91 Supervised Learning Jobs

National Payment Corporation of India (NPCI) is Hiring! Hiring Data Scientist (with Statistics, Quantitative Economics, Operations Research (OR), Bayesian Modelling experience only) Experience: 5 - 10 Years (Mandatory)Tier-1 schools/colleges: ISI, IITs (Kharagpur, Chennai, Kanpur and Bombay), BITS and DSE ( D elhi S chool of E conomics) or any similar Mandatory (Must) Must have experience of 5-10 years working in Statistics, Quantitative Economics, Operations Research (OR), Bayesian Modelling or any similar fields (Must) Atleast a Bachelors level education in Statistics, Economics, Industrial Engineering or any similar fields from Tier-1 schools/colleges Exposed to Supervised and Un-supervised Learning methods/algorithms from all genres viz. Statistical (e.g. Logistic, Discriminant, K-means etc), Machine Learning (e.g. Random Forest, SVM etc), or Deep Learning (e.g. NN, CNN etc) Excellent Python and SQL skills handling large volume of data have the flair to pick-up any language/technology/tool in quick time Passion in solving business problems with data Good storytelling and articulation skills Good teaming skills Proactive and can figure out things on his/her own attitude Should have good sense of ownership Ability to manage projects from conceptualization to presentation/delivery/adoption Good-to-have Some banking /finance background Worked with multiple business partners kind of scenario/environment Some stakeholder management skills External conference presentations / White Papers / Articles Publishing / Patents Some exposures using Google OR, IBM ILOG etc OR tools Some exposure to NLP ( N atural L anguage P rocessing)

As a Tech Lead specializing in Data & Analytics, you will be responsible for the following: **Role Overview:** You will play a crucial role in handling and processing data efficiently, ensuring optimal performance and data integrity. Additionally, you will be involved in data analysis, statistical modeling, and visualization to derive meaningful insights for the organization. **Key Responsibilities:** - Proficient in SQL Server with a focus on query optimization. - Expertise in application data design and process management. - Extensive knowledge of data modeling techniques. - Hands-on experience with Azure Data Factory, Azure Synapse Analytics, and Microsoft Fabric. - Experience working with Azure Databricks. - Expertise in data warehouse development, including SSIS and SSAS. - Proficiency in ETL processes, data cleaning, and normalization. - Familiarity with big data technologies like Hadoop, Spark, and Kafka. - Understanding of data governance, compliance, and security within Azure environments. - Experience in data analysis, statistical modeling, and machine learning techniques. - Proficiency in analytical tools such as Python, R, and libraries like Pandas and NumPy. - Strong expertise in Power BI for data visualization, data modeling, and DAX queries. - Experience in implementing Row-Level Security in Power BI. - Ability to work with medium-complex data models and understand application data design quickly. - Familiar with industry best practices for Power BI and performance optimization. - Understanding of machine learning algorithms, including supervised, unsupervised, and deep learning techniques. **Qualifications Required:** - Ability to lead a team of 4-5 developers and take ownership of deliverables. - Commitment to continuous learning and staying updated with new technologies. - Strong communication skills in English, both written and verbal. - Effective interaction with customers during project implementation. - Capability to explain complex technical concepts to non-technical stakeholders. In addition to technical skills, the following skills are preferred for this role: - Data Management: SQL, Azure Synapse Analytics, Azure Analysis Service, Data Marts, Microsoft Fabric - ETL Tools: Azure Data Factory, Azure Databricks, Python, SSIS - Data Visualization: Power BI, DAX This comprehensive role requires a blend of technical expertise, leadership skills, and effective communication to drive successful data and analytics projects within the organization.,

You will be responsible for utilizing advanced analytics, machine learning, and statistical modeling techniques to help the retail business make data-driven decisions. You will work closely with teams across marketing, product management, supply chain, and customer insights to drive business strategies and innovations. **Key Responsibilities:** - Utilize your deep understanding of the retail industry to design AI solutions that address critical retail business needs. - Gather and clean data from various retail sources like sales transactions, customer interactions, inventory management, website traffic, and marketing campaigns. - Apply machine learning algorithms like classification, clustering, regression, and deep learning to enhance predictive models. - Use AI-driven techniques for personalization, demand forecasting, and fraud detection. - Utilize advanced statistical methods to optimize existing use cases and build new products. - Stay updated on the latest trends in data science and retail technology. - Collaborate with executives, product managers, and marketing teams to translate insights into business actions. **Qualifications Required:** - Strong analytical and statistical skills. - Expertise in machine learning and AI. - Experience with retail-specific datasets and KPIs. - Proficiency in data visualization and reporting tools. - Ability to work with large datasets and complex data structures. - Strong communication skills to interact with both technical and non-technical stakeholders. - A solid understanding of the retail business and consumer behavior. - Programming Languages: Python, R, SQL, Scala - Data Analysis Tools: Pandas, NumPy, Scikit-learn, TensorFlow, Keras - Visualization Tools: Tableau, Power BI, Matplotlib, Seaborn - Big Data Technologies: Hadoop, Spark, AWS, Google Cloud - Databases: SQL, NoSQL (MongoDB, Cassandra) You will need a minimum of 3 years of experience and a Bachelor's or Master's degree in Data Science, Statistics, Computer Science, Mathematics, or a related field to qualify for this position.,

About the Team Our Data Science team is the Avengers to Meeshos S.H.I.E.L.D ???. And why not? We are the ones who assemble during the toughest challenges and devise creative solutions, building intelligent systems for millions of our users looking at a thousand different categories of products. Weve barely scratched the surface, and have amazing challenges in charting the future of commerce for Bharat. Our typical day involves dealing with fraud detection, inventory optimisation, and platform vernacularisation. As Lead Data Scientist, you will navigate uncharted territories with us, discovering new paths to creating solutions for our users.?? You will be at the forefront of interesting challenges and solve unique customer problems in an untapped market. But wait theres more to us. Our team is huge on having a well-rounded personal and professional life. When we aren't nose-deep in data, you will most likely find us belting Summer of 69 at the nearest Karaoke bar, or debating who the best Spider-Man is: Maguire, Garfield, or Holland? You tell us ?? About the Role Love deep data? Does innovative-thinking describe you? Then you may be our next Lead Data Scientist. In this role youll be the Dumbledore to our team of wizards - our junior data scientists. You will be responsible for transforming scattered pieces of information into valuable data that can be used to achieve goals effectively. You will extract and mine critical bits of information and drive insightful discussions that result in app innovations. What you will do Own and deliver solutions across multiple charters by formulating well-scoped problem statements and driving them to execution with measurable impact Mentor a team of data scientists (DS2s and DS3s), helping them with project planning, execution, and on-call issue resolution Design and optimize key user journeys (e.g., Reseller Experience, Search, Fraud Systems) by identifying user intents and behavioral patterns from large-scale data Collaborate with machine learning engineers and big data teams to build scalable ML pipelines and improve inference performance Continuously track and improve model performance using state-of-the-art (SOTA) techniques and libraries Lead experimental design for usability improvements and user growth, leveraging statistical rigor Contribute to system-level thinking by enhancing internal tools, frameworks, and libraries to improve team efficiency and code quality Partner with engineering to ensure data reliability, compliance with security/PII guidelines, and integration of models into production systems Proactively explore new areas of opportunity through research, data mining, and academic collaboration, including publishing and attending top-tier conferences Communicate findings, plans, and results clearly with DS, product, and tech stakeholders, and create technical documentation consumable by both DS and engineering teams Conduct research collaborations with premier colleges and universities Attend conferences and publish research papers What you will need A Bachelor's degree in Computer Science, Data Science, or a related field; a Masters is a plus 6--8 years of experience in data science with a strong track record of building and deploying ML solutions at scale Deep understanding of core ML techniques supervised, unsupervised, and semi-supervised learning along with strong foundations in statistics and linear algebra Exposure to deep learning concepts and architectures (e.g., CNNs, RNNs, Transformers) and their practical applications Proficiency in Python and SQL, with experience in building data pipelines and analytical workflows Hands-on experience with large-scale data processing using Apache Spark, Hadoop/Hive, or cloud platforms such as GCP Strong programming fundamentals and experience writing clean, maintainable, and production-ready code Excellent analytical and problem-solving skills the ability to extract actionable insights from messy and high-volume data Solid grasp of statistical testing, hypothesis validation, and common pitfalls in experimental design Experience designing and interpreting A/B tests, including uplift measurement and segmentation Ability to work closely with product and engineering teams to translate business goals into scalable ML or data solutions Bonus points for: Experience with reinforcement learning or sequence modeling techniques Contributions to ML libraries, internal tools, or research publications

Role Overview: As a Senior Manager for data science, data modeling, and Analytics, you will lead a team of data scientists and analysts while actively contributing to the development and implementation of advanced analytics solutions. This role requires a blend of strategic leadership and hands-on technical expertise to drive data-driven decision-making across the organization. Key Responsibilities: - Design, develop, and deploy advanced machine learning models and statistical analyses to solve complex business problems. - Utilize programming languages such as Python, R, and SQL to manipulate data and build predictive models. - Understand end-to-end data pipelines, including data collection, cleaning, transformation, and visualization. - Collaborate with IT and data engineering teams to integrate analytics solutions into production environments. - Provide thought leadership on solutions and metrics based on the understanding of the nature of business requirements. Team Leadership & Development: - Lead, mentor, and manage a team of data scientists and analysts, fostering a collaborative and innovative environment. - Provide guidance on career development, performance evaluations, and skill enhancement. - Promote continuous learning and adoption of best practices in data science methodologies. - Engage and manage a hierarchical team while fostering a culture of collaboration. Strategic Planning & Execution: - Collaborate with senior leadership to define the data science strategy aligned with business objectives. - Identify and prioritize high-impact analytics projects that drive business value. - Ensure the timely delivery of analytics solutions, balancing quality, scope, and resource constraints. Client Engagement & Stakeholder Management: - Serve as the primary point of contact for clients, understanding their business challenges and translating them into data science solutions. - Lead client presentations, workshops, and discussions to communicate complex analytical concepts in an accessible manner. - Develop and maintain strong relationships with key client stakeholders, ensuring satisfaction and identifying opportunities for further collaboration. - Manage client expectations, timelines, and deliverables, ensuring alignment with business objectives. - Develop and deliver regular reports and dashboards to senior management, market stakeholders, and clients highlighting key insights and performance metrics. - Act as a liaison between technical teams and business units to align analytics initiatives with organizational goals. Cross-Functional Collaboration: - Work closely with cross-capability teams such as Business Intelligence, Market Analytics, Data Engineering to integrate analytics solutions into business processes. - Translate complex data insights into actionable recommendations for non-technical stakeholders. - Facilitate workshops and presentations to promote data-driven conversations across the organization. - Closely work with support functions to provide timely updates to leadership on operational metrics. Governance & Compliance: - Ensure adherence to data governance policies, including data privacy regulations (e.g., GDPR, PDPA). - Implement best practices for data quality, security, and ethical use of analytics. - Stay informed about industry trends and regulatory changes impacting data analytics. Qualifications: - Education: Bachelors or Masters degree in Data Science, Computer Science, Statistics, Mathematics, or a related field. - Experience: 12+ years of experience in advanced analytics, data science, data modeling, machine learning, Generative AI, or a related field with 5+ years in a leadership capacity. - Proven track record of managing and delivering complex analytics projects. - Familiarity with the BFSI/Hi Tech/Retail/Healthcare industry and experience with product, transaction, and customer-level data. - Experience with media data will be advantageous. Technical Skills: - Proficiency in programming languages like Python, R, or SQL. - Experience with data visualization tools (e.g., Tableau, Power BI). - Familiarity with big data platforms (e.g., Hadoop, Spark) and cloud services (e.g., AWS, GCP, Azure). - Knowledge of machine learning frameworks and libraries. Soft Skills: - Strong analytical and problem-solving abilities. - Excellent communication and interpersonal skills. - Ability to influence and drive change within the organization. - Strategic thinker with a focus on delivering business outcomes. Additional Company Details: The job is located in Bengaluru under the brand Merkle on a full-time permanent contract.,

Job Description: You will be responsible for leading the configuration, maintenance, and optimization of the organization's network and security infrastructure to ensure high performance and reliability. Your key responsibilities will include: - Architecting and integrating networks across multiple business units and diverse cloud environments, ensuring seamless connectivity and scalability. - Championing the use of Infrastructure as Code processes to automate and maintain infrastructure consistency, scalability, and up-to-date configurations. - Overseeing the configuration, deployment, and management of F5 Local Traffic Managers (LTMs) and Advanced Security Modules (ASMs) to ensure seamless application delivery and security. - Creating and implementing strategies for integrating cloud Virtual Private Clouds (VPCs), interconnects, and direct connects, ensuring efficient and secure data flow between on-premises and cloud environments. - Proactively identifying opportunities to enhance the network's scalability and resilience, ensuring it can handle growing business demands and traffic loads. - Working closely with infrastructure, application, and security teams to ensure network designs meet cross-functional requirements and adhere to best practices. Qualifications Required: - Minimum of 8 years of relevant work experience and a Bachelor's degree or equivalent experience. Company Details: Our beliefs are the foundation for how we conduct business every day. We live each day guided by our core values of Inclusion, Innovation, Collaboration, and Wellness. Together, our values ensure that we work together as one global team with our customers at the center of everything we do and they push us to ensure we take care of ourselves, each other, and our communities. If you want to learn more about our culture and community, you can visit https://about.pypl.com/who-we-are/default.aspx.,

As an AI/ML Engineer at our company, you will be part of a motivated team focusing on AI and Machine Learning projects. Your role involves working with Python programming and applying AI/ML fundamentals to design and deploy models effectively. **Key Responsibilities:** - Collaborate with senior engineers to design, implement, and deploy AI/ML models. - Write clean, efficient, and maintainable code in Python. - Assist in data pre-processing, feature engineering, and model evaluation. - Contribute to the development of algorithms and models for data extraction and analysis. - Stay updated with the latest advancements in AI/ML technologies and methodologies. **Qualifications Required:** - Bachelor's degree in Computer Science, Engineering, or a related field. - Strong proficiency in Python programming language. - Good understanding of AI/ML fundamentals, including supervised and unsupervised learning, neural networks, and model evaluation techniques. - Familiarity with popular AI/ML libraries and frameworks (e.g., TensorFlow, PyTorch, scikit-learn). - Experience with data manipulation and analysis using libraries like pandas and NumPy. - Strong problem-solving skills and attention to detail. - Excellent written and verbal communication skills. If you have previous projects or coursework related to AI/ML, it would be considered an added advantage. Join us to kickstart your career in AI and Machine Learning by contributing to the development and deployment of cutting-edge AI/ML models.,

The Retail Specialized Data Scientist will play a pivotal role in utilizing advanced analytics, machine learning, and statistical modeling techniques to help the retail business make data-driven decisions. This individual will work closely with teams across marketing, product management, supply chain, and customer insights to drive business strategies and innovations. The ideal candidate should have experience in retail analytics and the ability to translate data into actionable insights. Key Responsibilities: - Utilize deep understanding of the retail industry to design AI solutions for critical business needs. - Gather and clean data from various retail sources like sales transactions, customer interactions, inventory management, website traffic, and marketing campaigns. - Apply machine learning algorithms for classification, clustering, regression, and deep learning to enhance predictive models. - Utilize AI-driven techniques for personalization, demand forecasting, and fraud detection. - Implement advanced statistical methods to optimize existing use cases and develop new products. - Stay informed about the latest trends in data science and retail technology. - Collaborate with executives, product managers, and marketing teams to translate insights into business actions. Professional Skills: - Strong analytical and statistical skills. - Expertise in machine learning and AI. - Experience with retail-specific datasets and KPIs. - Proficiency in data visualization and reporting tools. - Ability to work with large datasets and complex data structures. - Strong communication skills for interaction with technical and non-technical stakeholders. - Solid understanding of the retail business and consumer behavior. Technical Skills: - Programming Languages: Python, R, SQL, Scala - Data Analysis Tools: Pandas, NumPy, Scikit-learn, TensorFlow, Keras - Visualization Tools: Tableau, Power BI, Matplotlib, Seaborn - Big Data Technologies: Hadoop, Spark, AWS, Google Cloud - Databases: SQL, NoSQL (MongoDB, Cassandra) Minimum Qualifications: - Experience: Minimum 3 years of relevant experience. - Educational Qualification: Bachelors or Master's degree in Data Science, Statistics, Computer Science, Mathematics, or a related field. Location: Bangalore / Gurgaon / Mumbai / Chennai / Pune / Hyderabad / Kolkata Must-Have Skills: - Solid understanding of retail industry dynamics and key performance indicators. - Ability to communicate complex data insights to non-technical stakeholders. - Meticulous in ensuring data quality and consistency. - Proficiency in Python for data manipulation, statistical analysis, and machine learning. - Experience with supervised and unsupervised learning algorithms. - Use advanced analytics to optimize pricing strategies based on market demand. Good-to-Have Skills: - Familiarity with big data processing platforms like Apache Spark, Hadoop, or cloud-based platforms. - Experience with ETL processes and tools like Apache Airflow. - Familiarity with designing scalable and efficient data pipelines and architecture. - Experience with data visualization tools like Tableau, Power BI, Matplotlib, and Seaborn.,

Skill required: Delivery - Advanced Analytics Designation: I&F Decision Sci Practitioner Specialist Qualifications: Master of Engineering/Masters in Business Economics Years of Experience: 7 to 11 years About Accenture Accenture is a global professional services company with leading capabilities in digital, cloud and security.Combining unmatched experience and specialized skills across more than 40 industries, we offer Strategy and Consulting, Technology and Operations services, and Accenture Song all powered by the worlds largest network of Advanced Technology and Intelligent Operations centers. Our 699,000 people deliver on the promise of technology and human ingenuity every day, serving clients in more than 120 countries. We embrace the power of change to create value and shared success for our clients, people, shareholders, partners and communities.Visit us at www.accenture.com What would you do Data & AI You will be a core member of Accenture Operations global Data & AI group, an energetic, strategic, high-visibility and high-impact team, to innovate and transform the Accenture Operations business using machine learning, advanced analytics to support data-driven decisioning. What are we looking for Extensive experience in leading Data Science and Advanced Analytics delivery teams Strong statistical programming experience Python or working knowledge on cloud native platforms like AWS Sagemaker is preferred Azure/ GCP Experience working with large data sets and big data tools like AWS, SQL, PySpark, etc. Solid knowledge in at least more than two of the following Supervised and Unsupervised Learning, Classification, Regression, Clustering, Neural Networks, Ensemble Modelling (random forest, boosted tree, etc) Experience in working with Pricing models is a plus Experience in atleast one of these business domains: Energy, CPG, Retail, Marketing Analytics, Customer Analytics, Digital Marketing, eCommerce, Health, Supply Chain Extensive experience in client engagement and business development Ability to work in a global collaborative team environment Quick Learner and Independently deliver results. Qualifications: Masters / Ph.D. Computer science, Engineering, Statistics, Mathematics, Economics or related disciplines. Roles and Responsibilities: Building data science models to uncover deeper insights, predict future outcomes, and optimize business processes for clients. Utilizing advanced statistical and machine learning techniques to develop models that can assist in decision-making and strategic planning. Refining and improving data science models based on feedback, new data, and evolving business needs. Data Scientists in Operations follow multiple approaches for project execution from adapting existing assets to Operations use cases, exploring third-party and open-source solutions for speed to execution and for specific use cases to engaging in fundamental research to develop novel solutions. Data Scientists are expected to collaborate with other data scientists, subject matter experts, sales, and delivery teams from Accenture locations around the globe to deliver strategic advanced machine learning / data-AI solutions from design to deployment. Show more Show less

Skill required: Delivery - Advanced Analytics Designation: I&F Decision Sci Practitioner Assoc Mgr Qualifications: Master of Engineering/Masters in Business Economics Years of Experience: 10 to 14 years About Accenture Accenture is a global professional services company with leading capabilities in digital, cloud and security.Combining unmatched experience and specialized skills across more than 40 industries, we offer Strategy and Consulting, Technology and Operations services, and Accenture Song all powered by the worlds largest network of Advanced Technology and Intelligent Operations centers. Our 699,000 people deliver on the promise of technology and human ingenuity every day, serving clients in more than 120 countries. We embrace the power of change to create value and shared success for our clients, people, shareholders, partners and communities.Visit us at www.accenture.com What would you do Data & AI You will be a core member of Accenture Operations global Data & AI group, an energetic, strategic, high-visibility and high-impact team, to innovate and transform the Accenture Operations business using machine learning, advanced analytics to support data-driven decisioning. What are we looking for Extensive experience in leading Data Science and Advanced Analytics delivery teams Strong statistical programming experience Python or working knowledge on cloud native platforms like AWS Sagemaker is preferred Azure/ GCP Experience working with large data sets and big data tools like AWS, SQL, PySpark, etc. Solid knowledge in at least more than two of the following Supervised and Unsupervised Learning, Classification, Regression, Clustering, Neural Networks, Ensemble Modelling (random forest, boosted tree, etc) Experience in working with Pricing models is a plus Experience in atleast one of these business domains: Energy, CPG, Retail, Marketing Analytics, Customer Analytics, Digital Marketing, eCommerce, Health, Supply Chain Extensive experience in client engagement and business development Ability to work in a global collaborative team environment Quick Learner and Independently deliver results. Qualifications: Masters / Ph.D. Computer science, Engineering, Statistics, Mathematics, Economics or related disciplines. Roles and Responsibilities: Leading team of data scientists to build and deploy data science models to uncover deeper insights, predict future outcomes, and optimize business processes for clients. Refining and improving data science models based on feedback, new data, and evolving business needs. Analyze available data to identify opportunities for enhancing brand equity, improving retail margins, achieving profitable growth, and expanding market share for clients. Data Scientists in Operations follow multiple approaches for project execution from adapting existing assets to Operations use cases, exploring third-party and open-source solutions for speed to execution and for specific use cases to engaging in fundamental research to develop novel solutions. Data Scientists are expected to collaborate with other data scientists, subject matter experts, sales, and delivery teams from Accenture locations around the globe to deliver strategic advanced machine learning / data-AI solutions from design to deployment. Show more Show less

Skill required: Delivery - Advanced Analytics Designation: I&F Decision Science Practitioner Specialist Qualifications: Master of Engineering,Masters in Business Economics Years of Experience: 7 to 11 Years About Accenture Accenture is a global professional services company with leading capabilities in digital, cloud and security.Combining unmatched experience and specialized skills across more than 40 industries, we offer Strategy and Consulting, Technology and Operations services, and Accenture Song all powered by the worlds largest network of Advanced Technology and Intelligent Operations centers. Our 699,000 people deliver on the promise of technology and human ingenuity every day, serving clients in more than 120 countries. We embrace the power of change to create value and shared success for our clients, people, shareholders, partners and communities.Visit us at www.accenture.com What would you do Data & AI. You will be a core member of Accenture Operations global Data & AI group, an energetic, strategic, high-visibility and high-impact team, to innovate and transform the Accenture Operations business using machine learning, advanced analytics to support data-driven decisioning. What are we looking for Extensive experience in leading Data Science and Advanced Analytics delivery teams Strong statistical programming experience Python or working knowledge on cloud native platforms like AWS Sagemaker is preferred Azure/ GCP Experience working with large data sets and big data tools like AWS, SQL, PySpark, etc. Solid knowledge in at least more than two of the following Supervised and Unsupervised Learning, Classification, Regression, Clustering, Neural Networks, Ensemble Modelling (random forest, boosted tree, etc) Experience in working with Pricing models is a plus Experience in atleast one of these business domains: Energy, CPG, Retail, Marketing Analytics, Customer Analytics, Digital Marketing, eCommerce, Health, Supply Chain Extensive experience in client engagement and business development Ability to work in a global collaborative team environment Quick Learner and Independently deliver results.Qualifications: Masters / Ph.D. Computer science, Engineering, Statistics, Mathematics, Economics or related disciplines. Roles and Responsibilities: Leading team of data scientists to build and deploy data science models to uncover deeper insights, predict future outcomes, and optimize business processes for clients. Refining and improving data science models based on feedback, new data, and evolving business needs. Analyze available data to identify opportunities for enhancing brand equity, improving retail margins, achieving profitable growth, and expanding market share for clients. Data Scientists in Operations follow multiple approaches for project execution from adapting existing assets to Operations use cases, exploring third-party and open-source solutions for speed to execution and for specific use cases to engaging in fundamental research to develop novel solutions. Data Scientists are expected to collaborate with other data scientists, subject matter experts, sales, and delivery teams from Accenture locations around the globe to deliver strategic advanced machine learning / data-AI solutions from design to deployment. Show more Show less

Roles and Responsibilities Design and deliver high-quality training programs on data science, machine learning, artificial intelligence, natural language processing, and deep learning. Develop engaging course materials, including presentations, tutorials, and hands-on exercises. Conduct interactive sessions to facilitate knowledge sharing among participants. Provide individualized support to trainees through email or chat platforms. Collaborate with subject matter experts to ensure accuracy of course content. Desired Candidate Profile 3-8 years of experience in teaching/training or related field (data science/machine learning). B.Tech/B.E. degree from a reputed institution in Any Specialization. Strong expertise in Python programming language with proficiency in libraries such as NumPy Pandas etc.

As a highly skilled individual in the field of AI and machine learning, you will be responsible for designing and implementing advanced machine learning models and deep learning algorithms. Your expertise will be utilized to develop scalable ML pipelines using tools such as TensorFlow, PyTorch, Scikit-learn, or similar platforms. You will take the lead in managing the end-to-end model lifecycle, starting from data preparation to deployment and monitoring. Collaboration will be a key aspect of your role, as you will work closely with data engineers, software developers, and domain experts to seamlessly integrate AI/ML solutions into various products. Your responsibilities will also include model tuning, evaluation, and optimization to ensure accuracy and performance meet the desired standards. Additionally, creating technical documentation and presenting your findings to stakeholders will be crucial in this position. To excel in this role, you must hold a Bachelor's or Master's degree in Computer Science, Data Science, Mathematics, or a related field. A Ph.D. would be preferred. Your extensive experience of 10+ years in software engineering or data science, with a minimum of 5+ years focused on AI/ML development, will be invaluable. You should have hands-on expertise in supervised/unsupervised learning, NLP, computer vision, recommendation systems, deep learning frameworks (such as TensorFlow, PyTorch), and model deployment tools like Docker, Flask, FastAPI, Kubernetes, etc. Proficiency in Python and its data ecosystem (Pandas, NumPy, Scikit-learn) is essential for this role. Moreover, strong knowledge of cloud platforms (AWS, GCP, Azure) for model deployment is required. Exceptional problem-solving and communication skills will further enhance your performance in this position. It would be advantageous if you have experience with large language models (LLMs), transformers, generative AI, and familiarity with MLOps tools (MLflow, Kubeflow, Vertex AI). Prior involvement in remote or contract roles, along with contributions to open-source AI/ML projects or research paper publications, would be considered a plus. This is a full-time role with contractual/temporary or freelance opportunities available, with a contract length of 12 months. The work schedule is during the day shift, and the work location is in person. Thank you for considering this exciting opportunity to leverage your AI/ML expertise and drive innovation in a dynamic work environment.,

As an Associate Architect Machine Learning (ML) with 4-7 years of experience, you will play a crucial role in integrating generative AI (Gen AI) capabilities into various Software Development Lifecycle (SDLC) phases to enhance efficiency and innovation. Your primary focus will be on identifying high-impact business opportunities where Gen AI adoption can accelerate project delivery and improve solutioning across multiple domains. This position requires a blend of technical expertise, strategic thinking, and client engagement skills to successfully drive Gen AI implementation. Your responsibilities will include collaborating across multiple projects to identify Gen AI and ML strategies, leading discussions with clients to understand their pain points and recommend AI-driven solutions, actively contributing to strategy and operational meetings, and working closely with project engineering and product teams to implement Gen AI capabilities into production-ready solutions. You will also be involved in conducting proof-of-concepts (POCs) and feasibility studies, assisting teams with ML model selection, training, and deployment, and mentoring junior engineers and data scientists in best practices for ML and Gen AI development. To excel in this role, you must possess strong technical expertise in traditional ML techniques (supervised/unsupervised learning, time series forecasting, NLP) and Gen AI models (LLMs, diffusion models, transformers). Proficiency in Python, TensorFlow, PyTorch, and experience with cloud-based ML services (AWS, GCP, Azure) is essential. You should also be adept at architecting and optimizing scalable AI systems using microservices, containerization, and distributed computing for high availability and cost efficiency. Additionally, you must demonstrate strategic thinking skills by identifying and assessing new Gen AI opportunities in business processes, along with strong client handling and communication abilities to lead client discussions, presentations, and workshops effectively. Preferred qualifications for this role include prior experience in Gen AI solutioning for enterprise use cases, familiarity with LLM fine-tuning, prompt engineering, and knowledge retrieval techniques, as well as experience in deploying ML solutions in production environments at scale. Joining our team will provide you with the opportunity to be at the forefront of AI-driven innovation, collaborate with top AI/ML experts, and work on challenging projects that leverage cutting-edge AI technologies. If you are passionate about ML, Gen AI, and driving innovation, we invite you to apply and be a part of shaping the future of AI-driven solutions. Apply now to embark on this exciting journey with us.,

As a software engineer at Google, you will be part of a dynamic team that develops cutting-edge technologies to revolutionize how billions of users worldwide connect, explore, and interact with information. Our projects encompass a wide range of areas such as information retrieval, distributed computing, system design, networking, security, artificial intelligence, natural language processing, UI design, and mobile technologies. Your role will involve working on pivotal projects that address Google's evolving needs, with the flexibility to transition between teams and projects as both you and our business progress. Google Play is a platform that offers a variety of digital content, including music, movies, books, apps, and games. As a member of the Android and Mobile team focusing on Google Play, you will contribute to diverse aspects such as engineering backend systems, shaping product strategies, and establishing content partnerships. Your efforts will enable users to seamlessly access their purchased content across multiple devices through cloud synchronization. Responsibilities: - Apply expertise in Machine Learning to enhance user safety. - Integrate online/offline systems with various Google platforms to access signals, features, and insights. - Collaborate with subject matter experts to set up data pipelines for analysis and machine learning modeling. - Develop, code, and enhance automated review and detection models. - Lead projects in conjunction with other shopping horizontal teams, leveraging Machine Learning expertise to define projects, solutions, and oversee implementation. Minimum Qualifications: - Bachelor's degree or equivalent practical experience. - 5 years of software development experience in one or more programming languages, along with proficiency in data structures and algorithms. - 3 years of experience with Machine Learning/Artificial Intelligence algorithms and tools, or natural language processing. - 3 years of experience testing, maintaining, or launching software products. - 1 year of experience in software design and architecture. Preferred Qualifications: - Proficiency in C++ or Python. - Knowledge of machine learning concepts such as supervised and unsupervised learning, clustering, semi-supervised learning, anomaly detection, and Large Language Model (LLM) fine-tuning. - Familiarity with data analysis and Machine Learning frameworks. - Understanding of computer science principles and Google infrastructure, including databases, operating systems, algorithms, and Machine Learning technologies.,

You should possess a qualification of M.Tech / M.E / MS / M.Sc / Ph.D in Computer Science or a related discipline (Applied Mathematics, Statistics, Electrical and/or Computer Engineering) with a focus on Artificial Intelligence / Machine Learning. A CGPA of 7.5/10 or above in UG as well as PG level (in case of percentage, 70% or above) is required. You should have a minimum of 2 years of experience. As a team member, you will be responsible for applied research, development, and validation of advanced machine learning and AI algorithms for solving complex real-world problems at scale. Collaborating closely with the product team, you will analyze business problems and product vision to innovate algorithmic solutions. Your role will involve creating prototypes and demonstrations to validate innovative ideas and translating research outcomes into productized innovation by working with AI Engineers and software engineers. Additionally, you will create and maintain research plans, conduct experiments, consolidate and document results, and publish works as appropriate. It is important to document and protect intellectual property (IP) generated from R&D efforts by collaborating with designated teams and/or external agencies. Furthermore, mentoring junior staff to ensure correct procedures are followed, and collaborating with stakeholders, academic/research partners, and peer researchers to deliver tangible outcomes will be part of your responsibilities. The ideal candidate is expected to have a strong foundation in computer science fundamentals and analyzing and designing AI/Machine learning algorithms. Hands-on experience in at least two of the following areas is required: Supervised, unsupervised and semi-supervised machine learning algorithms, Reinforcement Learning, Deep learning & Representation Learning, Knowledge-based systems (knowledge representation, reasoning, and planning; FOL, ontologies etc.), Evolutionary Computing, Probabilistic Graphical Models, Streaming, incremental, and non-stationary learning. You should be proficient in at least one programming language and have experience in implementing AI/machine learning algorithms in Python or R. Additionally, experience with tools/frameworks/libraries such as Jupyter/Zeppelin, scikit-learn, matplotlib, pandas, Tensorflow, Keras, Apache Spark, etc. would be desirable. Applied research experience of at least 2-5 years on real-world problems using AI/Machine Learning techniques is necessary. Having at least one publication in a top-tier conference/journal related to AI/Machine Learning (E.g. ICML, AAAI, NIPS, ICCV, CVPR, KDD, SIGMOD, IJCNN, IJCAI, EMNLP, ICPR, ICDM, etc.) and/or patents would be beneficial. Experience in contributing to open-source projects related to AI/Machine Learning would be considered a strong advantage. This position is for Job Code: DSM_TVM and is located in Trivandrum. For further information, please reach out via email to recruitment@flytxt.com.,

Line of Service Advisory Industry/Sector Not Applicable Specialism Data, Analytics & AI Management Level Manager Job Description & Summary A career within Data and Analytics services will provide you with the opportunity to help organisations uncover enterprise insights and drive business results using smarter data analytics. We focus on a collection of organisational technology capabilities, including business intelligence, data management, and data assurance that help our clients drive innovation, growth, and change within their organisations in order to keep up with the changing nature of customers and technology. We make impactful decisions by mixing mind and machine to leverage data, understand and navigate risk, and help our clients gain a competitive edge. Creating business intelligence from data requires an understanding of the business, the data, and the technology used to store and analyse that data. Using our Rapid Business Intelligence Solutions, data visualisation and integrated reporting dashboards, we can deliver agile, highly interactive reporting and analytics that help our clients to more effectively run their business and understand what business questions can be answered and how to unlock the answers. Job Description: Machine Learning Analytics Manager (BFSI) We are seeking a highly skilled and experienced Machine Learning Analytics Manager with a minimum of 6 years of relevant experience, preferably in the BFSI (Banking, Financial Services, and Insurance) industry. As a Machine Learning Analytics Manager, you will play a key role in leading our data analytics team and driving innovative solutions using machine learning techniques. Responsibilities: ? Team Leadership: Lead and mentor a team of data scientists, analysts, and machine learning engineers to deliver impactful data-driven insights and solutions. Provide guidance and support in problem-solving, algorithm development, and model evaluation. ? Machine Learning Strategy: Collaborate with cross-functional teams to identify and prioritize business challenges that can be addressed through machine learning and data analytics. Develop a comprehensive machine learning strategy aligned with the company&aposs objectives. ? Model Development: Oversee the development of machine learning models and algorithms, including supervised and unsupervised learning methods, regression models, neural networks, and decision trees. ? Data Analysis: Conduct exploratory data analysis to understand underlying patterns, trends, and opportunities in large and complex datasets related to BFSI operations. ? Model Deployment: Drive the integration of machine learning models into production systems, ensuring scalability, efficiency, and accuracy in real-world applications. ? Risk Analysis: Utilize machine learning techniques to assess and mitigate risks in the BFSI domain, including credit risk, fraud detection, and market risk. ? Performance Monitoring: Implement monitoring mechanisms to track model performance and provide continuous improvement to ensure the models' effectiveness over time. ? Collaborative Projects: Collaborate with cross-functional teams, including product managers, business analysts, and IT professionals, to design and implement data- driven solutions for various business use cases. ? Industry Trends: Stay updated with the latest developments and best practices in machine learning, data analytics, and the BFSI industry, and incorporate relevant advancements into the team&aposs projects. Requirements: ? Master&aposs degree in Computer Science, Statistics, Mathematics, or a related field. ? 6+ years of hands-on experience in machine learning and data analytics, with a significant focus on BFSI applications. ? Proficiency in programming languages such as Pyspark, Python or R, experience working with data visualization tools, Azure, AWS, GCP (any one cloud solution) ? Extensive knowledge of machine learning algorithms and techniques, including supervised and unsupervised learning, time series analysis, and natural language processing. ? Strong leadership and team management skills, with the ability to drive projects and collaborate effectively with cross-functional teams and stakeholder management. ? Demonstrated expertise in deploying machine learning models in real-world applications, preferably in the BFSI industry. Excellent problem-solving and analytical skills, with a data-driven approach to decision-making. ? Strong communication skills, both written and verbal, to present complex technical concepts to non-technical stakeholders Mandatory Skills: Machine Learning Preferred Skills: Machine Learning Years of Experience: 8-10 Qualifications: BTech Required Skills Machine Learning Optional Skills Desired Languages (If blank, desired languages not specified) Travel Requirements Available for Work Visa Sponsorship Government Clearance Required Job Posting End Date Show more Show less

About Concentric: Join the journey to reinvent data security. Concentric, a next-generation AI data security start-up, is helping enterprises discover and protect their business-critical data. We are growing fast and expanding rapidly. Our core values are: Trust, Humility, Learning. Location: Pune About the openings: The role will be part of our customer success team. You will work extensively on large datasets to identify and help remediate data risks for customers from diverse domains, and support them as a trusted security advisor. Responsibility: - Analyse customer data on Concentric Platform, extract relevant insights to identify data risks, and develop risk remediation strategies. - Prepare and present data risk reports to customers. Handhold them for implementation of the risk remediation strategies. - Label large datasets for supervised learning of AI models. - Serve as customers" trusted data security advisor, providing subject matter expertise and strategic guidance to drive adoption of the Concentric platform aligned with customer objectives. Preferred Qualification & Skills: - Strong experience with data analytics. Proven ability to extract relevant insights from big volumes of data to solve specific problems. Eye for detecting trends and anomalies in data. - Customer advisory experience, preferably in the data security domain. - Experience with Excel as a data analysis and reporting tool is required. Knowledge of other tools like Python, Kibana, Jira, ppt will be a plus. - Proven team leadership skills. - Broad knowledge of operationalizing data security, regulations, and standards will be an advantage. - Excellent communication skills across various formats and mediums. Strong presentation and facilitation skills. - Use creative problem-solving skills to help customers reach their business goals and maximize the value they are getting from the Concentric platform. - Graduate/Post Graduate in Engineering discipline from a premium institute. - Experience in developing training datasets for AI models and data labeling for supervised learning of AI models.,

As a Data Science Consultant with expertise in machine learning and Python, you will be responsible for the end-to-end architecture of Data Science and machine learning projects. Your role will involve productionizing machine learning models and guiding the development team in implementing machine learning use cases. You will provide technology consulting to define the right Data Science and ML use cases. Your responsibilities will include data collection, profiling, exploratory data analysis, and data preparation. You will be involved in AI model development, tuning, and validation. Utilizing visualization tools such as PowerBI and Tableau, you will present findings to business users and project management teams. Additionally, you will propose ML-based solution approaches, provide estimates for new use cases, and contribute to AI-based modules in Infosys solutions development. In this role, you will continuously explore new advances in AI and execute Proof of Concepts (PoCs). You will also mentor and guide other team members, sharing your knowledge and expertise in ML algorithms, AI domains including NLP, speech, and computer vision, as well as supervised, unsupervised, and reinforcement learning. Your proficiency in tools for data analysis, auto ML, model deployment, and scaling will be key to your success. Preferred Skills: - Expertise in Artificial Intelligence across all domains related to AI - Proficiency in programming languages such as Python - Knowledge of databases - Familiarity with cloud platforms such as Azure, AWS, and GCP Join us in this dynamic role where you will play a crucial part in driving Data Science and machine learning initiatives, contributing to cutting-edge solutions and impacting business outcomes.,

As a Senior Data Scientist at Zinnia, you will be a vital member of our team, playing a key role in developing cutting-edge solutions to drive the growth of life and annuities products. Your expertise in machine learning and forecasting will be instrumental in influencing decision-makers and shaping the future of our business. In this high-impact role, you will independently own and build forecasting models, working closely with stakeholders from Product, Data Engineering & Analytics, and Business Strategy. By leveraging data from various sources, you will provide valuable insights and develop new data-driven tools to enhance customer experiences and streamline internal processes. Your responsibilities will include developing machine learning applications using Python, implementing supervised and unsupervised models such as random forest, gradient boosting, and support vector machines. You will also work on advanced modeling techniques like reinforcement learning and neural networks to deliver prescriptive insights and automated decision-making capabilities. Moreover, you will collaborate with data engineering teams to ensure the quality of data, conduct experiments to measure model impact, and manage training pipelines effectively. Your role will involve translating complex business problems into actionable data science projects and deploying models to production infrastructure. As a mentor and collaborator, you will work with other data scientists and data analysts to foster a culture of learning and innovation within the team. Additionally, you will partner with marketing teams to conceptualize applications that drive company growth and strategy, connecting machine learning solutions with business needs. To excel in this role, you should have a minimum of 5 years of experience in building and validating machine learning models in Python. Your expertise should cover a range of model techniques including supervised and unsupervised learning, as well as advanced techniques like neural networks and natural language modeling. Experience with relational cloud databases and unstructured datasets will also be crucial for success in this position. If you are a highly motivated individual with a passion for data science, a drive to solve complex business challenges, and a desire to make a significant impact in the insurance industry, we invite you to join us at Zinnia and be part of our mission to protect financial futures through innovation and data-driven insights.,

At Novartis, we are committed to reimagining medicine through the utilization of data and digital technologies to revolutionize our interactions with patients, healthcare professionals, and healthcare systems. As a Senior Data Engineer in the Data & Digital Commercial organization, you will play a pivotal role in establishing the technical framework for AI-powered commercial solutions, enhancing engagement, access, and performance on a global scale and within local markets. This role at a mid-management level involves a blend of hands-on data engineering, overseeing deliveries, managing vendors, and collaborating with stakeholders. You will be instrumental in developing pipelines and data platforms that facilitate AI/ML applications in areas such as sales effectiveness, omnichannel marketing, customer segmentation, and real-world commercial insights. In this role, you will be responsible for shaping and owning the product roadmap for AI solutions that drive next-generation commercial capabilities. This includes intelligent targeting, omnichannel orchestration, and optimization of engagement with healthcare professionals. You will drive innovation by exploring new AI technologies, validating concepts through MVPs and pilots, and scaling valuable solutions. Your role will also involve translating commercial objectives into actionable technical requirements and solution architectures. Leading cross-functional teams comprising data science, data engineering, MLOps, and digital product specialists will be a key aspect of your responsibilities. You will oversee the end-to-end technical delivery process, from data ingestion and model development to deployment, monitoring, and retraining. It will be crucial to ensure that the models are performant, scalable, secure, and seamlessly integrated into platforms such as CRM and content engines. Collaborating with commercial stakeholders, including field teams, marketing, and analytics, will be essential for defining needs, aligning priorities, and driving adoption. You will act as a bridge between business and technical teams, effectively communicating trade-offs, timelines, and value propositions. Your thought leadership will be influential at various levels, from operational teams to senior leadership. In addition to technical responsibilities, ensuring compliance with Novartis standards and external regulations is paramount. Embedding ethical AI principles into product design, such as fairness, transparency, and accountability, is essential for responsible AI implementation. The role will require expertise in core technical focus areas such as AI/ML development (supervised learning, NLP, recommender systems), data infrastructure (scalable pipelines, real-time data ingestion, structured/unstructured healthcare data), MLOps (model deployment, versioning, monitoring), integration (REST/gRPC APIs, CRM integration), and cloud platforms (AWS, Azure, GCP). To qualify for this role, you should hold a Bachelor's or Master's degree in computer science, engineering, or a related field. With over 10 years of product management experience, including at least 5 years in AI/ML or data-centric product delivery, you should possess a strong technical foundation and a track record of collaborating closely with engineering and data science teams. Experience in healthcare or life sciences environments is advantageous. At Novartis, we are dedicated to fostering a diverse and inclusive work environment that reflects the patients and communities we serve. We are committed to providing reasonable accommodations for individuals with disabilities during the recruitment process. If you are passionate about making a difference in the lives of patients and communities through innovative science and collaboration, we invite you to join our team at Novartis and be a part of a community of smart, dedicated individuals working towards breakthroughs that transform lives. For further information about Novartis and our culture, visit: https://www.novartis.com/about/strategy/people-and-culture If you are interested in exploring other career opportunities at Novartis, join our talent community here: https://talentnetwork.novartis.com/network To learn more about the benefits and rewards of working at Novartis, read our handbook here: https://www.novartis.com/careers/benefits-rewards,

ZS is a place where passion changes lives. As a management consulting and technology firm focused on improving life and how we live it, we transform ideas into impact by bringing together data, science, technology and human ingenuity to deliver better outcomes for all. Here you'll work side-by-side with a powerful collective of thinkers and experts shaping life-changing solutions for patients, caregivers and consumers, worldwide. ZSers drive impact by bringing a client-first mentality to each and every engagement. We partner collaboratively with our clients to develop custom solutions and technology products that create value and deliver company results across critical areas of their business. Bring your curiosity for learning, bold ideas, courage and passion to drive life-changing impact to ZS. Data Science Consultants design, develop and execute high-impact analytics solutions for large, complex, structured, and unstructured data sets (including big data) to help clients make better fact-based decisions. What You'll Do .Execute and lead application of numerical optimization techniques on large, unstructured data sets to solve problems .Collaborate with engineering teams to deploy optimization based solutions on datasets of large dimensionality to create practical solutions that achieve desired results in a computationally efficient and statistically effective manner .Play a key role in development of data science capabilities for solving problems and offerings that create scale and advance our analytic capabilities .Lead conversations with clients and other ZS stakeholders to effectively integrate and communicate analysis findings .Evaluate emerging datasets and technologies and help define our analytic platform .Own development of select assets/accelerators that create scale .Contribute to thought leadership through research and publications .Guide and manage project teams of Associates/Associate Consultants. What You'll Bring .Bachelor's degree in computer science, Information Technology, or a related field (or equivalent work experience). .6 - 9 years of relevant experience .Strong theoretical and applied understanding of linear programming, convex optimization, non- linear programming, and other optimization topics .Experience with other data science concepts and algorithms (e.g. supervised / unsupervised learning, reinforcement learning, simulation modeling, recommender systems, etc.) .Relevant programming background (e.g. Python/ R) .Understanding of relevant tools/platforms (e.g. ML / data engineering tools and platforms) .Team management and skill development experience .Agile project planning and project management experience preferred .Excellent oral and written communication skills .Strong attention to detail, with a research-focused mindset .Excellent critical thinking and problem-solving skills .High motivation, good work ethic and maturity. Perks & Benefits: ZS offers a comprehensive total rewards package including health and well-being, financial planning, annual leave, personal growth and professional development. Our robust skills development programs, multiple career progression options and internal mobility paths and collaborative culture empowers you to thrive as an individual and global team member. We are committed to giving our employees a flexible and connected way of working. A flexible and connected ZS allows us to combine work from home and on-site presence at clients/ZS offices for the majority of our week. The magic of ZS culture and innovation thrives in both planned and spontaneous face-to-face connections. Travel: Travel is a requirement at ZS for client facing ZSers business needs of your project and client are the priority. While some projects may be local, all client-facing ZSers should be prepared to travel as needed. Travel provides opportunities to strengthen client relationships, gain diverse experiences, and enhance professional growth by working in different environments and cultures. Considering applying At ZS, we honor the visible and invisible elements of our identities, personal experiences, and belief systems-the ones that comprise us as individuals, shape who we are, and make us unique. We believe your personal interests, identities, and desire to learn are integral to your success here. We are committed to building a team that reflects a broad variety of backgrounds, perspectives, and experiences. about our inclusion and belonging efforts and the networks ZS supports to assist our ZSers in cultivating community spaces and obtaining the resources they need to thrive. If you're eager to grow, contribute, and bring your unique self to our work, we encourage you to apply. ZS is an equal opportunity employer and is committed to providing equal employment and advancement opportunities without regard to any class protected by applicable law. To complete your application: Candidates must possess or be able to obtain work authorization for their intended country of employment.An on-line application, including a full set of transcripts (official or unofficial), is required to be considered. NO AGENCY CALLS, PLEASE. Find Out More At:

Line of Service Advisory Industry/Sector Not Applicable Specialism Data, Analytics & AI Management Level Senior Manager Job Description & Summary At PwC, our people in data and analytics engineering focus on leveraging advanced technologies and techniques to design and develop robust data solutions for clients. They play a crucial role in transforming raw data into actionable insights, enabling informed decision-making and driving business growth. In data engineering at PwC, you will focus on designing and building data infrastructure and systems to enable efficient data processing and analysis. You will be responsible for developing and implementing data pipelines, data integration, and data transformation solutions. * Why PWC At PwC , you will be part of a vibrant community of solvers that leads with trust and creates distinctive outcomes forour clients and communities. This purpose-led and values-driven work, powered by technology in an environment that drives innovation, will enable you to make a tangible impact in the real world. We reward your contributions, support your wellbeing, and offer inclusive benefits, flexibility programmes and mentorship that will help you thrive in work and life. Together, we grow, learn, care, collaborate, and create a future of infinite experiences foreach other. Learn more about us . At PwC , we believe in providing equal employment opportunities, without any discrimination on the grounds of gender, ethnic background, age, disability, marital status, sexual orientation, pregnancy, gender identity or expression, religion or other beliefs, perceived differences and status protected by law. We strive to create an environment where each one of our people can bring their true selves and contribute to their personal growth and the firms growth. To enable this, we have zero tolerance for any discrimination and harassment based on the above considerations. " Job Description & Summary: We are seeking an experienced **AI Engineer** with a minimum of 4 years of experience in developing machine learning models and at least 3 years of experience deploying AI solutions into production. The ideal candidate will be proficient in Python, TensorFlow or PyTorch, and experienced with MLOps tools and cloud platforms. As an AI Engineer in the retail home improvement space, you&aposll help build intelligent systems that enhance the customer experience, optimize inventory, and drive smarter business decisions. Responsibilities: - Design, develop, and deploy AI and machine learning solutions tailored to retail challengessuch as personalized product recommendations, dynamic pricing, and demand forecasting. - Collaborate with data scientists, product managers, engineers, and retail analysts to develop AI-driven features that improve customer experience and operational efficiency. - Build and manage data pipelines that support large-scale training and inference workloads using structured and semi-structured retail data. - Develop and optimize deep learning models using TensorFlow or PyTorch for applications like visual product search, customer segmentation, and chatbot automation. - Integrate AI models into customer-facing platforms (e.g., mobile apps, websites) and backend retail systems (e.g., inventory management, logistics). - Monitor model performance post-deployment and implement continuous improvement strategies based on business KPIs and real-time data. - Contribute to model governance, testing, and documentation to ensure models are fair, explainable, and secure. - Stay informed about AI trends in the retail and e-commerce industry to help the team stay competitive and innovative. Mandatory skill sets: Must have knowledge, skills and experiences AI Engineer - Tensorflow, Python, Pytorch, Scikit learn, NLP, Deep learning, Supervised learning, MLOPs, CICD, API development with FastAPI, ML System Integrations, Understanding of Jenkins, GitHub Actions and Airflow. Docker and Kubernetes, Model design, development, deployment and maintenance Preferred skill sets: Good to have knowledge, skills and experiences Experience with Front end applications such as Streamlit Years of experience required: Experience and Qualifications Experience - 4 Years to 12 years NP - Immediate to 30 days 3 days / week work from client office Education qualification: o BE, B.Tech, ME, M,Tech, MBA, MCA (60% above) Education (if blank, degree and/or field of study not specified) Degrees/Field of Study required: Bachelor of Technology, Master of Business Administration, Bachelor of Engineering, Master of Engineering Degrees/Field of Study preferred: Certifications (if blank, certifications not specified) Required Skills AI Programming Optional Skills Accepting Feedback, Accepting Feedback, Active Listening, Agile Scalability, Amazon Web Services (AWS), Analytical Thinking, Apache Airflow, Apache Hadoop, Azure Data Factory, Coaching and Feedback, Communication, Creativity, Data Anonymization, Data Architecture, Database Administration, Database Management System (DBMS), Database Optimization, Database Security Best Practices, Databricks Unified Data Analytics Platform, Data Engineering, Data Engineering Platforms, Data Infrastructure, Data Integration, Data Lake, Data Modeling + 35 more Desired Languages (If blank, desired languages not specified) Travel Requirements Not Specified Available for Work Visa Sponsorship No Government Clearance Required No Job Posting End Date Show more Show less

About Northern Trust: Northern Trust is a globally recognized, award-winning financial institution that has been in continuous operation since 1889. With over 22,000 partners and more than 130 years of financial experience, Northern Trust takes pride in providing innovative financial services and guidance to the world's most successful individuals, families, and institutions while upholding enduring principles of service, expertise, and integrity. The Model Risk Management Group (MRMG) is a centralized function within the Bank that has experienced rapid growth in response to increasing global regulatory focus on model risk. We are currently seeking a Consultant, Risk Analytics to join our team. In this role, your primary responsibility will be to support the model validation function, acting as a lead contributor in identifying and diagnosing model-related risks across various aspects including input data, assumption, methodology, and outcomes analysis. Key Responsibilities: - Validate models primarily developed in Python or SAS, with a focus on challenging the conceptual soundness of machine learning models and ensuring the quality of input data. - Demonstrate advanced proficiency in financial models related to portfolio analysis, asset management, Value at Risk, Monte Carlo simulations, CAPM, and factors. - Exhibit a solid understanding of risks associated with AI/ML models, such as Fairness, Privacy, Transparency, and Explainability. - Engage in stress testing, CCAR, CECL, and other relevant areas. - Solve complex quantitative problems, analyze possible solutions, and develop a deep understanding of various algorithms and machine learning techniques. - Review and assess bank-wide quantitative models including those used for CECL, CCAR/DFAST stress testing, credit risk projections, operational risk, AML, and other machine learning models. - Ensure model development, monitoring, and validation approaches align with regulatory expectations and internal risk management needs. - Evaluate model specifications, assumptions, testing completeness, and performance metrics, while documenting observations and recommending remediation actions. - Maintain strong relationships with key stakeholders like model developers, owners, and users. Qualifications: - 6 to 8 years of modeling or quantitative analysis experience in a relevant discipline. - A degree in STEM field, mathematics, actuarial science, engineering, or statistics (Advanced degree preferred). - Strong interpersonal, verbal, and written communication skills. - Proficiency in Python, with experience in SAS and R desired. - Mastery of analytical tools like Excel, Word, and PowerPoint. - Deep understanding of linear and logistic regression, along with experience in Machine Learning models. - Familiarity with cloud and big data technologies is a plus. Joining Northern Trust offers a chance to be part of a flexible and collaborative work culture where innovation is encouraged, and career growth is supported. As a company committed to serving communities, Northern Trust values inclusivity and flexibility in the workplace. Apply today to explore opportunities with one of the world's most esteemed and sustainable companies. #MadeForGreater Northern Trust is dedicated to providing reasonable accommodations to individuals with disabilities. If you require accommodation during the employment process, please contact MyHRHelp@ntrs.com. We look forward to learning more about your interests and experiences and discussing how you can contribute to our team. Share your flexible working requirements with us, and together, we can achieve greater success.,

As a member of Kainskep Solutions, you will be part of a human, friendly, engaging, supportive, agile, and super collaborative culture that values teamwork, ownership, innovation, challenge, and collaboration. We believe in the strength of a diverse team and are committed to creating a diverse and inclusive environment. In this role, you will utilize programming languages such as Python, R, and SQL for data manipulation, statistical analysis, and machine learning tasks. You will apply fundamental statistical concepts and develop supervised and unsupervised machine learning models. Evaluating model performance, conducting data manipulation and visualization, and performing exploratory data analysis will be key aspects of your responsibilities. To excel in this position, you should possess a Bachelor's degree or higher in Computer Science, Statistics, Mathematics, or a related field. Proficiency in programming languages like Python, R, and SQL, as well as strong analytical skills, are essential. The ability to learn quickly, adapt to new technologies and methodologies, and prior experience in data analysis or machine learning are advantageous. Additionally, experience in Computer Vision, Generative AI techniques, and Microsoft AI technologies would be beneficial. The job type is full-time, offering benefits such as a flexible schedule and paid sick time. The work schedule is Monday to Friday, with an in-person work location. The expected start date for this role is 24/03/2025.,