer vision algorithms Experience in professional software development

S3B Global is looking for Data Scientist to join our dynamic team and embark on a rewarding career journey. Undertaking data collection, preprocessing and analysis Building models to address business problems Presenting information using data visualization techniques Identify valuable data sources and automate collection processes Undertake preprocessing of structured and unstructured data Analyze large amounts of information to discover trends and patterns Build predictive models and machine - learning algorithms Combine models through ensemble modeling Present information using data visualization techniques Propose solutions and strategies to business challenges Collaborate with engineering and product development teams

In the IBM Chief Information Office,you wi be part of a dynamic team driving the future of AI and data science in arge-scae enterprise transformations. We offer a coaborative environment where your technica expertise wi be vaued, and your professiona deveopment wi be supported. Join us to work on chaenging projects, everage the atest technoogies, and make a tangibe impact on eading organisations. As a Data Scientist within IBM's Chief Information Office, you wi support AI-driven projects across the enterprise. You wi appy your technica skis in AI, machine earning, and data anaytics to assist in impementing data-driven soutions that aign with business goas. This roe invoves working with team members to transate data insights into actionabe recommendations. Key Responsibiities: Technica Execution and Leadership: Deveop and depoy AI modes and data anaytics soutions. Support the impementation and optimisation of AI-driven strategies per business stakehoder requirements. Hep refine data-driven methodoogies for transformation projects. Data Science and AI: Design and impement machine earning soutions and statistica modes, from probem formuation through depoyment, to anayse compex datasets and generate actionabe insights. Learn and utiise coud patforms to ensure the scaabiity of AI soutions. Leverage reusabe assets and appy IBM standards for data science and deveopment. Project Support: Lead and contribute to various stages of AI and data science projects, from data exporation to mode deveopment. Monitor project timeines and hep resove technica chaenges. Design and impement measurement frameworks to benchmark AI soutions, quantifying business impact through KPIs. Coaboration: Ensure aignment to stakehoders strategic direction and tactica needs. Work with data engineers, software deveopers, and other team members to integrate AI soutions into existing systems. Contribute technica expertise to cross-functiona teams. Required education Bacheor's Degree Preferred education Master's Degree Required technica and professiona expertise Bacheors or Masters in Computer Science, Data Science, Statistics, or a reated fied is required; an advanced degree is strongy preferred Experience: 5+ yearsof experience in data science, AI, or anaytics with a focus on impementing data-driven soutions Experience with data ceaning, data anaysis, A/B testing, and data visuaization Experience with AI technoogies through coursework or projects Technica Skis: Proficiency in SQL and Python for performing data anaysis and deveoping machine earning modes Knowedge of common machine earning agorithms and frameworksinear regression, decision trees, random forests, gradient boosting (e.g., XGBoost, LightGBM), neura networks, and deep earning frameworks such as TensorFow and PyTorch Experience with coud-based patforms and data processing frameworks Understanding of arge anguage modes (LLMs) Famiiarity with IBMs watsonx product suite Famiiarity with object-oriented programming Anaytica Skis: Strong probem-soving abiities and eagerness to earn

As an Data Engineer at IBM you wi harness the power of data to unvei captivating stories and intricate patterns. You' contribute to data gathering, storage, and both batch and rea-time processing. Coaborating cosey with diverse teams, you' pay an important roe in deciding the most suitabe data management systems and identifying the crucia data required for insightfu anaysis. As a Data Engineer, you' tacke obstaces reated to database integration and untange compex, unstructured data sets. In this roe, your responsibiities may incude: Impementing and vaidating predictive modes as we as creating and maintain statistica modes with a focus on big data, incorporating a variety of statistica and machine earning techniques Designing and impementing various enterprise search appications such as Easticsearch and Spunk for cient requirements Work in an Agie, coaborative environment, partnering with other scientists, engineers, consutants and database administrators of a backgrounds and discipines to bring anaytica rigor and statistica methods to the chaenges of predicting behaviour’s. Buid teams or writing programs to ceanse and integrate data in an efficient and reusabe manner, deveoping predictive or prescriptive modes, and evauating modeing resuts Required education Bacheor's Degree Preferred education Master's Degree Required technica and professiona expertise Proof of Concept (POC) DeveopmentDeveop POCs to vaidate and showcase the feasibiity and effectiveness of the proposed AI soutions. Hep in showcasing the abiity of Gen AI code assistant to refactor/rewrite and document code from one anguage to another Document soution architectures, design decisions, impementation detais, and essons earned. Stay up to date with the atest trends and advancements in AI, foundation modes, and arge anguage modes. Evauate emerging technoogies, toos, and frameworks to assess their potentia impact on soution design and impementation Preferred technica and professiona experience Experience and working knowedge in COBOL & JAVA woud be preferred Having experience in Code generation, code matching & code transation everaging LLM capabiities woud be a Big pus Demonstrate a growth mindset to understand cients' business processes and chaenges

As an Data Engineer at IBM you wi harness the power of data to unvei captivating stories and intricate patterns. You' contribute to data gathering, storage, and both batch and rea-time processing. Coaborating cosey with diverse teams, you' pay an important roe in deciding the most suitabe data management systems and identifying the crucia data required for insightfu anaysis. As a Data Engineer, you' tacke obstaces reated to database integration and untange compex, unstructured data sets. In this roe, your responsibiities may incude: Impementing and vaidating predictive modes as we as creating and maintain statistica modes with a focus on big data, incorporating a variety of statistica and machine earning techniques Designing and impementing various enterprise search appications such as Easticsearch and Spunk for cient requirements Work in an Agie, coaborative environment, partnering with other scientists, engineers, consutants and database administrators of a backgrounds and discipines to bring anaytica rigor and statistica methods to the chaenges of predicting behaviour’s. Buid teams or writing programs to ceanse and integrate data in an efficient and reusabe manner, deveoping predictive or prescriptive modes, and evauating modeing resuts Required education Bacheor's Degree Preferred education Master's Degree Required technica and professiona expertise Proof of Concept (POC) DeveopmentDeveop POCs to vaidate and showcase the feasibiity and effectiveness of the proposed AI soutions. Hep in showcasing the abiity of Gen AI code assistant to refactor/rewrite and document code from one anguage to another Document soution architectures, design decisions, impementation detais, and essons earned. Stay up to date with the atest trends and advancements in AI, foundation modes, and arge anguage modes. Evauate emerging technoogies, toos, and frameworks to assess their potentia impact on soution design and impementation Preferred technica and professiona experience Experience and working knowedge in COBOL & JAVA woud be preferred Having experience in Code generation, code matching & code transation everaging LLM capabiities woud be a Big pus Demonstrate a growth mindset to understand cients' business processes and chaenges

As an Data Engineer at IBM you wi harness the power of data to unvei captivating stories and intricate patterns. You' contribute to data gathering, storage, and both batch and rea-time processing. Coaborating cosey with diverse teams, you' pay an important roe in deciding the most suitabe data management systems and identifying the crucia data required for insightfu anaysis. As a Data Engineer, you' tacke obstaces reated to database integration and untange compex, unstructured data sets. In this roe, your responsibiities may incude Impementing and vaidating predictive modes as we as creating and maintain statistica modes with a focus on big data, incorporating a variety of statistica and machine earning techniques Designing and impementing various enterprise search appications such as Easticsearch and Spunk for cient requirements Work in an Agie, coaborative environment, partnering with other scientists, engineers, consutants and database administrators of a backgrounds and discipines to bring anaytica rigor and statistica methods to the chaenges of predicting behaviours. Buid teams or writing programs to ceanse and integrate data in an efficient and reusabe manner, deveoping predictive or prescriptive modes, and evauating modeing resuts Required education Bacheor's Degree Preferred education Master's Degree Required technica and professiona expertise Proof of Concept (POC) DeveopmentDeveop POCs to vaidate and showcase the feasibiity and effectiveness of the proposed AI soutions. Hep in showcasing the abiity of Gen AI code assistant to refactor/rewrite and document code from one anguage to another Document soution architectures, design decisions, impementation detais, and essons earned. Stay up to date with the atest trends and advancements in AI, foundation modes, and arge anguage modes. Evauate emerging technoogies, toos, and frameworks to assess their potentia impact on soution design and impementation Preferred technica and professiona experience Experience and working knowedge in COBOL & JAVA woud be preferred Having experience in Code generation, code matching & code transation everaging LLM capabiities woud be a Big pus Demonstrate a growth mindset to understand cients' business processes and chaenges

We are seeking a highy skied Advanced Anaytics Speciaist to join our dynamic team. The successfu candidate wi be responsibe for everaging advanced anaytics techniques to derive actionabe insights, inform business decisions, and drive strategic initiatives. This roe requires a deep understanding of data anaysis, statistica modeing, machine earning, and data visuaization. In this roe, you wi be responsibe for architecting and deivering AI soutions using cutting-edge technoogies, with a strong focus on foundation modes and arge anguage modes. You wi work cosey with customers, product managers, and deveopment teams to understand business requirements and design custom AI soutions that address compex chaenges. Experience with toos ike Github Copiot, Amazon Code Whisperer etc. is desirabe. Success is our passion, and your accompishments wi refect this, driving your career forward, propeing your team to success, and heping our cients to thrive. Day-to-Day Duties: Proof of Concept (POC) DeveopmentDeveop POCs to vaidate and showcase the feasibiity and effectiveness of the proposed AI soutions. Coaborate with deveopment teams to impement and iterate on POCs, ensuring aignment with customer requirements and expectations. Hep in showcasing the abiity of Gen AI code assistant to refactor/rewrite and document code from one anguage to another, particuary COBOL to JAVA through rapid prototypes/ PoC Documentation and Knowedge SharingDocument soution architectures, design decisions, impementation detais, and essons earned. Create technica documentation, white papers, and best practice guides. Contribute to interna knowedge sharing initiatives and mentor new team members. Industry Trends and InnovationStay up to date with the atest trends and advancements in AI, foundation modes, and arge anguage modes. Evauate emerging technoogies, toos, and frameworks to assess their potentia impact on soution design and impementation Required education Bacheor's Degree Preferred education Master's Degree Required technica and professiona expertise Deveop and impement advanced anaytica modes and agorithms to sove compex business probems. Anayze arge datasets to uncover trends, patterns, and insights that drive business performance. Coaborate with cross-functiona teams to identify key business chaenges and opportunities. Create and maintain data pipeines and workfows to ensure the accuracy and integrity of data. Design and deiver insightfu reports and dashboards to communicate findings to stakehoders. Stay up to date with the atest advancements in anaytics, machine earning, and data science. Provide technica expertise and mentorship to junior team members. QuaificationsBacheor’s or Master’s degree in Data Science, Statistics, Mathematics, Computer Science, or a reated fied.Proven experience in advanced anaytics, data science, or a simiar roe.Proficiency in programming anguages such as Python, R, or SQL.Experience with data visuaization toos ike Tabeau, Power BI, or simiar. Strong understanding of statistica modeing and machine earning agorithms.Exceent anaytica, probem-soving, and critica thinking skis.Abiity to communicate compex anaytica concepts to non-technica stakehoders.Experience with big data technoogies (e.g., Hadoop, Spark) is a pus. Preferred Skis: Famiiarity with coud-based anaytics patforms (e.g., AWS, Azure). Knowedge of natura anguage processing (NLP) and deep earning techniques. Experience with project management and agie methodoogies Preferred technica and professiona experience Famiiarity with coud-based anaytics patforms (e.g., AWS, Azure). Knowedge of natura anguage processing (NLP) and deep earning techniques. Experience with project management and agie methodoogies

Work with broader team to buid, anayze and improve the AI soutions. You wi aso work with our software deveopers in consuming different enterprise appications Required education Bacheor's Degree Preferred education Master's Degree Required technica and professiona expertise Resource shoud have 5-7 years of experience. Sound knowedge of Python and shoud know how to use the ML reated services. Proficient in Python with focus on Data Anaytics Packages. Strategy Anayse arge, compex data sets and provide actionabe insights to inform business decisions. Strategy Design and impementing data modes that hep in identifying patterns and trends. Coaboration Work with data engineers to optimize and maintain data pipeines. Perform quantitative anayses that transate data into actionabe insights and provide anaytica, data-driven decision-making. Identify and recommend process improvements to enhance the efficiency of the data patform. Deveop and maintain data modes, agorithms, and statistica modes Preferred technica and professiona experience Experience with conversation anaytics. Experience with coud technoogies Experience with data exporation toos such as Tabeu

As an Data Engineer at IBM you wi harness the power of data to unvei captivating stories and intricate patterns. You' contribute to data gathering, storage, and both batch and rea-time processing. Coaborating cosey with diverse teams, you' pay an important roe in deciding the most suitabe data management systems and identifying the crucia data required for insightfu anaysis. As a Data Engineer, you' tacke obstaces reated to database integration and untange compex, unstructured data sets. In this roe, your responsibiities may incude: Impementing and vaidating predictive modes as we as creating and maintain statistica modes with a focus on big data, incorporating a variety of statistica and machine earning techniques Designing and impementing various enterprise search appications such as Easticsearch and Spunk for cient requirements Work in an Agie, coaborative environment, partnering with other scientists, engineers, consutants and database administrators of a backgrounds and discipines to bring anaytica rigor and statistica methods to the chaenges of predicting behaviour’s. Buid teams or writing programs to ceanse and integrate data in an efficient and reusabe manner, deveoping predictive or prescriptive modes, and evauating modeing resuts Required education Bacheor's Degree Preferred education Master's Degree Required technica and professiona expertise Proof of Concept (POC) DeveopmentDeveop POCs to vaidate and showcase the feasibiity and effectiveness of the proposed AI soutions. Hep in showcasing the abiity of Gen AI code assistant to refactor/rewrite and document code from one anguage to another Document soution architectures, design decisions, impementation detais, and essons earned. Stay up to date with the atest trends and advancements in AI, foundation modes, and arge anguage modes. Evauate emerging technoogies, toos, and frameworks to assess their potentia impact on soution design and impementation Preferred technica and professiona experience Experience and working knowedge in COBOL & JAVA woud be preferred Having experience in Code generation, code matching & code transation everaging LLM capabiities woud be a Big pus Demonstrate a growth mindset to understand cients' business processes and chaenges

Dreaming big is in our DNA. It’s who we are as a company. It’s our culture. It’s our heritage. And more than ever, it’s our future. A future where we’re always looking forward. Always serving up new ways to meet life’s moments. A future where we keep dreaming bigger. We look for people with passion, talent, and curiosity, and provide them with the teammates, resources and opportunities to unleash their full potential. The power we create together – when we combine your strengths with ours – is unstoppable. Are you ready to join a team that dreams as big as you do? AB InBev GCC was incorporated in 2014 as a strategic partner for Anheuser-Busch InBev. The center leverages the power of data and analytics to drive growth for critical business functions such as operations, finance, people, and technology. The teams are transforming Operations through Tech and Analytics. Do You Dream Big? We Need You. Job Title: Data Scientist Location: Bangalore Reporting to: Manager- Analytics/ Senior Manager-Analytics Purpose of the role Contributing to the Data Science efforts of AB InBevʼs global non-commercial analytics capability of Supply Analytics. Candidate will be required to contribute and may also need to guide the DS team staffed on the area and assess the efforts required to scale and standardize the use of Data Science across multiple ABI markets KEY TASKS AND ACCOUNTABILITIES Understand the business problem and translate that to an analytical problem; participate in the solution design process. Manage the full AI/ML lifecycle, including data preprocessing, feature engineering, model training, validation, deployment, and monitoring. Develop reusable and modular Python code adhering to OOP (Object-Oriented Programming) principles. Design, develop, and deploy machine learning models into production environments on Azure. Collaborate with data scientists, software engineers, and other stakeholders to meet business needs. Ability to communicate findings clearly to both technical and business stakeholders. Qualifications, Experience, Skills Level of educational attainment required (1 or more of the following) B.Tech /BE/ Masters in CS/IS/AI/ML Previous Work Experience Required Minimum 3 years of relevant experience Technical Skills Required Must Have Strong expertise in Python, including advanced knowledge of OOP concepts. Exposure to AI/ML methodologies with a previous hands-on experience in ML concepts like forecasting, clustering, regression, classification, optimization using Python Azure Tech Stack, Databricks, ML Flow in any cloud platform Airflow for orchestrating and automating workflows MLOPS concepts and containerization tools like Docker Experience with version control tools such as Git. Consistently display an intent for problem solving Strong communication skills (vocal and written) Ability to effectively communicate and present information at various levels of an organization. Good To Have Preferred industry exposure in Manufacturing Domain Product building experience Other Skills Required Passion for solving problems using data Detail oriented, analytical and inquisitive Ability to learn on the go Ability to work independently and with others We dream big to create future with more cheers