75 Seaborn Jobs - Page 3

Job Title - Retail Specialized Data Scientist Level 9 SnC GN Data & AI Management Level:09 - Consultant Location:Bangalore / Gurgaon / Mumbai / Chennai / Pune / Hyderabad / Kolkata Must have skills: A solid understanding of retail industry dynamics, including key performance indicators (KPIs) such as sales trends, customer segmentation, inventory turnover, and promotions. Strong ability to communicate complex data insights to non-technical stakeholders, including senior management, marketing, and operational teams. Meticulous in ensuring data quality, accuracy, and consistency when handling large, complex datasets. Gather and clean data from various retail sources, such as sales transactions, customer interactions, inventory management, website traffic, and marketing campaigns. Strong proficiency in Python for data manipulation, statistical analysis, and machine learning (libraries like Pandas, NumPy, Scikit-learn). Expertise in supervised and unsupervised learning algorithms Use advanced analytics to optimize pricing strategies based on market demand, competitor pricing, and customer price sensitivity. Good to have skills: Familiarity with big data processing platforms like Apache Spark, Hadoop, or cloud-based platforms such as AWS or Google Cloud for large-scale data processing. Experience with ETL (Extract, Transform, Load) processes and tools like Apache Airflow to automate data workflows. Familiarity with designing scalable and efficient data pipelines and architecture. Experience with tools like Tableau, Power BI, Matplotlib, and Seaborn to create meaningful visualizations that present data insights clearly. Job Summary :The Retail Specialized Data Scientist will play a pivotal role in utilizing advanced analytics, machine learning, and statistical modeling techniques to help our 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. Roles & Responsibilities: Leverage Retail Knowledge:Utilize your deep understanding of the retail industry (merchandising, customer behavior, product lifecycle) to design AI solutions that address critical retail business needs. Gather and clean data from various retail sources, such as sales transactions, customer interactions, inventory management, website traffic, and marketing campaigns. Apply machine learning algorithms, such as classification, clustering, regression, and deep learning, to enhance predictive models. Use AI-driven techniques for personalization, demand forecasting, and fraud detection. Use advanced statistical methods help optimize existing use cases and build new products to serve new challenges and use cases. 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. Professional & Technical 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 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

Job Title - Retail Specialized Data Scientist Level 9 SnC GN Data & AI Management Level:09 - Consultant Location:Bangalore / Gurgaon / Mumbai / Chennai / Pune / Hyderabad / Kolkata Must have skills: A solid understanding of retail industry dynamics, including key performance indicators (KPIs) such as sales trends, customer segmentation, inventory turnover, and promotions. Strong ability to communicate complex data insights to non-technical stakeholders, including senior management, marketing, and operational teams. Meticulous in ensuring data quality, accuracy, and consistency when handling large, complex datasets. Gather and clean data from various retail sources, such as sales transactions, customer interactions, inventory management, website traffic, and marketing campaigns. Strong proficiency in Python for data manipulation, statistical analysis, and machine learning (libraries like Pandas, NumPy, Scikit-learn). Expertise in supervised and unsupervised learning algorithms Use advanced analytics to optimize pricing strategies based on market demand, competitor pricing, and customer price sensitivity. Good to have skills: Familiarity with big data processing platforms like Apache Spark, Hadoop, or cloud-based platforms such as AWS or Google Cloud for large-scale data processing. Experience with ETL (Extract, Transform, Load) processes and tools like Apache Airflow to automate data workflows. Familiarity with designing scalable and efficient data pipelines and architecture. Experience with tools like Tableau, Power BI, Matplotlib, and Seaborn to create meaningful visualizations that present data insights clearly. Job Summary :The Retail Specialized Data Scientist will play a pivotal role in utilizing advanced analytics, machine learning, and statistical modeling techniques to help our 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. Roles & Responsibilities: Leverage Retail Knowledge:Utilize your deep understanding of the retail industry (merchandising, customer behavior, product lifecycle) to design AI solutions that address critical retail business needs. Gather and clean data from various retail sources, such as sales transactions, customer interactions, inventory management, website traffic, and marketing campaigns. Apply machine learning algorithms, such as classification, clustering, regression, and deep learning, to enhance predictive models. Use AI-driven techniques for personalization, demand forecasting, and fraud detection. Use advanced statistical methods help optimize existing use cases and build new products to serve new challenges and use cases. 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. Professional & Technical 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 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)

Develop models for underwriting, claims management, fraud detection, risk assessment. Use advanced ML techniques to analyze & enhance retention strategies. Process & analyze large datasets from various insurance systems to identify patterns. Required Candidate profile Proficient in Python & SQL for data analysis & modeling. Familiar with data science libraries like Pandas, NumPy, Scikit-learn, TensorFlow, or PyTorch. Experience with data visualization tools.

Required Skill Programming Languages: Proficiency in Python, R, or Java. Experience with libraries and frameworks such as TensorFlow, PyTorch, Keras, Scikit-learn, etc. Machine Learning: Strong understanding of machine learning algorithms, including supervised and unsupervised learning, reinforcement learning, and deep learning. Data Science: Experience with data analysis, data visualization, and statistical modeling. Proficiency in using tools like Pandas, NumPy, Matplotlib, and Seaborn. Big Data Technologies: Familiarity with big data processing frameworks like Hadoop, Spark, or Apache Flink. Cloud Platforms: Experience with cloud services such as AWS, Google Cloud, or Azure for deploying AI solutions. Natural Language Processing (NLP): Knowledge of NLP techniques and tools such as NLTK, SpaCy, or GPT-3. Computer Vision: Experience with computer vision techniques and libraries such as OpenCV, YOLO, or Fast R-CNN. Problem-Solving: Strong analytical and problem-solving skills with the ability to think critically and creatively. Communication: Excellent verbal and written communication skills, with the ability to explain complex technical concepts to non-technical stakeholders. Team Collaboration: Ability to work effectively in a collaborative team environment and contribute to team success.

Job Type: Full time Job description: Experience of at least 3 years in developing models using Python/PySpark libraries. Experience with Databricks or Dataiku DSS (Data Science Studio) would be an added advantage. Strong experience with Scala/Python/Java and Spark is required. Strong proficiency in developing, training, and evaluating state-of-the-art machine learning models and deploying them is required. Proficiency in statistical and probabilistic methods such as SVM, Decision-Trees, Bagging and Boosting Techniques, and Clustering is needed. Proficiency in core NLP techniques such as Text Classification, Named Entity Recognition (NER), Topic Modeling, and Sentiment Analysis is required. Understanding Generative AI, Large Language Models, and Transformers would be an added advantage. Have hands-on experience in Python data-science and math packages such as NumPy, Pandas, Sklearn, Seaborn, PyCaret, and Matplotlib. Proficiency in Python and common Machine Learning frameworks such as TensorFlow, NLTK, Stanford NLP, PyTorch, Ling Pipe, Caffe, Keras, SparkML, and OpenAI is required. Experience of working in large teams and using collaboration tools like GIT, Jira, and Confluence is a must. Good understanding of any of the cloud platforms such as AWS, Azure, or GCP is required. Understanding of Commercial Pharma landscape and Patient Data/Analytics would be a huge plus. Should have an attitude of willingness to learn, accepting the challenging environment, and confidence in delivering the results within timelines.

Dear Candidate, We are looking for a skilled Python Software Developer to design, develop, and optimize high-performance applications. You will work on building scalable back-end services, APIs, and data-driven applications while ensuring code quality and efficiency. If you are passionate about Python development, cloud technologies, and automation , wed love to hear from you! Key Responsibilities: Develop, test, and maintain backend applications and RESTful APIs using Python. Work with Django, Flask, or FastAPI frameworks to build scalable web applications. Optimize performance, security, and scalability of applications. Integrate third-party services, APIs, and data pipelines. Work with SQL and NoSQL databases (PostgreSQL, MySQL, MongoDB, Redis). Implement authentication and authorization mechanisms (JWT, OAuth, LDAP). Write clean, maintainable, and well-documented code following best practices. Conduct unit testing and test-driven development (TDD) using PyTest or Unittest. Implement CI/CD pipelines and automation for efficient deployments. Collaborate with DevOps teams to deploy applications on AWS, Azure, or GCP . Stay updated with Python libraries, frameworks, and industry trends . Required Skills & Qualifications: Strong proficiency in Python and object-oriented programming (OOP) . Experience with Django, Flask, or FastAPI for web application development. Familiarity with SQL and NoSQL databases (PostgreSQL, MySQL, MongoDB, Redis). Knowledge of RESTful APIs, GraphQL, and WebSockets . Experience with Docker and Kubernetes for containerized deployments. Hands-on experience with cloud platforms (AWS, GCP, or Azure). Strong understanding of data structures, algorithms, and system design . Experience with Celery, RabbitMQ, or Kafka for background task processing. Proficiency in Git and version control workflows (GitHub, GitLab, Bitbucket). Familiarity with CI/CD pipelines and automation (Jenkins, GitHub Actions, Azure DevOps). Strong problem-solving, debugging, and analytical skills. Soft Skills: Strong problem-solving and analytical skills. Excellent communication skills to work with cross-functional teams. Ability to work independently and as part of a team. Detail-oriented with a focus on delivering high-quality solutions Note: If you are interested, please share your updated resume and suggest the best number & time to connect with you. If your resume is shortlisted, one of the HR from my team will contact you as soon as possible. Srinivasa Reddy Kandi Delivery Manager Integra Technologies

The Basics. Team:Founders Office. Introduction . CashFlo is a one-of-a-kind AP automation and supply chain financing platform. Made in India. Made for India. Our mission? To unleash the untapped financial potential of millions of Indian businesses. Our AP and Payments automation suite is transforming the way large businesses across the country handle their payments. Founded by illustrious alumni from BCG, ISB, and IIM, CashFlo is fortified by the trust and backing of prominent investors such as Elevation Capital and General Catalyst. Recognized by Nasscom as the Best Supply Chain Finance solution from 2019 to 2021, CashFlo's platform creates a harmonious ecosystem for buyers, suppliers, and financiers. Our integrated AP & financing platform has become a key driver of growth for over 100 large enterprises and 200,000 mid-market and SME companies across more than ten sectors. We proudly serve a clientele that includes renowned brands like Mosaic Wellness, The Souled Store, Durian, Cona Electricals, as well as industry giants like ITC, IFB, Crompton, Zydus Healthcare, Lupin, Murugappa Group, among others. We combine in-depth financial and technological insights to deliver exceptional results. We take immense pride in our work and firmly believe in the exponential effect of a job well done, every day. We are on the lookout for individuals who share this ethos and are prepared to help us take CashFlo to unparalleled heights. Youll Excel If You Possess. Data Analysis Tools:Proficiency in data analysis tools such as Python (with libraries like Pandas, NumPy, Matplotlib, and Seaborn) and R. Data visualization:Experience with data visualization tools such as Tableau, Power BI, or Matplotlib for creating meaningful visualizations. Statistical Analysis:A good understanding of statistical concepts and techniques for hypothesis testing, regression analysis, and other statistical modelling. SQL Database Management:Strong SQL skills for data extraction, manipulation, and querying from relational databases like MySQL, PostgreSQL, or Microsoft SQL Server. Problem-Solving Skills: Strong problem-solving skills to identify business problems, formulate hypotheses, and use data to derive solutions. Communication Skills: Effective communication skills to convey complex data-driven insights to non-technical stakeholders. Joining CashFlo Why Its a Great Choice. Uniquely Positioned for Success:CashFlo sits at the unique intersection of Payments, Lending, and SaaS three of the fastest-growing and most lucrative spaces globally and in India. As a part of our team, you will be a key player in an industry-defining company. An Opportunity to Create Wealth:At CashFlo, we understand that our success is deeply linked with the success of our employees. That's why we offer the potential to create exponential wealth through equity in our rapidly growing early-stage company. You will not only contribute to our growth story, but also share in the rewards. A Collaborative and Driven Team:We pride ourselves on fostering a culture that encourages kindness, collaboration, and a shared commitment to quality. Our team members are always there to help each other, and we believe in lifting each other up. Your growth is our growth, and we succeed as a team. Direct Impact on Company Success:At CashFlo, every role is crucial. Your work will have a real, tangible impact on our success. You'll see the results of your hard work in real-time. Fast-Track Your Career:We invest in our employees' professional growth through comprehensive training programs, mentoring opportunities, and clear growth paths. Whether you aspire to grow as an individual contributor or on a management track, we provide the resources and support you need to accelerate your career. Competitive Compensation and Benefits:We offer competitive salaries, comprehensive benefits, and recognition programs. We value the work you do, and our compensation package reflects our commitment to attracting and retaining the best talent. Unwavering Commitment to Excellence:We are seeking individuals ready to dive into challenging work, individuals who are excited about going above and beyond to drive their own growth and the company's. If you are motivated by ambitious goals and are ready to make a significant impact, CashFlo is the place for you. Submit Your Application. You have successfully applied. You have errors in applying. Apply With Resume *. First Name*. Middle Name. Last Name*. Email*. Mobile. Phone. Total Work Experience*. Current Location. Current Company*. Current Designation*. Fixed CTC*. Expected CTC. How Did You Hear About Us. Social Network and Web Links. Provide us with links to see some of your work (Git/ Dribble/ Behance/ Pinterest/ Blog/ Medium). Employer. Education. Show more Show less

Job Description Orangemantra, a leading IT services company, is seeking a Junior Associate Python to join our dynamic team As a Junior AI/ML Engineer, you will work alongside our experienced engineers to help develop innovative AI and machine learning solutions that drive business transformation for our clients You will have the opportunity to work on exciting projects across a variety of industries, building and deploying cutting-edge models while learning and growing in the field of AI and ML Key Responsibilities Assist in developing machine learning models and AI algorithms to solve real-world business problems Conduct data preprocessing, feature engineering, and data cleaning to ensure high-quality input for model building Collaborate with senior engineers to design, train, and test machine learning models, ensuring their scalability and effectiveness Support in the implementation and deployment of AI/ML solutions into production environments Participate in the development of data pipelines, ensuring data quality and accessibility for AI/ML tasks Help in optimizing machine learning models for better performance, scalability, and efficiency Stay up to date with the latest trends and advancements in AI/ML technologies Contribute to internal documentation, and assist with testing and debugging models Skills & Qualifications: Bachelor's degree in Computer Science, Data Science, Engineering, or a related field Strong understanding of machine learning algorithms and frameworks (e g , linear regression, decision trees, clustering, deep learning) Proficiency in programming languages such as Python, R, or Java, with a focus on ML libraries like TensorFlow, Keras, PyTorch, or Scikit-learn Experience with data manipulation and analysis tools (e g , Pandas, NumPy) Familiarity with data visualization tools (e g , Matplotlib, Seaborn, or Power BI) Knowledge of cloud platforms and tools for deploying machine learning models (e g , AWS, Azure, or Google Cloud) is a plus Strong problem-solving and analytical skills Excellent communication and teamwork abilities, with a passion for learning and improving APPLY NOW

Job Description Orangemantra, a leading IT services company, is seeking a Junior Associate AI to join our dynamic team As a Junior Associate AI, you will work alongside our experienced engineers to help develop innovative AI and machine learning solutions that drive business transformation for our clients You will have the opportunity to work on exciting projects across a variety of industries, building and deploying cutting-edge models while learning and growing in the field of AI and ML Key Responsibilities Assist in developing machine learning models and AI algorithms to solve real-world business problems Conduct data preprocessing, feature engineering, and data cleaning to ensure high-quality input for model building Collaborate with senior engineers to design, train, and test machine learning models, ensuring their scalability and effectiveness Support in the implementation and deployment of AI/ML solutions into production environments Participate in the development of data pipelines, ensuring data quality and accessibility for AI/ML tasks Help in optimizing machine learning models for better performance, scalability, and efficiency Stay up to date with the latest trends and advancements in AI/ML technologies Contribute to internal documentation, and assist with testing and debugging models Skills & Qualifications: Bachelor's degree in Computer Science, Data Science, Engineering, or a related field Strong understanding of machine learning algorithms and frameworks (e g , linear regression, decision trees, clustering, deep learning) Proficiency in programming languages such as Python, R, or Java, with a focus on ML libraries like TensorFlow, Keras, PyTorch, or Scikit-learn Experience with data manipulation and analysis tools (e g , Pandas, NumPy) Familiarity with data visualization tools (e g , Matplotlib, Seaborn, or Power BI) Knowledge of cloud platforms and tools for deploying machine learning models (e g , AWS, Azure, or Google Cloud) is a plus Strong problem-solving and analytical skills Excellent communication and teamwork abilities, with a passion for learning and improving APPLY NOW

About The Role : Must have knowledge in Azure Datalake, Azure function, Azure Databricks, Azure data factory, PostgreSQL Working knowledge in Azure devops, Git flow would be an added advantage. (OR) SET 2: Must have working knowledge in AWS Kinesis, AWS EMR, AWS Glue, AWS RDS, AWS Athena, AWS RedShift. Should have demonstrable knowledge and expertise in working with timeseries data. Working knowledge in delivering data engineering / data science projects in Industry 4.0 is an added advantage. Should have knowledge on Palantir. Strong problem-solving skills with an emphasis on sustainable and reusable development. Experience using statistical computer languages to manipulate data and draw insights from large data sets :Python/PySpark, Pandas, Numpy seaborn / matplotlib, Knowledge in Streamlit.io is a plus Familiarity with Scala, GoLang, Java would be added advantage. Experience with big data tools:Hadoop, Spark, Kafka, etc. Experience with relational databases such as Microsoft SQL Server, MySQL, PostGreSQL, Oracle and NoSQL databases such as Hadoop, Cassandra, Mongo dB Experience with data pipeline and workflow management tools:Azkaban, Luigi, Airflow, etc Experience building and optimizing big data data pipelines, architectures and data sets. Strong analytic skills related to working with unstructured datasets. Primary Skills Provide innovative solutions to the data engineering problems that are faced in the project and solve them with technically superior code & skills. Where possible, should document the process of choosing technology or usage of integration patterns and help in creating a knowledge management artefact that can be used for other similar areas. Create & apply best practices in delivering the project with clean code. Should work innovatively and have a sense of proactiveness in fulfilling the project needs. Additional Information: Reporting to :Director- Intelligent Insights and Data Strategy Travel :Must be willing to be deployed at client locations anywhere in the world for long and short term as well as should be flexible to travel on shorter duration within India and abroad

Strong programming skills in Python or R, with good knowledge in data manipulation, analysis, and visualization libraries (e.g., pandas, numpy, matplotlib, seaborn) Knowledge of machine learning techniques and algorithms. . Required Candidate profile Hands-on knowledge on machine learning frameworks (e.g., scikit-learn, TensorFlow, PyTorch) Proficiency in SQL for data extraction, integration, and manipulation to analyze large datasets.

Project Role : AI / ML Engineer Project Role Description : Develops applications and systems that utilize AI tools, Cloud AI services, with proper cloud or on-prem application pipeline with production ready quality. Be able to apply GenAI models as part of the solution. Could also include but not limited to deep learning, neural networks, chatbots, image processing. Must have skills : Machine Learning Good to have skills : NA Minimum 5 year(s) of experience is required Educational Qualification : 15 years full time education Summary :These roles have many overlapping skills with GENAI Engineers and architects. Description may scaleup/scale down based on expected seniority. Roles & Responsibilities:-Implement generative AI models, identify insights that can be used to drive business decisions. Work closely with multi-functional teams to understand business problems, develop hypotheses, and test those hypotheses with data, collaborating with cross-functional teams to define AI project requirements and objectives, ensuring alignment with overall business goals.-Conducting research to stay up-to-date with the latest advancements in generative AI, machine learning, and deep learning techniques and identify opportunities to integrate them into our products and services.-Optimizing existing generative AI models for improved performance, scalability, and efficiency.-Ensure data quality and accuracy-Leading the design and development of prompt engineering strategies and techniques to optimize the performance and output of our GenAI models.-Implementing cutting-edge NLP techniques and prompt engineering methodologies to enhance the capabilities and efficiency of our GenAI models.-Determining the most effective prompt generation processes and approaches to drive innovation and excellence in the field of AI technology, collaborating with AI researchers and developers-Experience working with cloud based platforms (example:AWS, Azure or related)-Strong problem-solving and analytical skills-Proficiency in handling various data formats and sources through Omni Channel for Speech and voice applications, part of conversational AI-Prior statistical modelling experience-Demonstrable experience with deep learning algorithms and neural networks-Developing clear and concise documentation, including technical specifications, user guides, and presentations, to communicate complex AI concepts to both technical and non-technical stakeholders.-Contributing to the establishment of best practices and standards for generative AI development within the organization. Professional & Technical Skills:-Must have solid experience developing and implementing generative AI models, with a strong understanding of deep learning techniques such as GPT, VAE, and GANs.-Must be proficient in Python and have experience with machine learning libraries and frameworks such as TensorFlow, PyTorch, or Keras.-Must have strong knowledge of data structures, algorithms, and software engineering principles.-Must be familiar with cloud-based platforms and services, such as AWS, GCP, or Azure.-Need to have experience with natural language processing (NLP) techniques and tools, such as SpaCy, NLTK, or Hugging Face.-Must be familiar with data visualization tools and libraries, such as Matplotlib, Seaborn, or Plotly.-Need to have knowledge of software development methodologies, such as Agile or Scrum.-Possess excellent problem-solving skills, with the ability to think critically and creatively to develop innovative AI solutions. Additional Information:-Must have a degree in Computer Science, Artificial Intelligence, Machine Learning, or a related field. A Ph.D. is highly desirable.-strong communication skills, with the ability to effectively convey complex technical concepts to a diverse audience.-You possess a proactive mindset, with the ability to work independently and collaboratively in a fast-paced, dynamic environment. Additional Information: The candidate should have a minimum of 5 years of real time experience in Machine Learning. A 15 years full time education is required. Qualifications 15 years full time education

Skill required: IX Intelligent Asset Management Operations - Asset Data Management Designation: Asset Performance Mgmt Senior Analyst Qualifications: Any Graduation Years of Experience: 5 to 8 years What would you do? Role:Process Simulation EngineerThe Process Simulation Engineer is part of the Process Engineering and Automation Chapter within Client's and supports Client's Facilities and Operations of the Future program. This role is responsible for work supporting key research and development of digital engineering computer-based modeling and simulation tools to enhance the company s facilities engineering models. This role involves working with various types of equipment models, including facilities process models, pipeline models, and other specialty models. The engineer will utilize steady state process models, dynamic process models, data-driven models, and special modeling technologies to evaluate improvements to process simulation workflows. What are we looking for? B.S. Process/Chemical EngineeringSignificant field (10+ years) experience working process engineering and/or process control roles in the Downstream and/or Upstream sectors of Operator or EPC companies in the Oil and Gas value chain.5+ yrs of experience in software engineering, data engineering and cloud computing platforms (Azure).PhD (preferred), M.S, in a STEM-related field such as Chemical Engineering or Computer Science.Proficient with Agile and Waterfall project management methodologies and tools. Proven experience using Azure DevOps for managing user stories, dashboards, queries, code repos and code version control.Prior experience with programming languages such as Python and C# , and data science libraries such as Numpy, Scikit-learn, Pandas, Matplotlib, Seaborn, Keras, TensorFlow.Experience with process simulation and monitoring software such as Hysys (required), Flarenet (required), ProII (required), AspenOnline (preferred). Roles and Responsibilities: Research & Development of new technologies in Digital Process Systems Engineering space. The roles spans technologies related to process simulation & modeling, process control and optimization, technical safety, among others.Identification, scoping, development and timely delivery of Product Features and User Stories under Scaled Agile Framework (SAFE) or Waterfall project management methodologies.Interfacing with a broad set of stakeholders in Client Technology Center and Business Units, and with external parties such as industry partners and vendors.Research, develop and oversee R&D efforts for process simulations for facilities engineering models.Utilize tools such as Aspen HYSYS, Promax, and HTRI for process modeling and simulation.Evaluate engineering documents such as process flow diagrams (PFDs) and guidelines to develop simulations of simple processes.Resolve basic modeling issues and assist with the interpretation and reporting of modeling results.Follow established guidelines for thermodynamic packages and specific technology modeling strategies. Qualifications Any Graduation

Project Role : AI / ML Engineer Project Role Description : Develops applications and systems that utilize AI tools, Cloud AI services, with proper cloud or on-prem application pipeline with production ready quality. Be able to apply GenAI models as part of the solution. Could also include but not limited to deep learning, neural networks, chatbots, image processing. Must have skills : Machine Learning Good to have skills : NA Minimum 12 year(s) of experience is required Educational Qualification : 15 years full time education Summary :These roles have many overlapping skills with GENAI Engineers and architects. Description may scaleup/scale down based on expected seniority. Roles & Responsibilities:-Implement generative AI models, identify insights that can be used to drive business decisions. Work closely with multi-functional teams to understand business problems, develop hypotheses, and test those hypotheses with data, collaborating with cross-functional teams to define AI project requirements and objectives, ensuring alignment with overall business goals.-Conducting research to stay up-to-date with the latest advancements in generative AI, machine learning, and deep learning techniques and identify opportunities to integrate them into our products and services.-Optimizing existing generative AI models for improved performance, scalability, and efficiency.-Ensure data quality and accuracy-Leading the design and development of prompt engineering strategies and techniques to optimize the performance and output of our GenAI models.-Implementing cutting-edge NLP techniques and prompt engineering methodologies to enhance the capabilities and efficiency of our GenAI models.-Determining the most effective prompt generation processes and approaches to drive innovation and excellence in the field of AI technology, collaborating with AI researchers and developers-Experience working with cloud based platforms (example:AWS, Azure or related)-Strong problem-solving and analytical skills-Proficiency in handling various data formats and sources through Omni Channel for Speech and voice applications, part of conversational AI-Prior statistical modelling experience-Demonstrable experience with deep learning algorithms and neural networks-Developing clear and concise documentation, including technical specifications, user guides, and presentations, to communicate complex AI concepts to both technical and non-technical stakeholders.-Contributing to the establishment of best practices and standards for generative AI development within the organization. Professional & Technical Skills:-Must have solid experience developing and implementing generative AI models, with a strong understanding of deep learning techniques such as GPT, VAE, and GANs.-Must be proficient in Python and have experience with machine learning libraries and frameworks such as TensorFlow, PyTorch, or Keras.-Must have strong knowledge of data structures, algorithms, and software engineering principles.-Must be familiar with cloud-based platforms and services, such as AWS, GCP, or Azure.-Need to have experience with natural language processing (NLP) techniques and tools, such as SpaCy, NLTK, or Hugging Face.-Must be familiar with data visualization tools and libraries, such as Matplotlib, Seaborn, or Plotly.-Need to have knowledge of software development methodologies, such as Agile or Scrum.-Possess excellent problem-solving skills, with the ability to think critically and creatively to develop innovative AI solutions. Additional Information:-Must have a degree in Computer Science, Artificial Intelligence, Machine Learning, or a related field. A Ph.D. is highly desirable.-strong communication skills, with the ability to effectively convey complex technical concepts to a diverse audience.-You possess a proactive mindset, with the ability to work independently and collaboratively in a fast-paced, dynamic environment. Additional Information: The candidate should have a minimum of 5 years of real time experience in Machine Learning. A 15 years full time education is required. Qualifications 15 years full time education

We are seeking an experienced Mid-Level Data Scientist for the development of data-driven solutions aimed at identifying and capitalizing on critical business opportunities. You will design and implement predictive models, integrate internal and external data sources, and recommend machine learning strategies that enhance decision-making. This role requires hands-on expertise in model development, strategic collaboration with cross-functional teams, and mentoring junior data scientists. You will contribute to shaping the departments strategy and manage complex projects with a focus on delivering high-impact results. Key Responsibilities: Develop and implement advanced statistical and machine learning models to address business challenges and improve decision accuracy. Communicate findings and model insights effectively to stakeholders, ensuring alignment with business processes and objectives. Innovate and recommend new modeling techniques, tools, and approaches to enhance project outcomes. Collaborate with business teams to design and execute machine learning solutions that drive business value and improve overall decision-making. Identify opportunities for integrating new data sources, both internal and external, to enhance model performance and business outcomes. Develop and manage complex analytical projects, ensuring timely delivery while maintaining high-quality standards. Mentor junior data scientists, fostering a collaborative and growth-oriented team environment. Guide the strategy for machine learning and predictive modeling within the department, ensuring continuous improvement in data-driven decision-making. Qualifications: Bachelors degree in a quantitative field (e.g., Statistics, Mathematics, Computer Science, Engineering) or equivalent experience. 4-6 years of experience in data science, analytics, or quantitative modeling. Expertise in predictive modeling, machine learning, and statistical techniques such as clustering, classification, and regression. Proficiency in Python and SQL, with a strong understanding of data manipulation and analysis tools. Familiarity with a range of machine learning libraries and frameworks such as NumPy , Pandas , Scikit-learn , XGBoost , LightGBM , TensorFlow , Keras , and others listed below. Experience with big data tools and techniques (e.g., PySpark , Dask , Vaex , Apache Airflow ) is a plus. Strong project management skills and ability to break down complex tasks into manageable steps, ensuring timely project delivery. Proven ability to work collaboratively and influence business partners at all levels. Key Tools and Libraries: NumPy, Pandas, SciPy : Scientific computing, data analysis, and modeling. scikit-learn, XGBoost, LightGBM, CatBoost : Predictive modeling, classification, regression, and large datasets. TensorFlow, Keras, PyTorch : Deep learning, neural networks, distributed training. Plotly, Matplotlib, Seaborn, Altair : Data visualization, interactive dashboards, statistical plots. PySpark, Dask, Vaex : Big data processing and real-time data handling. Apache Airflow, PyCaret : Machine learning automation, pipeline scheduling. SpaCy, Hugging Face Transformers : Natural language processing and text analysis.

Department : Market Innovation Level - Senior position Expertise in supervised, unsupervised, machine learning, deep learning, reinforcement learning, statistics techniques. Proficiency in Python, PyTorch, TensorFlow. Good to have knowledge of Bayesian inference, probability distribution, hypothesis testing, A/B testing, and time series forecasting. Hands-on experience with feature engineering and hyperparameter tuning. Experience with MLflow, Weights & Biases, DVC (Data Version Control). Ability to track model performance across multiple experiments and datasets. End-to-end ML lifecycle management from Data ingestion, preprocessing, feature engineering, model training, deployment, and monitoring. Expertise in CI/CD for ML, containerization (Docker, Kubernetes), and orchestration (Kubeflow). Good to have experience in automating data labelling and feature stores (Feast). Good to have data processing experience in Spark, Flink, Druid, Nifi. Good to have real-time data streaming in Kafka and other messaging systems Designing and optimizing data pipelines for structured data. Good to have hands-on experience with Pyspark. Strong SQL skills for data extraction, transformation, and query optimization. Atleast one database experience such as NOSQL database. Implementing parallel and distributed ML techniques for large-scale systems. Good to have knowledge of model explainability (SHAP, LIME), bias mitigation, and adversarial robustness. Experience in model drift monitoring. Good to have CUDA for GPU acceleration. Good to have choosing between CPU/GPU for different ML workloads (batch inference on CPU, training on GPU). Good to have scaling deep learning models on multi-GPU. Strong presentation skills, including data storytelling, visualization (Matplotlib, Seaborn, Superset), and report writing. Experience in mentoring data scientists, research associates, and data engineers. Contributions to research papers, patents, or open-source projects.

Job Summary: We are seeking a skilled and data-driven Data Scientist specializing in Sales Analytics to join our dynamic team. In this role, you will leverage your expertise in Python, database technologies, and advanced analytics techniques to derive actionable insights from sales data, optimize processes, and drive data-informed business strategies. A strong understanding of MS SQL and PostgreSQL databases is essential for this role, along with the ability to create actionable plans from data to guide decision-making across the organization. Key Responsibilities: - Data Analysis & Insights: - Analyze large sales datasets to identify trends, patterns, and opportunities for revenue growth. - Perform segmentation, cohort analysis, and predictive modeling to support sales forecasting and target setting. - Database Management & Integration: - Extract, clean, and transform data from MS SQL and PostgreSQL databases to support analytical needs. - Optimize database queries and structures to enhance data accessibility and processing efficiency. - Collaborate with database administrators to ensure seamless integration and performance of analytics tools. - Model Development: - Build and deploy machine learning models to predict customer behavior, sales performance, and market trends. - Develop recommendation systems for cross-selling and upselling opportunities. - Sales Performance Optimization: - Collaborate with sales teams to optimize pricing strategies, sales funnel conversion rates, and customer acquisition efforts. - Design and implement A/B tests to measure the impact of sales strategies and campaigns. - Action Plan Development: - Translate complex data analyses into actionable business recommendations and strategies. - Collaborate with cross-functional teams to implement data-driven action plans and track their success. - Develop workflows and frameworks to integrate data insights into routine decision-making processes. - Dashboarding & Reporting: - Create and maintain dashboards and visualizations to provide stakeholders with real-time insights into sales performance. - Automate routine reporting tasks using Python, MS SQL, and PostgreSQL in combination with business intelligence tools. - Collaboration & Strategy: - Work closely with marketing, product, and finance teams to align data insights with overall business goals. - Present actionable recommendations and strategic insights to senior management and key stakeholders. Qualifications: - Education: - Bachelor's or Masters degree in Data Science, Statistics, Computer Science, Economics, or a related field. - Experience: - Minimum 3 years of experience in data science, preferably with a focus on sales or marketing analytics. - Demonstrated experience working with sales data, CRM systems, or revenue analytics. - Proven experience working with MS SQL and PostgreSQL databases for analytics and reporting. - Technical Skills: - Proficient in Python and its libraries (Pandas, NumPy, Scikit-learn, Matplotlib/Seaborn). - Strong knowledge of MS SQL and PostgreSQL, including query optimization, stored procedures, and data modeling. - Experience with data visualization tools like Tableau, Power BI, or similar. - Familiarity with machine learning frameworks such as TensorFlow, PyTorch (preferred), OpenCV etc. - Analytical Skills: - Strong statistical analysis skills and experience applying them in sales forecasting and performance analysis. - Ability to work with complex datasets and solve ambiguous problems creatively. - Soft Skills: - Proven ability to create actionable business strategies based on data-driven insights. - Excellent communication skills to present insights and recommendations to non-technical stakeholders. - Proactive and solution-oriented mindset with attention to detail. Preferred Qualifications: - Experience in sales or e-commerce industry. - Knowledge of marketing analytics, customer lifetime value (CLV) modeling, Basket Analysis, RFM, Product Pricing or churn prediction. What We Offer: - Competitive salary and performance bonuses. - The option for remote work. - Access to cutting-edge tools and technologies. - Opportunities for professional growth and development.

Role: Python Fullstack Software Engineer Exper: min 15 Years Salary: 24 LPA Candidate must have minimum 6+ years of experience in Python and 5+ years in ReactJS) Location: Chennai, Bangalore Qualifi: Any Regards, Allen 7200495207

Responsibilities Develop and deploy computer vision algorithms and deep learning models for diverse problems. Design and implement computer vision models using state-of-the-art techniques and frameworks. Explore and analyze unstructured data like images through image processing. Analyze, evaluate and optimize existing computer vision systems to improve performance and accuracy. Test and validate computer vision code and models, ensuring robustness and reliability. Research and implement new computer vision technologies to stay at the forefront of the field. Collaborate with cross-functional teams to develop innovative solutions that meet project requirements. Monitor the performance and accuracy of computer vision models, making necessary adjustments and improvements. Maintain and update computer vision systems to ensure their continued functionality and relevance. Provide technical support and guidance to team members and customers using computer vision systems. Requirements 3 - 5 years of experience as a Computer Vision Engineer. Bachelor's degree in Computer Science, or a related field. Proven experience in developing computer vision systems, including hands-on implementation and deployment. Strong knowledge of computer vision algorithms, libraries and tools, such as OpenCV, TensorFlow, PyTorch, Keras, NumPy, scikit-image, PIL, Matplotlib, Seaborn, etc. Familiarity with tools and libraries commonly used in computer vision projects such as CUDA, OpenCL, OpenGL. Expertise in various computer vision projects, including object detection, image classification, text detection & OCR, face detection, generative models, video analytics, object tracking and model compression/optimization. Knowledge of runtime AI frameworks like ONNX, TensorRT, OpenVINO. Experience in cloud platforms (AWS, Azure), Docker, Kubernetes and GitHub. Experience in training models through GPU computing or on the cloud. Familiarity with machine learning and deep learning concepts and frameworks. Excellent problem-solving skills and the ability to think analytically. Good written and verbal communication skills for effectively communicating with the team and ability to present information to varied technical and non-technical audiences. Ability to work independently and in a fast-paced environment and also be able to work in a team when required. Desired Candidate Profile Experience: 3 - 5 years Location: Bangalore/Coimbatore Qualification: Computer Science or a related field Job Type: Full-Time, Permanent Schedule: Day Shift, Monday to Friday Workplace Type: On-site (Work from Office) Notice Period: Immediate

Entity :- Accenture Strategy & Consulting Team :- Strategy & Consulting Global Network Practice :- Communications & Media - AI & Data Architectures Title :- Ind & Func AI Value Strategy Manager Job location :- Bangalore, Hyderabad About S&C - Global Network:- Accenture Strategy & Consulting Global Network - Data & AI practice help our clients grow their business in entirely new ways. Analytics enables our clients to achieve high performance through insights from data - insights that inform better decisions and strengthen customer relationships. From strategy to execution, Accenture works with organizations to develop analytic capabilities - from accessing and reporting on data to predictive modelling - to outperform the competition. WHAT'S IN IT FOR YOU? Accenture has committed to invest USD 3Billion into GenAI in the next 3 years. We will continually invest in your learning and growth. Youll work with Accenture's highly skilled and experienced practitioners, and Accenture will support you in growing your own career path and interests. You'll be part of a diverse, vibrant, global Accenture Data and AI community, continually pushing the boundaries of business capabilities. What you would do in this role ML Maturity Assessment: Conduct comprehensive assessments of the organizations ML maturity, identifying strengths, weaknesses, and areas for improvement. Provide strategic recommendations to enhance the overall ML capability and align it with business objectives. ML Ops Roadmap & Processes: Develop ML Ops roadmaps and establish robust processes for the end-to-end machine learning lifecycle, including data preparation, model training, deployment, and monitoring. Implement best practices in ML Ops to ensure efficiency, scalability, and reliability of ML systems. Implementation of Gen AI Solutions: Lead the design and implementation of state-of-the-art Generative AI solutions, leveraging deep learning frameworks such as TensorFlow and PyTorch. Drive innovation in Gen AI, staying abreast of the latest advancements and incorporating cutting-edge technologies into solutions. Incubating and Designing: Proactively identify opportunities for ML and Gen AI applications within the organization. Work closely with cross-functional teams to incubate and design bespoke ML solutions tailored to business requirements. Technical Leadership: Provide technical leadership and mentorship to data scientists, engineers, and other team members. Collaborate with stakeholders to ensure alignment between technical solutions and business objectives. Collaboration and Communication: Collaborate with business stakeholders to understand their needs and translate them into ML and Gen AI requirements. Effectively communicate complex technical concepts to non-technical audiences. Qualifications Who we are looking for? Bachelors or advanced degree in Computer Science, Data Science, or a related field. Over 12 years of hands-on experience in machine learning, with a focus on architecting end-to-end solutions. Proven expertise in conducting ML maturity assessments and developing ML Ops roadmaps. Demonstrable hands-on experience in designing & flawlessly operationalizing the Machine learning system on a cloud and / or an On-Prem platform. Extensive experience in implementing Generative AI solutions, including incubation, design, and deployment. Strong proficiency in deep learning frameworks such as TensorFlow and PyTorch. In-depth knowledge of ML Ops best practices and processes. Excellent problem-solving skills and ability to design scalable and reliable ML architectures. Strong leadership and communication skills, with a track record of leading successful ML initiatives. Experience in Telecom or Hi Tech or Software and platform industry desirable Tools & Techniques: TensorFlow, PyTorch, Scikit-learn, Keras NumPy, Pandas Matplotlib, Seaborn TensorFlow Serving, Docker and Kubernetes Good software engineering practices, including code modularization, documentation, and testing. Experience with API , Integration architecture , microservices If you are a visionary Machine Learning Architect with a passion for advancing ML maturity, implementing cutting-edge Gen AI solutions, and driving innovation, we invite you to apply and contribute to our organizations success. Accenture is an equal opportunities employer and welcomes applications from all sections of society and does not discriminate on grounds of race, religion or belief, ethnic or national origin, disability, age, citizenship, marital, domestic or civil partnership status, sexual orientation, gender identity, or any other basis as protected by applicable law.

As an Associate level Data Scientist at IBM, you will work to solve business problems using leading edge and open-source tools such as Python, R, and TensorFlow, combined with IBM tools and our AI application suites. You will prepare, analyze, and understand data to deliver insight, predict emerging trends, and provide recommendations to stakeholders. In your role, you may be responsible for: Implementing and validating predictive and prescriptive models and creating and maintaining statistical models with a focus on big data & incorporating machine learning. techniques in your projects Writing programs to cleanse and integrate data in an efficient and reusable manner Working in an Agile, collaborative environment, partnering with other scientists, engineers, consultants and database administrators of all backgrounds and disciplines to bring analytical rigor and statistical methods to the challenges of predicting behaviors Communicating with internal and external clients to understand and define business needs and appropriate modelling techniques to provide analytical solutions. Evaluating modelling results and communicating the results to technical and non-technical audiences. We have 1 of positions open in these locations: Bangalore, Karnataka, India. The below requirements are a guideline. If you have transferable skills we encourage you to apply to this role. Required education Bachelor's Degree Preferred education Master's Degree Required technical and professional expertise 2+ Years of experience. Technical Skills : Proficiency in programming languages such as Python, R, or SQL. Experience with machine learning frameworks such as Scikit-learn, TensorFlow, or PyTorch. Strong knowledge of statistical techniques (e.g., regression, classification, hypothesis testing). Familiarity with data manipulation libraries (e.g., Pandas, NumPy) and data visualization tools (e.g., Matplotlib, Seaborn, Tableau). Experience working with databases and data storage systems (e.g., SQL, NoSQL). Problem-Solving: Ability to think critically and solve complex problems using data-driven approaches. Communication: Strong written and verbal communication skills to present technical concepts to non-technical stakeholders. Teamwork: Ability to work in a collaborative team environment and contribute to both individual and group projects. Detail-Oriented: High attention to detail and commitment to producing accurate and high-quality work. Preferred technical and professional experience Experience with cloud platforms (e.g., AWS, Google Cloud, Azure) for data science workflows. Knowledge of big data technologies (e.g., Hadoop, Spark). Experience with deep learning techniques.

Entity :- Accenture Strategy Consulting Team :- Strategy Consulting Global Network Practice :- Communications Media - AI Data Architectures Title :- IF Decision Sci Practitioner Consultant Job location :- Bangalore, Hyderabad About SC - Global Network:- Accenture Strategy Consulting Global Network - Data AI practice help our clients grow their business in entirely new ways. Analytics enables our clients to achieve high performance through insights from data - insights that inform better decisions and strengthen customer relationships. From strategy to execution, Accenture works with organizations to develop analytic capabilities - from accessing and reporting on data to predictive modelling - to outperform the competition. WHAT'S IN IT FOR YOU Accenture has committed to invest USD 3Billion into GenAI in the next 3 years. We will continually invest in your learning and growth. Youll work with Accenture's highly skilled and experienced practitioners, and Accenture will support you in growing your own career path and interests. You'll be part of a diverse, vibrant, global Accenture Data and AI community, continually pushing the boundaries of business capabilities. What you would do in this role ML Maturity Assessment: Conduct comprehensive assessments of the organizations ML maturity, identifying strengths, weaknesses, and areas for improvement. Provide strategic recommendations to enhance the overall ML capability and align it with business objectives. ML Ops Roadmap Processes: Develop ML Ops roadmaps and establish robust processes for the end-to-end machine learning lifecycle, including data preparation, model training, deployment, and monitoring. Implement best practices in ML Ops to ensure efficiency, scalability, and reliability of ML systems. Implementation of Gen AI Solutions: Lead the design and implementation of state-of-the-art Generative AI solutions, leveraging deep learning frameworks such as TensorFlow and PyTorch. Drive innovation in Gen AI, staying abreast of the latest advancements and incorporating cutting-edge technologies into solutions. Incubating and Designing: Proactively identify opportunities for ML and / or Gen AI applications within the organization. Work closely with cross-functional teams to incubate and design bespoke ML solutions tailored to business requirements. Technical Leadership: Provide technical leadership and mentorship to data scientists, engineers, and other team members. Collaborate with stakeholders to ensure alignment between technical solutions and business objectives. Collaboration and Communication: Collaborate with business stakeholders to understand their needs and translate them into ML and Gen AI requirements. Effectively communicate complex technical concepts to non-technical audiences. Qualifications Who we are looking for Bachelors or advanced degree in Computer Science, Data Science, or a related field. Over 8 years of hands-on experience in machine learning, with a focus on architecting end-to-end solutions. Proven expertise in conducting ML maturity assessments and developing ML Ops roadmaps. Hands-on experience in operationalizing the Machine learning system on a cloud and / or an On-Prem platform. Experience in implementing Generative AI solutions, including incubation, design, and deployment will be a big plus. Proficiency in deep learning frameworks such as TensorFlow and PyTorch. Good knowledge of ML Ops best practices and processes. Excellent problem-solving skills and ability to design scalable and reliable ML architectures. Strong leadership and communication skills, with a track record of leading successful ML initiatives. Experience in Telecom or Hi Tech or Software and platform industry desirable Tools Techniques: TensorFlow, PyTorch, Scikit-learn, Keras NumPy, Pandas Matplotlib, Seaborn TensorFlow Serving, Docker and Kubernetes Good software engineering practices, including code modularization, documentation, and testing. Experience with open API , Integration architecture , microservices If you are a visionary Machine Learning Architect with a passion for advancing ML maturity, implementing cutting-edge Gen AI solutions, and driving innovation, we invite you to apply and contribute to our organizations success. Accenture is an equal opportunities employer and welcomes applications from all sections of society and does not discriminate on grounds of race, religion or belief, ethnic or national origin, disability, age, citizenship, marital, domestic or civil partnership status, sexual orientation, gender identity, or any other basis as protected by applicable law.

We are looking for a Data Scientist with a strong background in Machine Learning, Deep Learning, and AI-driven applications. The ideal candidate should be passionate about building models, extracting insights from data, fine-tuning LLMs, and developing AI-powered solutions. You will work closely with cross-functional teams to develop innovative AI applications and help drive data-driven decision-making. Key Responsibilities: Data Analysis & Pattern Recognition ? Read and analyze large datasets to uncover trends and actionable insights. Model Development ? Build, train, and optimize Machine Learning/Deep Learning models. Generative AI & LLM Fine-Tuning ? Work on fine-tuning large language models, Retrieval-Augmented Generation (RAG), and NLP/NLU applications. AI-Powered Applications ? Develop AI-driven applications, including chatbots and automation tools. Computer Vision & OpenCV ? Implement image processing and deep learning models for visual data. MLOps & Deployment ? Develop and deploy ML models using MLOps frameworks for scalability and efficiency. Agentic AI & Autonomous Systems (Preferred) ? Research and implement AI agents for decision-making tasks. Data Visualization & Insights ? Utilize visualization tools to present findings and support strategic decisions. Domain Understanding & Strategy ? Collaborate with stakeholders to understand business needs and contribute AI-driven solutions. Be a team player and help the team to build applications Requirements Programming: Python Machine Learning & Deep Learning: TensorFlow, PyTorch, Scikit-learn NLP & NLU: Large Language Models, Transformers, RAG Applications Computer Vision: OpenCV, Image Processing, Object Detectio MLOps & Model Deployment: Docker, Kubernetes, MLflow Generative AI & LLM Fine-Tuning: OpenAI, Hugging Face, LangChain Data Visualization: Tableau, Power BI, Matplotlib, Seaborn Agentic AI (Preferred but not mandatory)

Project Role : AI / ML Engineer Project Role Description : Develops applications and systems that utilize AI tools, Cloud AI services, with proper cloud or on-prem application pipeline with production ready quality. Be able to apply GenAI models as part of the solution. Could also include but not limited to deep learning, neural networks, chatbots, image processing. Must have skills : Machine Learning Good to have skills : NA Minimum 3 year(s) of experience is required Educational Qualification : 15 years full time education Summary :These roles have many overlapping skills with GENAI Engineers and architects. Description may scaleup/scale down based on expected seniority. Roles & Responsibilities:-Implement generative AI models, identify insights that can be used to drive business decisions. Work closely with multi-functional teams to understand business problems, develop hypotheses, and test those hypotheses with data, collaborating with cross-functional teams to define AI project requirements and objectives, ensuring alignment with overall business goals.-Conducting research to stay up-to-date with the latest advancements in generative AI, machine learning, and deep learning techniques and identify opportunities to integrate them into our products and services.-Optimizing existing generative AI models for improved performance, scalability, and efficiency.-Ensure data quality and accuracy-Leading the design and development of prompt engineering strategies and techniques to optimize the performance and output of our GenAI models.-Implementing cutting-edge NLP techniques and prompt engineering methodologies to enhance the capabilities and efficiency of our GenAI models.-Determining the most effective prompt generation processes and approaches to drive innovation and excellence in the field of AI technology, collaborating with AI researchers and developers-Experience working with cloud based platforms (example:AWS, Azure or related)-Strong problem-solving and analytical skills-Proficiency in handling various data formats and sources through Omni Channel for Speech and voice applications, part of conversational AI-Prior statistical modelling experience-Demonstrable experience with deep learning algorithms and neural networks-Developing clear and concise documentation, including technical specifications, user guides, and presentations, to communicate complex AI concepts to both technical and non-technical stakeholders.-Contributing to the establishment of best practices and standards for generative AI development within the organization. Professional & Technical Skills:-Must have solid experience developing and implementing generative AI models, with a strong understanding of deep learning techniques such as GPT, VAE, and GANs.-Must be proficient in Python and have experience with machine learning libraries and frameworks such as TensorFlow, PyTorch, or Keras.-Must have strong knowledge of data structures, algorithms, and software engineering principles.-Must be familiar with cloud-based platforms and services, such as AWS, GCP, or Azure.-Need to have experience with natural language processing (NLP) techniques and tools, such as SpaCy, NLTK, or Hugging Face.-Must be familiar with data visualization tools and libraries, such as Matplotlib, Seaborn, or Plotly.-Need to have knowledge of software development methodologies, such as Agile or Scrum.-Possess excellent problem-solving skills, with the ability to think critically and creatively to develop innovative AI solutions. Additional Information:-Must have a degree in Computer Science, Artificial Intelligence, Machine Learning, or a related field. A Ph.D. is highly desirable.-strong communication skills, with the ability to effectively convey complex technical concepts to a diverse audience.-You possess a proactive mindset, with the ability to work independently and collaboratively in a fast-paced, dynamic environment. Qualifications 15 years full time education

Project Role : AI / ML Engineer Project Role Description : Develops applications and systems that utilize AI tools, Cloud AI services, with proper cloud or on-prem application pipeline with production ready quality. Be able to apply GenAI models as part of the solution. Could also include but not limited to deep learning, neural networks, chatbots, image processing. Must have skills : Machine Learning Good to have skills : NA Minimum 5 year(s) of experience is required Educational Qualification : 15 years full time education Summary :These roles have many overlapping skills with GENAI Engineers and architects. Description may scaleup/scale down based on expected seniority. Roles & Responsibilities:-Implement generative AI models, identify insights that can be used to drive business decisions. Work closely with multi-functional teams to understand business problems, develop hypotheses, and test those hypotheses with data, collaborating with cross-functional teams to define AI project requirements and objectives, ensuring alignment with overall business goals.-Conducting research to stay up-to-date with the latest advancements in generative AI, machine learning, and deep learning techniques and identify opportunities to integrate them into our products and services.-Optimizing existing generative AI models for improved performance, scalability, and efficiency.-Ensure data quality and accuracy-Leading the design and development of prompt engineering strategies and techniques to optimize the performance and output of our GenAI models.-Implementing cutting-edge NLP techniques and prompt engineering methodologies to enhance the capabilities and efficiency of our GenAI models.-Determining the most effective prompt generation processes and approaches to drive innovation and excellence in the field of AI technology, collaborating with AI researchers and developers-Experience working with cloud based platforms (example:AWS, Azure or related)-Strong problem-solving and analytical skills-Proficiency in handling various data formats and sources through Omni Channel for Speech and voice applications, part of conversational AI-Prior statistical modelling experience-Demonstrable experience with deep learning algorithms and neural networks-Developing clear and concise documentation, including technical specifications, user guides, and presentations, to communicate complex AI concepts to both technical and non-technical stakeholders.-Contributing to the establishment of best practices and standards for generative AI development within the organization. Professional & Technical Skills:-Must have solid experience developing and implementing generative AI models, with a strong understanding of deep learning techniques such as GPT, VAE, and GANs.-Must be proficient in Python and have experience with machine learning libraries and frameworks such as TensorFlow, PyTorch, or Keras.-Must have strong knowledge of data structures, algorithms, and software engineering principles.-Must be familiar with cloud-based platforms and services, such as AWS, GCP, or Azure.-Need to have experience with natural language processing (NLP) techniques and tools, such as SpaCy, NLTK, or Hugging Face.-Must be familiar with data visualization tools and libraries, such as Matplotlib, Seaborn, or Plotly.-Need to have knowledge of software development methodologies, such as Agile or Scrum.-Possess excellent problem-solving skills, with the ability to think critically and creatively to develop innovative AI solutions. Additional Information:-Must have a degree in Computer Science, Artificial Intelligence, Machine Learning, or a related field. A Ph.D. is highly desirable.-strong communication skills, with the ability to effectively convey complex technical concepts to a diverse audience.-You possess a proactive mindset, with the ability to work independently and collaboratively in a fast-paced, dynamic environment. Qualifications 15 years full time education