70 Unsupervised Learning Jobs - Page 2

As a Senior Data Scientist with 5+ years of experience, you will play a crucial role in our team based in Indore/Pune. Your responsibilities will involve designing and implementing models, extracting insights from data, and interpreting complex data structures to facilitate business decision-making. You should have a strong background in Machine Learning areas such as Natural Language Processing, Machine Vision, Time Series, etc. Your expertise should extend to Model Tuning, Model Validation, Supervised and Unsupervised Learning. Additionally, hands-on experience with model development, data preparation, and deployment of models for training and inference is essential. Proficiency in descriptive and inferential statistics, hypothesis testing, and data analysis and exploration are key skills required for this role. You should be adept at developing code that enables reproducible data analysis. Familiarity with AWS services like Sagemaker, Lambda, Glue, Step Functions, and EC2 is expected. Knowledge of data science code development and deployment IDEs such as Databricks, Anaconda distribution, and similar tools is essential. You should also possess expertise in ML algorithms related to time-series, natural language processing, optimization, object detection, topic modeling, clustering, and regression analysis. Your skills should include proficiency in Hive/Impala, Spark, Python, Pandas, Keras, SKLearn, StatsModels, Tensorflow, and PyTorch. Experience with end-to-end model deployment and production for at least 1 year is required. Familiarity with Model Deployment in Azure ML platform, Anaconda Enterprise, or AWS Sagemaker is preferred. Basic knowledge of deep learning algorithms like MaskedCNN, YOLO, and visualization and analytics/reporting tools such as Power BI, Tableau, Alteryx would be advantageous for this role.,

As a data science expert, you will be responsible for developing strategies and solutions to address various problems using cutting-edge machine learning, deep learning, and GEN AI techniques. Your role will involve leading a team of data scientists to ensure timely and high-quality delivery of project outcomes. You will analyze large and complex datasets across different domains, perform exploratory data analysis, and select features to build and optimize classifiers and regressors. Enhancing data collection procedures, ensuring data quality and accuracy, and presenting analytical results to technical and non-technical stakeholders will be key aspects of your job. You will create custom reports and presentations with strong data visualization skills to effectively communicate analytical conclusions to senior company officials and other stakeholders. Proficiency in data mining, EDA, feature selection, model building, and optimization using machine learning and deep learning techniques is essential. Your primary skills should include a deep understanding and hands-on experience with data science and machine learning techniques, algorithms for supervised and unsupervised problems, NLP, computer vision, and GEN AI. You should also have expertise in building deep learning models for text and image analytics using frameworks like ANNs, CNNs, LSTM, Transfer Learning, Encoder, and decoder. Proficiency in programming languages such as Python, R, and common data science tools like NumPy, Pandas, Matplotlib, and frameworks like TensorFlow, Keras, PyTorch, XGBoost is required. Experience with statistical inference, hypothesis testing, and cloud platforms like Azure/AWS, as well as deploying models in production, will be beneficial for this role. Excellent communication and interpersonal skills are necessary to convey complex analytical concepts to diverse stakeholders effectively.,

lululemon is an innovative performance apparel company that specializes in providing high-quality products for yoga, running, training, and other athletic activities. Our focus lies in developing technical fabrics and functional designs to create products and experiences that support individuals in their journey of movement, growth, connection, and overall well-being. At lululemon, we attribute our success to our dedication to innovation, our commitment to our people, and the meaningful relationships we establish within the communities we serve. We are dedicated to driving positive change and fostering a healthier and more prosperous future. A key aspect of our mission involves cultivating an environment that is equitable, inclusive, and growth-oriented for all our team members. Our India Tech Hub is instrumental in enhancing our technological capabilities across various domains such as Product Systems, Merchandising and Planning, Digital Presence, distribution and logistics, and corporate systems. The team in India collaborates closely with our global team on projects of strategic significance. Joining the Content team at lululemon offers an exciting opportunity to contribute to a fast-paced environment that is constantly exploring new initiatives to support our rapidly expanding business. We are a team that embraces cutting-edge technology and is driven by a continuous pursuit of improvement. Innovation is at the core of our ethos, and we encourage each other to step out of our comfort zones and embrace new challenges. Professional and personal growth is paramount to us, and we believe in learning from failures to pave the way for a brighter future. We foster an environment where team members can freely share feedback and ideas, promoting ongoing organizational growth. Operating within an agile methodology, we collaborate with product teams across various functions and a core commerce platform team. At lululemon, we prioritize creating a culture of enjoyment and lightheartedness in our daily work routine. We recognize the strength in unity and celebrate the fact that we are more powerful as a team rather than as individuals. Responsibilities: - Develop Statistical/Machine Learning models/analysis for Merchandising and Planning Business problems - Play a key role in all stages of the Data science project life cycle - Collaborate with Product Management and Business teams to gain Business understanding and collect requirements - Identify necessary data sources and automate the collection process - Conduct pre-processing and exploratory data analysis - Evaluate and interpret results, presenting findings to stakeholders and business leaders - Collaborate with engineering and product development teams to deploy models into production systems when applicable Requirements and Skills: - Demonstrated experience in delivering technical solutions using Time Series/Machine Learning techniques - Proficient in applied Statistical skills, including familiarity with Statistical tests, distributions, etc. - Strong expertise in applied Machine Learning skills such as Time Series, Regression Analysis, Supervised and Unsupervised Learning - Proficient Programming Skills in Python and database query languages like SQL, with additional familiarity with Snowflake & Databricks being advantageous - Experience with time series forecasting techniques like ARIMA, Prophet, Deep AR - Familiarity with data visualization libraries such as Plotly, Business intelligence tools like PowerBI, Tableau - Excellent communication and presentation abilities - Previous experience in the Retail industry Responsibilities: - Identify valuable data sources and automate collection processes - Preprocess structured and unstructured data - Analyze large datasets to identify trends and patterns - Develop predictive models and machine-learning algorithms - Employ ensemble modeling techniques - Utilize data visualization methods to present information effectively - Propose actionable solutions and strategies to address business challenges - Collaborate with engineering and product development teams,

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) Additional Information: - Qualification Experience: Minimum 3 year(s) of experience is required Educational Qualification: Bachelors or Master's degree in Data Science, Statistics, Computer Science, Mathematics, or a related field.

The Data Science and AI/ML team collaborates across the organization to identify, develop and deliver Artificial Intelligence (AI) and Machine Learning (ML) powered software solutions that improve patient outcomes, delight partners and customers, and enhance business operations in an AI First fashion. The team works on projects ranging from building sophisticated models to delivering personalized recommendations to patients, analyzing sleep data to optimize equipment and settings, proactively identifying health risk factors, and optimizing global supply chain operations. As a Sr. Machine Learning Engineer, you will play a crucial role in contributing to and leading the development of ML architecture and operations. Your responsibilities include optimizing time to market and quality of AI/ML applications by working on projects within the AI operations team. You will ensure that global AI/ML systems are production-grade, scalable, and utilize cutting-edge technology and methodology. Additionally, you will collaborate with stakeholders, mentor junior team members, and engage with business stakeholders. Key Responsibilities: - Collaborate with Product Management, Engineering, and other stakeholders to create impactful AI/ML features and products. - Work closely with Data Scientists and Data Engineers to own the end-to-end process, train junior team members, and maintain AI/ML architectures. - Document model design, experiments, tests, and outcomes, and stay informed of industry trends. - Implement process improvements, build production-level AI/ML systems, and support technical issues for stakeholders. - Participate in Code Review and handle escalated incidents to resolution. Requirements: - 4+ years of industry experience in Machine Learning Engineering, Data Science, or Data Engineering. - M.S or PhD in Data Science/Machine Learning or related areas. - Proficiency in data analytics systems development, model building, and online deployment. - Experience in building scalable AI/ML systems for various advanced problems. - Hands-on experience with large datasets, Python, and cloud-based tools. - Strong mathematical foundation and knowledge of machine learning techniques. Joining the team means more than just a job it's an opportunity to be part of a culture that values excellence, diversity, and innovation. If you are looking for a challenging and supportive environment where your ideas are encouraged, apply now to be a part of our team dedicated to making the world a healthier place. We are committed to reviewing every application we receive.,

Machine learning (ML) is a subfield of artificial intelligence that enables systems to learn from data and improve their performance on specific tasks without explicit programming. It focuses on developing algorithms that can analyze data, identify patterns, and make predictions or decisions. Essentially, machine learning allows computers to learn from experience, just like humans do, by adjusting their behavior based on the data they are exposed to. Core Concepts: - Learning from Data: Machine learning algorithms are trained on large datasets to identify patterns and relationships within the data. - No Explicit Programming: Unlike traditional programming, where you tell the computer exactly what to do, ML algorithms learn from data and adapt their behavior. - Prediction and Decision Making: The goal of ML is to enable systems to make accurate predictions or decisions based on the patterns they have learned. - Adaptability and Improvement: As ML models are exposed to more data, they can improve their performance and become more accurate over time. Types of Machine Learning: - Supervised Learning: Algorithms are trained on labeled data, where the desired output is provided for each input. - Unsupervised Learning: Algorithms work with unlabeled data and try to find hidden patterns or structures within the data. - Reinforcement Learning: Algorithms learn by interacting with an environment and receiving rewards or penalties for their actions. Job Types: Full-time, Fresher Benefits: - Provident Fund Schedule: - Day shift Work Location: In person,

Skill required: Data Scientist - Data Science Designation: I&F Decision Science Practitioner Specialist Qualifications: Any Graduation Years of Experience: Experienced About Accenture 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. Visit us at www.accenture.com What would you do You will be aligned with our Insights & Intelligence vertical and help us generate insights by leveraging the latest Artificial Intelligence (AI) and Analytics techniques to deliver value to our clients. You will also help us apply your expertise in building world-class solutions, conquering business problems, addressing technical challenges using AI Platforms and technologies. You will be required to utilize the existing frameworks, standards, patterns to create architectural foundation and services necessary for AI applications that scale from multi-user to enterprise-class and demonstrate yourself as an expert by actively blogging, publishing research papers, and creating awareness in this emerging area. You will be working as a part of Marketing & Customer Analytics team which provides a set of processes that measure, manage and analyze marketing activities in order to provide actionable insights and recommendations to marketing organizations in terms of optimizing ROI & performance efficiency in operations.Customer analytics is a process by which data from customer behavior is used to help make key business decisions via market segmentation and predictive analytics. This information is used by businesses for direct marketing, site selection, and customer relationship management. You should have exposure to digital marketing, A/B testing, MVT, Google Analytics/Site Catalyst. You will be a core member of Accenture Operations global Applied Intelligence 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. The objectives of the team include but are not limited toLeading 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. What are we looking for Extensive experience in leading Data Science and Advanced Analytics delivery teams Strong statistical programming experience - Python, R, SAS, S-plus, MATLAB, STATA or SPSS. Experience working with large data sets and big data tools like Snowflake, AWS, Spark, etc. Solid knowledge in at least one of the following Supervised and Unsupervised Learning, Classification, Regression, Clustering, Neural Networks, Ensemble Modelling (random forest, boosted tree, etc.), Multivariate Statistics, Non-parametric Methods, Reliability Models, Markov Models, Stochastic models, Bayesian Models Experience in atleast one of these business domainsCPG, 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 Roles and Responsibilities: In this role you are required to do analysis and solving of moderately complex problems Typically creates new solutions, leveraging and, where needed, adapting existing methods and procedures The person requires understanding of the strategic direction set by senior management as it relates to team goals Primary upward interaction is with direct supervisor or team leads Generally, interacts with peers and/or management levels at a client and/or within Accenture The person should require minimal guidance when determining methods and procedures on new assignments Decisions often impact the team in which they reside and occasionally impact other teams Individual would manage medium-small sized teams and/or work efforts (if in an individual contributor role) at a client or within Accenture Please note that this role may require you to work in rotational shifts Qualification Any Graduation

As a Data Scientist, you will be responsible for building cutting-edge models using NLP, ML, and AI techniques to solve a variety of problems across different domains. Your main tasks will include working closely with the engineering team to deploy models in production, validating the models, and ensuring their effectiveness. You should possess expert-level knowledge in Natural Language Processing, Information Extraction, Scraping, and Text Mining Algorithms, as well as a strong familiarity with deep learning methods for text analytics. Proficiency in Machine Learning algorithms such as XGBoost, Linear Regression, Logistic Regression, SVM, Random Forest, Bayesian Methods, Unsupervised Learning, and Reinforcement Learning is essential for this role. Additionally, experience in time series analysis with real-world datasets, familiarity with technologies like Flask, FastAPI, and Hug, and being an expert Python programmer are key requirements for this position. You should have a proven track record of expertise demonstrated through high-quality publications, competitions, or challenges. Collaboration with domain experts, a passion for making a meaningful impact, and strong problem-solving skills are highly valued attributes. A minimum qualification of B.E/B.Tech in Computer Science, Electrical Engineering, or EXTC with a solid foundation in mathematics and statistics is necessary. Excellent communication skills, teamwork abilities, and the capacity to thrive in a startup environment are also essential for success in this role. In this role, you will be expected to take care of Text Analytics on Qualitative Customer Feedback and Call Center complaints conversations via Email or Chat. The ideal candidate should have 2 to 8 years of relevant experience, with a salary ranging from 15 Lac to 18 Lac P.A. The industry focus is on Analytics and Business Intelligence. If you are a Data Scientist with expertise in Core Python, Machine Learning, and a strong interest in an internship, this opportunity is perfect for you. Walk-ins are welcome for candidates who meet the specified qualifications and key skills outlined above.,

We are looking for a skilled Generative AI Developer to be a part of our team and contribute to the development of advanced generative models. In this role, you will focus on creating AI systems that have the ability to produce innovative and human-like content across various domains such as natural language generation, image generation, and even video or music synthesis. To excel in this position, you should possess expertise in machine learning, deep learning, and natural language processing, along with a thorough understanding of specific generative models like GANs, VAEs, and other neural networks. Your responsibilities will involve developing and refining generative models using techniques such as GANs, VAEs, Transformers, and Diffusion models. You will also be working on tasks related to text generation, image generation, music or sound generation, video creation, and other creative AI applications. Furthermore, you will be expected to design, construct, and deploy models utilizing frameworks like TensorFlow, PyTorch, Hugging Face, OpenAI's GPT, or similar tools. It will be crucial to optimize AI models for performance, accuracy, and scalability in real-world production environments. Staying updated on the latest trends, research papers, and breakthroughs in the field of generative AI will also be a part of your role. Collaboration with other teams, such as data scientists, machine learning engineers, and product teams, to integrate models into production systems will be essential. Additionally, you will work on data preprocessing, augmentation, and designing pipelines to ensure high-quality input for model training. Documenting your code, processes, and model outputs for team-wide visibility and knowledge sharing will also be a key aspect of your responsibilities. **Required Qualifications & Skills:** - Bachelor's or Master's degree in Computer Science or related fields. - 3-4 years of hands-on experience in developing Generative AI solutions. - Strong understanding of deep learning algorithms, particularly in generative models like GANs, VAEs, Diffusion models, or large-scale language models like GPT. - Hands-on experience with machine learning frameworks and libraries such as TensorFlow, PyTorch, or Hugging Face. - Experience working with neural networks, unsupervised learning, and natural language processing. - Proficient programming skills in Python, including deep learning libraries like TensorFlow, Keras, and PyTorch. - Familiarity with cloud platforms (AWS, GCP, or Azure) for model training and deployment. - Solid mathematical and statistical knowledge, especially in probability theory, linear algebra, and optimization. - Experience in large-scale model training, fine-tuning, or distributed computing. - Knowledge of reinforcement learning and self-supervised learning. - Understanding of AI ethics, bias mitigation, and interpretability in generative models.,

Job Role: As a Senior Data Scientist, you will be responsible for designing, developing and productionizing of ML-driven solutions to business problems. You will work closely with local and onshore team of data scientists and stakeholders to understand their needs and pain points, and then translate those into actionable data science projects. Your primary focus will be statistical data analyses and helping build high-quality predictive models integrated with our products. The ideal candidate is an experienced data wrangler with a deep understanding of data science principles and a proven track record of delivering ML-driven solutions. S/he will effectively communicate complex technical concepts to technical and non-technical audiences. Key Responsibilities: Plan, productionize, and document scalable Data Science solutions Understand the business problem from stakeholders and convert it to actionable tasks Driven to create in-depth Exploratory Data Analysis and Feature Engineering; experienced with ML Ops Adept at standard and latest ML algorithms and Model explainability. Knowledge about causal inference is a great to-have Help mentor and guide Data Scientists Qualifications - Internal Key Requirements: Experience : At least 8 years of relevant experience Education: Bachelors or masters degree in computer science or mathematics, Statistics or a related field. PhD with lesser experience is welcome. Required Skills: Proficient in ML models across supervised and unsupervised learning, along with knowledge of Deep Learning models using TensorFlow / PyTorch Experienced in Natural Language Processing with focus on Transformer models Experienced in using Generative AI. At least one project implementation is expected Knowledge in MLOps is recommended Extensive coding experience in Python (and R) as well as scripting in SQL Visualization of outputs, using Tableau/ Power BI/ Streamlit, along with crisp communication Strong ability to assess the business problem and suggest applicable data science solutions Great at presenting and explaining model results to any kind of audience Personal Attributes: Ability to adapt and work with a distributed team Ability to manage multiple initiatives Ability to work with ambiguous requirements, seek clarity and manage risks. Ability to communicate complex concepts in a simple yet intelligent way.

Armada is an edge computing startup dedicated to providing computing infrastructure to remote areas with limited connectivity and cloud infrastructure. Our mission is to bridge the digital divide by deploying advanced technology infrastructure globally. We are seeking passionate AI Engineers to join our team and work on exciting AI and ML challenges in diverse locations around the world. As an AI Engineer at Armada, you will be responsible for developing ML/DL models tailored to specific challenges, preparing datasets, evaluating model performance, and deploying solutions in production environments. Ideal candidates will have expertise in machine learning, deep learning, and real-time computer vision techniques. Experience with containerization, microservices architecture, and deploying ML models independently is essential for this role. This role is office-based at our Trivandrum, Kerala office. Key responsibilities include translating business requirements into AI/ML model requirements, building AI/ML/DL models using state-of-the-art algorithms, testing and evaluating models, and deploying them in production environments. You will also work with customers and internal teams to refine model quality and establish continuous learning pipelines. The ideal candidate will have a BS or MS degree in computer science or related field, along with 5+ years of software development experience. Proficiency in Python, Java, and/or C/C++, as well as expertise in traditional statistical machine learning and deep learning techniques, is required. Experience with major deep learning frameworks (e.g., PyTorch, Tensorflow) and solving real-world problems with machine learning is highly desirable. Preferred experience includes building software for autonomous systems, working with container platforms like Kubernetes, and strong analytical and time-management skills. We offer a competitive salary and equity options for India-based candidates, providing an opportunity to share in Armada's success and growth. If you are a self-driven individual with a passion for cutting-edge AI and thrive in a fast-paced, collaborative environment, we encourage you to apply. Join our dynamic AI Engineering team and contribute to developing disruptive edge-compute systems with real-world applications. At Armada, we are committed to equal opportunity and value teamwork, innovation, and a results-driven approach.,

As an AI/ML Manager at our Pune location, you will be responsible for leading the development of machine learning proof of concepts (PoCs) and demos using structured/tabular data for various use cases like forecasting, risk scoring, churn prediction, and optimization. Your role will involve collaborating with sales engineering teams to understand client requirements and presenting ML solutions during pre-sales calls and technical workshops. You will be expected to build ML workflows using tools such as SageMaker, Azure ML, or Databricks ML, managing training, tuning, evaluation, and model packaging. Applying supervised, unsupervised, and semi-supervised techniques like XGBoost, CatBoost, k-Means, PCA, and time-series models will be a key part of your responsibilities. Working closely with data engineering teams, you will define data ingestion, preprocessing, and feature engineering pipelines using Python, Spark, and cloud-native tools. Packaging and documenting ML assets for scalability and transition into delivery teams post-demo will be essential. Staying updated with the latest best practices in ML explainability, model performance monitoring, and MLOps practices is also expected. Participation in internal knowledge sharing, tooling evaluation, and continuous improvement of lab processes are additional aspects of this role. To qualify for this position, you should have at least 8+ years of experience in developing and deploying classical machine learning models in production or PoC environments. Strong hands-on experience with Python, pandas, scikit-learn, and ML libraries like XGBoost, CatBoost, LightGBM is required. Familiarity with cloud-based ML environments such as AWS SageMaker, Azure ML, or Databricks is preferred. A solid understanding of feature engineering, model tuning, cross-validation, and error analysis is necessary. Experience with unsupervised learning, clustering, anomaly detection, and dimensionality reduction techniques will be beneficial. You should be comfortable presenting models and insights to both technical and non-technical stakeholders during pre-sales engagements. Working knowledge of MLOps concepts, including model versioning, deployment automation, and drift detection, will be an advantage. If you are interested in this opportunity, please apply or share your resume at kanika.garg@austere.co.in.,

You will be involved in building a machine learning-based anomaly detection system using structured and sequential sensor data. Your main task will be to identify unusual patterns or faults through data modeling and visualization. This internship will provide you with a real-world opportunity to work on machine learning pipelines and understand both supervised and unsupervised approaches to anomaly detection. During this phase, you will focus on offline/static modeling using historical sensor data in tabular and time-series formats. Your primary objectives will include analyzing sensor datasets representing various operational scenarios, applying and evaluating supervised classification models, transitioning into unsupervised anomaly detection approaches, visualizing insights, and documenting findings for technical and non-technical audiences. Your key responsibilities will involve performing data preprocessing tasks such as cleaning, encoding, normalization, and feature engineering. Additionally, you will be required to train and evaluate classification models using Artificial Neural Networks (ANN) and Long Short-Term Memory (LSTM) models for sequence-based classification. You will also explore and implement unsupervised anomaly detection techniques like Isolation Forest, One-Class SVM, and Z-score or IQR-based statistical methods. Analyzing and visualizing model outputs using confusion matrices, anomaly heatmaps, and time-series plots will also be part of your responsibilities. Optionally, you may also be tasked with building a lightweight dashboard (e.g., using Streamlit) to present findings. TechnoExcel is the leading training and consulting company in Hyderabad offering data analytics solutions.,

As an AI Engineer at Armada, you will be part of a cutting-edge edge computing startup dedicated to providing advanced technology infrastructure to remote areas with limited connectivity and cloud infrastructure. Your role will involve harnessing the power of AI to revolutionize operations and enhance lives in some of the most isolated regions globally. You will have the opportunity to work on a diverse array of AI and ML challenges on a global scale, from the mines of Australia to the oil fields of Northern Canada and the coffee plantations of Colombia. Ideal candidates will be passionate about AI and possess expertise in machine learning, deep learning, and real-time computer vision techniques. Your responsibilities will include translating business requirements into AI/ML model requirements, preparing and evaluating datasets, building models using state-of-the-art algorithms such as transformers, testing and benchmarking model quality, and deploying models in production environments. Additionally, you will collaborate with customers and internal teams to refine model quality and establish continuous learning pipelines. To qualify for this role, you should hold a BS or MS degree in computer science or a related technical field, have at least 5 years of software development experience with proficiency in Python, Java, or C/C++, and possess hands-on expertise in machine learning techniques and algorithms. Experience with deep learning frameworks such as PyTorch and TensorFlow, as well as familiarity with containers and modular software design, is essential. Preferred qualifications include experience in building software for autonomous systems, producing computationally efficient software for real-time applications, and a background in container platforms like Kubernetes. Strong analytical, time-management, and communication skills are also highly valued. If you are a self-driven individual with a passion for cutting-edge AI technologies and a desire to tackle challenging AI and ML problems, Armada offers a dynamic environment where you can contribute to the development of high-performance computing solutions for various industries. Join us in bridging the digital divide and empowering AI systems to interact with the real world seamlessly and securely. In return, Armada offers a competitive base salary and equity options for India-based candidates, providing an opportunity to share in the success and growth of the company. If you are a go-getter with a growth mindset, a detail-oriented problem-solver, and a collaborative team player who thrives in a fast-paced environment, we want to hear from you. Apply now and be part of our mission to revolutionize edge computing with AI.,

As a Data Science Manager in the Research and Development (R&D) team at our organization, you will play a crucial role in driving innovation through advanced machine learning and AI algorithms. Your primary responsibility will involve conducting applied research, development, and validation of cutting-edge algorithms to address complex real-world problems on a large scale. You will collaborate closely with the product team to gain insights into business challenges and product objectives, enabling you to devise creative algorithmic solutions. Your role will entail creating prototypes and demonstrations to validate new ideas and transform research findings into practical innovations by collaborating with AI Engineers and software engineers. In addition, you will be responsible for formulating and executing research plans, carrying out experiments, documenting and consolidating results, and potentially publishing your work. It will also be essential for you to safeguard intellectual property resulting from R&D endeavors by working with relevant teams and external partners. Furthermore, part of your role will involve mentoring junior staff to ensure adherence to established procedures and collaborating with various stakeholders, academic/research partners, and fellow researchers to deliver tangible outcomes. To excel in this position, you are required to possess a strong foundation in computer science principles and proficient skills in analyzing and designing AI/Machine learning algorithms. Practical experience in several key areas such as supervised and unsupervised machine learning, reinforcement learning, deep learning, knowledge-based systems, evolutionary computing, probabilistic graphical models, among others, is essential. You should also be adept in at least one programming language and have hands-on experience in implementing AI/machine learning algorithms using Python or R. Familiarity with tools, frameworks, and libraries like Jupyter/Zeppelin, scikit-learn, matplotlib, pandas, Tensorflow, Keras, Apache Spark, etc., will be advantageous. Ideally, you should have at least 2-5 years of applied research experience in solving real-world problems using AI/Machine Learning techniques. Additionally, having a publication in a reputable conference or journal related to AI/Machine Learning or holding patents in the field would be beneficial. Experience in contributing to open-source projects within the AI/Machine Learning domain will be considered a strong asset. If you are excited about this challenging opportunity, please refer to the Job Code DSM_TVM for the position based in Trivandrum. For further details, feel free to reach out to us at recruitment@flytxt.com.,

As an experienced Machine Learning Engineer with 5 to 7 years of experience in Pune, you will play a crucial role in developing, training, and fine-tuning Machine Learning models for AI/ML applications. Your responsibilities will include designing and implementing data pipelines for data processing, model training, and inference. You will be tasked with deploying models using MLOps and integrating them with cloud infrastructure. Collaboration with product managers and designers to conceptualize AI-driven features will be an essential part of your role. Additionally, you will be expected to research and implement various ML and AI techniques to improve performance. To excel in this position, you should have proficiency in Python and ML frameworks such as Scikit-learn, XGBoost, TensorFlow, and PyTorch. Experience with SQL and ETL data pipelines, including data processing and feature engineering, is required. Familiarity with Docker and container-based deployments for creating cloud-agnostic products is essential. A strong understanding of AI and Machine Learning concepts, including Supervised Learning, Unsupervised Learning, Deep Learning, and Reinforcement Learning, is crucial. Knowledge of at least one cloud platform (AWS, Azure, GCP) and ML deployment strategies, preferably Azure, is expected. Exposure to LLMs (e.g., OpenAI, Hugging Face, Mistral) and foundation models will be beneficial, along with an understanding of various Statistical models.,

As a Senior Data Scientist with 5+ years of experience, you will be responsible for designing and implementing models, mining data for insights, and interpreting complex data structures to drive business decision-making. Your expertise in machine learning, including areas such as NLP, Machine vision, and Time series, will be essential in this role. You will be expected to have strong skills in Model Tuning, Model Validation, Supervised and Unsupervised Learning, and hands-on experience with model development, data preparation, training, and inference-ready deployment of models. Your proficiency in descriptive and inferential statistics, hypothesis testing, and data analysis will help in developing code for reproducible analysis of data. Experience with AWS services like Sagemaker, Lambda, Glue, Step functions, and EC2 is necessary, along with knowledge of Databricks, Anaconda distribution, and similar data science code development and deployment IDEs. Your familiarity with ML algorithms related to time-series, natural language processing, optimization, object detection, topic modeling, clustering, and regression analysis will be highly valued. You should have expertise in Hive/Impala, Spark, Python, Pandas, Keras, SKLearn, StatsModels, Tensorflow, and PyTorch. End-to-end model deployment and production experience of at least 1 year is required, along with a good understanding of Model Deployment in Azure ML platform, Anaconda Enterprise, or AWS Sagemaker. Basic knowledge of deep learning algorithms such as MaskedCNN, YOLO, and familiarity with Visualization and analytics/Reporting Tools like Power BI, Tableau, and Alteryx will be considered advantageous for this role.,

You will be combining your expertise in mathematics, statistics, computer science, and domain knowledge to create AIML models that can effectively address various business challenges. Your role will involve collaborating closely with the AI Technical Manager, GCC Petro technical professionals, and data engineers to integrate these models into the business framework. You will be responsible for identifying and framing opportunities to apply advanced analytics modeling and related technologies to data, thereby helping businesses gain insight, improve decision-making, workflow, and automation. In this position, you will need to understand and communicate the value of proposed opportunities with team members and other stakeholders. Identifying the necessary data and appropriate technology to solve the identified business challenges will be a crucial aspect of your responsibilities. You will also be involved in cleaning data, developing, and testing models, as well as establishing the life cycle management process for these models. Additionally, you will provide technical mentoring in modeling and analytics technologies, the specifics of the modeling process, and general consulting skills. Driving innovation in AIML to enhance capabilities in data-driven decision-making will be a key focus area. You are expected to align with the team on shared goals and outcomes, recognize others" contributions, work collaboratively, seek diverse perspectives, and take actions to develop yourself and others beyond existing skill sets. Furthermore, you should encourage innovative ideas, adapt to change and changing technologies, and effectively understand and communicate data insights and model behaviors to stakeholders with varying levels of technical expertise. **Required Qualifications:** - Minimum 5 years of experience in designing and developing AIML models and/or various optimization algorithms (5 to 9 years of experience) - Solid foundation in mathematics, probability, and statistics with demonstrated depth of knowledge and experience in advanced analytics and data science methodologies (e.g., supervised and unsupervised learning, statistics, data science model development) - Proficiency in Python and working knowledge of cloud AIML services; Azure Machine Learning and Databricks preferred - Domain knowledge relevant to the energy sector and working knowledge of the Oil and Gas value chain (e.g., upstream, midstream, or downstream) and associated business workflows - Proven ability to frame data science opportunities, leverage standard foundational tools and Azure services to perform exploratory data analysis for purposes of data cleaning and discovery, visualize data, and identify actions to reach needed results - Ability to quickly assess the current state and apply technical concepts across cross-functional business workflows - Experience with driving successful execution deliverables and accountabilities to meet quality and schedule goals - Ability to translate complex data into actionable insights that drive business value - Demonstrated ability to engage and establish collaborative relationships both inside and outside the immediate workgroup at various organizational levels across functional and geographic boundaries to achieve desired outcomes - Demonstrated ability to adjust behavior based on feedback and provide feedback to others - Team-oriented mindset with effective communication skills and the ability to work collaboratively - Strong problem-solving skills and attention to detail - Excellent communication and collaboration skills,

Are you our Type Monotype, named "One of the Most Innovative Companies in Design" by Fast Company, is dedicated to bringing brands to life through type and technology that consumers engage with daily. With a rich legacy spanning centuries, Monotype boasts a library featuring renowned typefaces like Helvetica, Futura, and Times New Roman, among others. Additionally, Monotype offers a pioneering service that enhances access to fonts for creative professionals, facilitating their discovery, licensing, and utilization in today's digital landscape. Collaborating with major global brands and individual creatives, Monotype provides a diverse range of solutions to streamline the design of captivating brand experiences. Monotype Solutions India serves as a strategic center of excellence for Monotype, recognized as a certified Great Place to Work for three consecutive years. The center's rapid growth encompasses various domains such as Product Development, Product Management, Experience Design, User Research, Market Intelligence, AI and Machine Learning research, Innovation, Customer Success, Enterprise Business Solutions, and Sales. Headquartered in the Boston area with a global presence across 4 continents, Monotype stands as the world's leading font company, trusted by the top brands worldwide and acknowledged as One of the Most Innovative Companies in Design by Fast Company. Monotype is a pioneering technology company at the forefront of AI innovation in fonts. We are currently seeking a motivated and curious AI/ML Engineer to join our dynamic team. As an AI/ML Engineer, you will be instrumental in designing and implementing state-of-the-art AI/ML solutions to address real-world challenges. This position is based in the Delhi NCR area. **What you will be doing:** - Designing, developing, and testing AI/ML models using supervised and unsupervised learning techniques. - Preparing and pre-processing data for model training and evaluation. - Collaborating with data scientists and engineers to define project requirements and success metrics. - Deploying and monitoring models in production environments. - Staying updated with the latest advancements in AI/ML research and development. **What we are looking for:** - Bachelor's degree in computer science, mathematics, statistics, or a related field. - Strong grasp of machine learning concepts, algorithms, and techniques. - Knowledge or understanding of deep learning frameworks (TensorFlow, PyTorch) and programming languages (Python, R). - Familiarity with data wrangling and manipulation tools (pandas, NumPy). - Excellent communication and collaboration skills. - A keen interest in continuous learning and exploring new technologies. **Preferred Skills:** - Strong understanding of computer vision, natural language processing, and other AI-related domains. - Knowledge or understanding of generative AI models, particularly Stable Diffusion. - Published research papers or contributions to the AI/ML community are advantageous. - Knowledge or understanding of building and deploying ML pipelines. Monotype is expanding globally, and proficiency in one or more of the following languages (German, Japanese, French, Spanish) is desirable but not mandatory for this role.,

About The Role 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 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. Qualification Master of Engineering,Masters in Business Economics

Job ID: 21570 Location: Chennai, IN Area of interest: Technology Job type: Regular Employee Work style: Office Working Opening date: 27 Mar 2025 Job Summary Experience in applying machine learning techniques, Natural Language Processing or Computer Vision using TensorFlow, Pytorch Strong analytical and problem-solving skills Solid software engineering skills across multiple languages including but not limited to Java or Python, C/C++ Build and deploy end to end ML models and leverage metrics to support predictions, recommendations, search, and growth strategies Deep understanding of ML techniques such as: classification, clustering, deep learning, optimization methods, supervised and unsupervised techniques Proven ability to apply, debug, and develop machine learning models Establish scalable, efficient, automated processes for data analyses, model development, validation and implementation, Choose suitable DL algorithms, software, hardware and suggest integration methods. Ensure AI ML solutions are developed, and validations are performed in accordance with Responsible AI guidelines & Standards To closely monitor the Model Performance and ensure Model Improvements are done post Project Delivery Coach and mentor our team as we build scalable machine learning solutions Strong communication skills and an easy-going attitude Oversee development and implementation of assigned programs and guide teammates Carry out testing procedures to ensure systems are running smoothly Ensure that systems satisfy quality standards and procedures Build and manage strong relationships with stakeholders and various teams internally and externally, Provide direction and structure to assigned projects activities, establishing clear, precise goals, objectives and timeframes, run Project Governance calls with senior Stakeholders Strategy As the Squad Lead of AI ML Delivery team, the candidate is expected to lead the squad Delivery for AIML. Business Understand the Business requirement and execute the ML solutioning and ensue the delivery commitments are delivered on time and schedule. Processes Design and Delivery of AI ML Use cases RAI, Security & Governance Model Validation & Improvements Stakeholder Management People & Talent Manage the team in terms of project assignments and deadlines Manage a team dedicated for reviewing models related unstructured and structured data. Hire, nurture talent as required. Key Responsibilities Risk Management Ownership of the delivery, highlighting various risks on a timely manner to the stakeholders. Identifying proper remediation plan for the risks with proper risk roadmap. Governance Awareness and understanding of the regulatory framework, in which the Group operates, and the regulatory requirements and expectations relevant to the role. Regulatory & Business Conduct Display exemplary conduct and live by the Groups Values and Code of Conduct. Take personal responsibility for embedding the highest standards of ethics, including regulatory and business conduct, across Standard Chartered Bank. This includes understanding and ensuring compliance with, in letter and spirit, all applicable laws, regulations, guidelines and the Group Code of Conduct. Lead the team to achieve the outcomes set out in the Banks Conduct Principles: [Fair Outcomes for Clients; Effective Financial Markets; Financial Crime Compliance; The Right Environment.] * Effectively and collaboratively identify, escalate, mitigate and resolve risk, conduct and compliance matters. [Insert local regulator e.g. PRA/FCA prescribed responsibilities and Rationale for allocation]. [Where relevant - Additionally, for subsidiaries or relevant non -subsidiaries] Serve as a Director of the Board of [insert name of entities] Exercise authorities delegated by the Board of Directors and act in accordance with Articles of Association (or equivalent) Key stakeholders Business Stakeholders AIML Engineering Team AIML Product Team Product Enablement Team SCB Infrastructure Team Interfacing Program Team Skills and Experience Use NLP, Vision and ML techniques to bring order to unstructured data Experience in extracting signal from noise in large unstructured datasets a plus Work within the Engineering Team to design, code, train, test, deploy and iterate on enterprise scale machine learning systems Work alongside an excellent, cross-functional team across Engineering, Product and Design create solutions and try various algorithms to solve the problem. Stakeholder Management Qualifications Masters with specialisation in Technology with certification in AI and ML 5-12 years relevant of Hands-on Experience in developing and delivering AI solutions About Standard Chartered We're an international bank, nimble enough to act, big enough for impact. For more than 170 years, we've worked to make a positive difference for our clients, communities, and each other. We question the status quo, love a challenge and enjoy finding new opportunities to grow and do better than before. If you're looking for a career with purpose and you want to work for a bank making a difference, we want to hear from you. You can count on us to celebrate your unique talents and we can't wait to see the talents you can bring us. Our purpose, to drive commerce and prosperity through our unique diversity, together with our brand promise, to be here for good are achieved by how we each live our valued behaviours. When you work with us, you'll see how we value difference and advocate inclusion. Together we: Do the right thing and are assertive, challenge one another, and live with integrity, while putting the client at the heart of what we do Never settle, continuously striving to improve and innovate, keeping things simple and learning from doing well, and not so well Are better together, we can be ourselves, be inclusive, see more good in others, and work collectively to build for the long term What we offer Core bank funding for retirement savings, medical and life insurance, with flexible and voluntary benefits available in some locations. Time-off including annual leave, parental/maternity (20 weeks), sabbatical (12 months maximum) and volunteering leave (3 days), along with minimum global standards for annual and public holiday, which is combined to 30 days minimum. Flexible working options based around home and office locations, with flexible working patterns. Proactive wellbeing support through Unmind, a market-leading digital wellbeing platform, development courses for resilience and other human skills, global Employee Assistance Programme, sick leave, mental health first-aiders and all sorts of self-help toolkits A continuous learning culture to support your growth, with opportunities to reskill and upskill and access to physical, virtual and digital learning. Being part of an inclusive and values driven organisation, one that embraces and celebrates our unique diversity, across our teams, business functions and geographies - everyone feels respected and can realise their full potential. www.sc.com/careers,

At EY, you'll have the chance to build a career as unique as you are, with the global scale, support, inclusive culture, and technology to become the best version of you. Your unique voice and perspective are essential in helping EY become even better. Join us to create an exceptional experience for yourself and contribute towards building a better working world for all. As a part of the EY GDS AI and Data team, you will assist clients in solving complex business challenges using data and technology. By delving deep into data, you will extract maximum value and identify opportunities in various sectors such as Banking, Insurance, Manufacturing, Healthcare, Retail, Auto, Supply Chain, and Finance. Your technical skills will include proficiency in Statistical Programming Languages like Python and R, familiarity with Libraries & Frameworks such as Pandas, NumPy, Scikit-learn, and more. You should be adept in Data Manipulation Tools like SQL and Excel, and experienced in Data Visualization Tools like Matplotlib, Seaborn, ggplot2. Your expertise should cover Machine Learning Techniques including supervised and unsupervised learning, as well as model evaluation techniques like cross-validation and ROC curves. To excel in this role, you should possess 5-7 years of experience in constructing statistical forecast models specifically tailored for the pharma industry. A deep understanding of patient flows and treatment journeys across Oncology and Non-Oncology tasks is crucial for success. We are looking for individuals who bring a combination of commercial acumen, technical expertise, and a willingness to learn in a dynamic environment. Your role at EY will offer exposure to diverse and meaningful projects, coupled with education and coaching for personal development. You will have the autonomy to drive your growth through an individual progression plan, taking on challenging and stimulating tasks in a collaborative and knowledge-sharing environment. Working at EY provides a platform for continuous learning and growth, with opportunities to enhance your skills and advance your career. You will receive support, coaching, and feedback from engaging colleagues, along with the freedom and flexibility to shape your role according to your preferences. EY is a global leader in assurance, tax, transaction, and advisory services, committed to building a better working world. Our culture emphasizes training, opportunities, and creative freedom to drive positive change. Join us in our mission to create long-term value for clients, people, and society, and to instill trust in the capital markets. At EY, you will be part of diverse teams across 150 countries, leveraging data and technology to provide assurance and support clients in growth, transformation, and operations. Through our work in assurance, consulting, law, strategy, tax, and transactions, we strive to address the complex challenges of today's world by asking better questions and finding innovative solutions.,

Staff Engineer/Tech Lead AI/ML [ Natural Language Processing, Transformers, Gen AI, LLM, Neural Networks] The Opportunity As a Staff Engineer (MTS-6) , you will own the architecture and AI/ML systems that power both log and metrics analysis , enabling automated diagnostics and reducing triage time for QA failures, regression runs, and customer issues. Youll also help define and drive the central AI charter at Nutanix, building reusable components, model infrastructure, and scalable ML services. About the Team The Panacea team has a passionate set of engineers across India and US office. We move fast, collaborate closely, and care deeply about quality and ownership. Our mission is to deliver AI/ML-powered developer productivity tools that solve real engineering and support pain points at scale. Why Join Us Build AI-first observability tools that redefine how engineers triage and troubleshoot. Own systems that reduce hours of manual work in engineering and SRE workflows . Collaborate with a tight-knit team of high-ownership engineers who are passionate about impact and innovation. Hybrid work model that supports flexibility and deep focus. Help shape the central AI charter at Nutanix and influence future AI products across the company. Your Role AI-Powered Observability Platform : Own the vision, architecture, and delivery of Panaceas ML-based log and metrics analyzer that reduces triage time and improves engineering efficiency. AI/ML-powered Log Analyzer Tool : Use deep learning (e.g., ModernBERT ) to represent log messages, detect anomalies, group patterns, and surface actionable insights to users. Metrics Anomaly Detection Engine : Build robust ML models to detect anomalies in time-series metrics like CPU, memory, disk I/O, network traffic, service health , and moreautomatically identifying performance degradation or system regressions across distributed environments. Auto-RCA Engine : Combine log and metrics signals with graph-based correlation and LLM-powered summarization to automatically diagnose the root cause of system failures. Feedback Loop & Continuous Learning : Build infrastructure for incorporating user feedback to continuously retrain and improve anomaly detection systems. LLM Integration : Integrate LLMs for user queries, problem summarization, anomaly explanation, and contextual recommendations. Central AI Charter : Contribute to Nutanixs foundational AI platform by defining shared tooling, datasets, governance, and reusable ML components across products. Responsibilities Architect and scale ML pipelines for real-time and batch-based anomaly detection in both logs and time-series metrics. Build and fine-tune ModernBERT and other transformer-based models for log understanding, anomaly classification, and summarization. Develop unsupervised and semi-supervised ML models for detecting anomalies in system metrics (CPU, memory, network throughput, latency, etc.). Implement correlation models to connect anomalies across logs and metrics to form a cohesive RCA narrative. Own the entire ML lifecycle: data ingestion, feature extraction, model training, evaluation, deployment, and monitoring. Build explainable AI systems that increase adoption and trust within engineering, QA, and support teams. Collaborate with cross-functional stakeholders (SRE, QA, Dev) to deeply understand pain points and translate them into intelligent tooling. Drive technical excellence through code and design reviews, mentoring, and setting engineering best practices. What You Will Bring Educational Background : B.Tech/M.Tech in Computer Science, Machine Learning, AI, or related fields. Experience : 12+ years of engineering experience , including designing , developing and deploying AI/ML systems at scale. ML Expertise : Strong in time-series anomaly detection, statistical modeling, supervised/unsupervised learning. Experience building ML models for metrics data (CPU, memory, IOPS, network, etc.) using models like Isolation Forest, Prophet, LSTM, or deep autoencoders. Expertise in NLP using ModernBERT, BERT, or log classification, clustering, and summarization. Experience with LLMs for downstream tasks like summarization, root cause reasoning, or intelligent Q&A. Engineering Skills : Strong Python background, hands-on with ML libraries (PyTorch, TensorFlow, Scikit-learn), time-series frameworks, and MLOps tools. Familiar with data pipelines and serving models. Observability Knowledge : Hands-on with logs, metrics, traces, and popular monitoring tools (e.g., Prometheus, Grafana, ELK). Leadership : Ability to independently drive projects from requirements to delivery, mentor junior engineers, and deliver business impact. Work Arrangement Hybrid: This role operates in a hybrid capacity, blending the benefits of remote work with the advantages of in-person collaboration. For most roles, that will mean coming into an office a minimum of 2 - 3 days per week, however certain roles and/or teams may require more frequent in-office presence. Additional team-specific guidance and norms will be provided by your manager.

Job Role: As a Senior Data Scientist, you will be responsible for designing, developing and productionizing of ML-driven solutions to business problems. You will work closely with local and onshore team of data scientists and stakeholders to understand their needs and pain points, and then translate those into actionable data science projects. Your primary focus will be statistical data analyses and helping build high-quality predictive models integrated with our products. The ideal candidate is an experienced data wrangler with a deep understanding of data science principles and a proven track record of delivering ML-driven solutions. S/he will effectively communicate complex technical concepts to technical and non-technical audiences. Key Responsibilities: Plan, productionize, and document scalable Data Science solutions Understand the business problem from stakeholders and convert it to actionable tasks Driven to create in-depth Exploratory Data Analysis and Feature Engineering; experienced with ML Ops Adept at standard and latest ML algorithms and Model explainability. Knowledge about causal inference is a great to-have Help mentor and guide Data Scientists Qualifications - Internal Key Requirements: Experience : At least 8 years of relevant experience Education: Bachelors or masters degree in computer science or mathematics, Statistics or a related field. PhD with lesser experience is welcome. Required Skills: Proficient in ML models across supervised and unsupervised learning, along with knowledge of Deep Learning models using TensorFlow / PyTorch Experienced in Natural Language Processing with focus on Transformer models Experienced in using Generative AI. At least one project implementation is expected Knowledge in MLOps is recommended Extensive coding experience in Python (and R) as well as scripting in SQL Visualization of outputs, using Tableau/ Power BI/ Streamlit, along with crisp communication Strong ability to assess the business problem and suggest applicable data science solutions Great at presenting and explaining model results to any kind of audience Personal Attributes: Ability to adapt and work with a distributed team Ability to manage multiple initiatives Ability to work with ambiguous requirements, seek clarity and manage risks. Ability to communicate complex concepts in a simple yet intelligent way

Job Title - S&C Global Network - AI - Retail - Consultant - Retail Specialized Data Scientist/ 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) Additional Information: - Qualification Experience: Minimum 3 year(s) of experience is required Educational Qualification: Bachelors or Master's degree in Data Science, Statistics, Computer Science, Mathematics, or a related field.