3498 Data Scientist Jobs - Page 35

Job Description: 1. Be a hands on problem solver with consultative approach, who can apply Machine Learning & Deep Learning algorithms to solve business challenges a. Use the knowledge of wide variety of AI/ML techniques and algorithms to find what combinations of these techniques can best solve the problem b. Improve Model accuracy to deliver greater business impact c. Estimate business impact due to deployment of model 2. Work with the domain/customer teams to understand business context , data dictionaries and apply relevant Deep Learning solution for the given business challenge 3. Working with tools and scripts for sufficiently pre-processing the data & feature engineering for model development – Python / R / SQL / Cloud data pipelines 4. Design , develop & deploy Deep learning models using Tensorflow / Pytorch 5. Experience in using Deep learning models with text, speech, image and video data a. Design & Develop NLP models for Text Classification, Custom Entity Recognition, Relationship extraction, Text Summarization, Topic Modeling, Reasoning over Knowledge Graphs, Semantic Search using NLP tools like Spacy and opensource Tensorflow, Pytorch, etc b. Design and develop Image recognition & video analysis models using Deep learning algorithms and open source tools like OpenCV c. Knowledge of State of the art Deep learning algorithms 6. Optimize and tune Deep Learnings model for best possible accuracy 7. Use visualization tools/modules to be able to explore and analyze outcomes & for Model validation eg: using Power BI / Tableau 8. Work with application teams, in deploying models on cloud as a service or on-prem a. Deployment of models in Test / Control framework for tracking b. Build CI/CD pipelines for ML model deployment 9. Integrating AI&ML models with other applications using REST APIs and other connector technologies 10. Constantly upskill and update with the latest techniques and best practices. Write white papers and create demonstrable assets to summarize the AIML work and its impact.

Job Description This role is responsible for managing the client expectations. Strategize with various stakeholders to meet customer requirements. KEY RESPONSIBILITIES Data Science: Develop machine learning models to support recommendation systems and NLP projects; provide actionable insights for product and service optimization. Data Engineering: Build and maintain scalable ETL pipelines, optimize data storage solutions (data lakes, columnar formats), and ensure data accuracy for analytics. Data Analysis and Insight Generation: Skilled in analyzing complex datasets to uncover trends and patterns; generate and present insights that drive strategic decisions and enhance client services. Stakeholder Collaboration: Work with product and service teams to understand data needs and translate them into technical solutions. Working Relationships Reporting to Project Manager External Stakeholders Clients Skills/ Competencies Required Technical Skills Proficiency with Python (Pandas, NumPy), SQL, and Java. Experience with LLMs, LangChain, and Generative AI technologies. Familiarity with ML frameworks (TensorFlow, PyTorch) and data engineering tools (Spark, Kafka). Microservices, CI CD, ML Strong data analysis skills and ability to present findings to both technical and non-technical stakeholders. Proficient understanding of key data engineering concepts, such as data lakes, columnar formats, ETL tools, and BI tools. Knowledge in Machine Learning, NLP, Recommender systems, personalization, Segmentation, microservices architecture and API development. Ability to adapt to a fast-paced, dynamic work environment and learn new technologies quickly. Soft Skills Work in a team/ Independently. Excellent Written Verbal Communication Skills Solid critical thinking and questioning skills. High degree of flexibility - willing to fill in the gaps rather than relying on others Strong communication skills, especially in presenting data insights. Flexibility, problem-solving, and a proactive approach in a fast-paced environment

This is a unique opportunity to apply your skills and contribute to impactful global business initiatives. As an Applied AI ML Lead - Data Scientist- Vice President at JPMorgan Chase within the Commercial & Investment Banks Global Banking team, you ll leverage your technical expertise and leadership abilities to support AI innovation. You should have deep knowledge of AI/ML and effective leadership to inspire the team, align cross-functional stakeholders, engage senior leadership, and drive business results. Job Responsibilities Lead a local AI/ML team with accountability and engagement into a global organization. Mentor and guide team members, fostering an inclusive culture with a growth mindset. Collaborate on setting the technical vision and executing strategic roadmaps to drive AI innovation. Deliver AI/ML projects through our ML development life cycle using Agile methodology. Help transform business requirements into AI/ML specifications, define milestones, and ensure timely delivery. Work with product and business teams to define goals and roadmaps. Maintain alignment with cross-functional stakeholders. Exercise sound technical judgment, anticipate bottlenecks, escalate effectively, and balance business needs versus technical constraints. Design experiments, establish mathematical intuitions, implement algorithms, execute test cases, validate results and productionize highly performant, scalable, trustworthy and often explainable solution. Mentor Junior Machine Learning associates in delivering successful projects and building successful career in the firm. Participate and contribute back to firmwide Machine Learning communities through patenting, publications and speaking engagements. Evaluate and design effective processes and systems to facilitate communication, improve execution, and ensure accountability. Required qualifications, capabilities, and skills 14+ years (BS) or 8+ (MS) or 5+ (PhD) years of relevant in Computer Science, Data Science, Information Systems, Statistics, Mathematics or equivalent experience. Track record of managing AI/ML or software development teams. Experience as a hands-on practitioner developing production AI/ML solutions. Deep knowledge and experience in machine learning and artificial intelligence. Ability to set teams up for success in speed and quality, and design effective metrics and hypotheses. Expert in at least one of the following areas Natural Language Processing, Knowledge Graph, Computer Vision, Speech Recognition, Reinforcement Learning, Ranking and Recommendation, or Time Series Analysis. Deep knowledge in Data structures, Algorithms, Machine Learning, Data Mining, Information Retrieval, Statistics. Demonstrated expertise in machine learning frameworks Tensorflow, Pytorch, pyG, Keras, MXNet, Scikit-Learn. Strong programming knowledge of python, spark; Strong grasp on vector operations using numpy, scipy; Strong grasp on distributed computation using Multithreading, Multi GPUs, Dask, Ray, Polars etc. Familiarity in AWS Cloud services such as EMR, Sagemaker etc. , Strong people management and team-building skills. Ability to coach and grow talent, foster a healthy engineering culture, and attract/retain talent. Ability to build a diverse, inclusive, and high-performing team. Ability to inspire collaboration among teams composed of both technical and non-technical members. Effective communication, solid negotiation skills, and strong leadership. This is a unique opportunity to apply your skills and contribute to impactful global business initiatives. As an Applied AI ML Lead - Data Scientist- Vice President at JPMorgan Chase within the Commercial & Investment Banks Global Banking team, you ll leverage your technical expertise and leadership abilities to support AI innovation. You should have deep knowledge of AI/ML and effective leadership to inspire the team, align cross-functional stakeholders, engage senior leadership, and drive business results. Job Responsibilities Lead a local AI/ML team with accountability and engagement into a global organization. Mentor and guide team members, fostering an inclusive culture with a growth mindset. Collaborate on setting the technical vision and executing strategic roadmaps to drive AI innovation. Deliver AI/ML projects through our ML development life cycle using Agile methodology. Help transform business requirements into AI/ML specifications, define milestones, and ensure timely delivery. Work with product and business teams to define goals and roadmaps. Maintain alignment with cross-functional stakeholders. Exercise sound technical judgment, anticipate bottlenecks, escalate effectively, and balance business needs versus technical constraints. Design experiments, establish mathematical intuitions, implement algorithms, execute test cases, validate results and productionize highly performant, scalable, trustworthy and often explainable solution. Mentor Junior Machine Learning associates in delivering successful projects and building successful career in the firm. Participate and contribute back to firmwide Machine Learning communities through patenting, publications and speaking engagements. Evaluate and design effective processes and systems to facilitate communication, improve execution, and ensure accountability. Required qualifications, capabilities, and skills 14+ years (BS) or 8+ (MS) or 5+ (PhD) years of relevant in Computer Science, Data Science, Information Systems, Statistics, Mathematics or equivalent experience. Track record of managing AI/ML or software development teams. Experience as a hands-on practitioner developing production AI/ML solutions. Deep knowledge and experience in machine learning and artificial intelligence. Ability to set teams up for success in speed and quality, and design effective metrics and hypotheses. Expert in at least one of the following areas Natural Language Processing, Knowledge Graph, Computer Vision, Speech Recognition, Reinforcement Learning, Ranking and Recommendation, or Time Series Analysis. Deep knowledge in Data structures, Algorithms, Machine Learning, Data Mining, Information Retrieval, Statistics. Demonstrated expertise in machine learning frameworks Tensorflow, Pytorch, pyG, Keras, MXNet, Scikit-Learn. Strong programming knowledge of python, spark; Strong grasp on vector operations using numpy, scipy; Strong grasp on distributed computation using Multithreading, Multi GPUs, Dask, Ray, Polars etc. Familiarity in AWS Cloud services such as EMR, Sagemaker etc. , Strong people management and team-building skills. Ability to coach and grow talent, foster a healthy engineering culture, and attract/retain talent. Ability to build a diverse, inclusive, and high-performing team. Ability to inspire collaboration among teams composed of both technical and non-technical members. Effective communication, solid negotiation skills, and strong leadership.

We are looking to add an experienced and enthusiastic Lead Data Scientist to our Jet2 Data Science team in India. Reporting to the Data Science Delivery Manager , the Lead Data Scientist is a key appointment to the Data Science Team , with responsibility for executing the data science strategy and realising the benefits we can bring to the business by combining insights gained from multiple large data sources with the contextual understanding and experience of our colleagues across the business. In this exciting role, y ou will be joining an established team of 40+ Data Science professionals , based across our UK and India bases , who are using data science to understand, automate and optimise key manual business processes, inform our marketing strategy, and ass ess product development and revenue opportunities and optimise operational costs. As Lead Data Scientist, y ou will have strong experience in leading data science projects and creating machine learning models and be able t o confidently communicate with and enthuse key business stakeholders . Roles and Responsibilities A typical day in your role at Jet2TT: A lead data scientist would lead a team of data science team Lead will be responsible for delivering & managing day-to-day activities The successful candidate will be highly numerate with a statistical background , experienced in using R, Python or similar statistical analysis package Y ou will be expected to work with internal teams across the business , to identify and collaborate with stakeholders across the wider group. Leading and coaching a group of Data Scientists , y ou will plan and execute the use of machine learning and statistical modelling tools suited to the identified initiative delivery or discovery problem identified . You will have strong ability to analyse the create d algorithms and models to understand how changes in metrics in one area of the business could impact other areas, and be able to communicate those analyses to key business stakeholders. You will identify efficiencies in the use of data across its lifecycle, reducing data redundancy, structuring data to ensure efficient use of time , and ensuring retained data/information provides value to the organisation and remains in-line with legitimate business and/or regulatory requirements. Your ability to rise above group think and see beyond the here and now is matched only by your intellectual curiosity. Strong SQL skills and the ability to create clear data visualisations in tools such as Tableau or Power BI will be essential . They will also have experience in developing and deploying predictive models using machine learning frameworks and worked with big data technologies. As we aim to realise the benefits of cloud technologies, some familiarity with cloud platforms like AWS for data science and storage would be desirable. You will be skilled in gathering data from multiple sources and in multiple formats with knowledge of data warehouse design, logical and physical database design and challenges posed by data quality. Qualifications, Skills and Experience (Candidate Requirements): Experience in leading small to mid-size data science team Minimum 7 years of experience in the industry & 4+ experience in data science Experience in building & deploying machine learning algorithms & detail knowledge on applied statistics Good understanding of various data architecture RDBMS, Datawarehouse & Big Data Experience of working with regions such as US, UK, Europe or Australia is a plus Liaise with the Data Engineers, Technology Leaders & Business Stakeholder Working knowledge of Agile framework is good to have Demonstrates willingness to learn Mentoring, coaching team members Strong delivery performance, working on complex solutions in a fast-paced environment

We use cookies to offer you the best possible website experience. Your cookie preferences will be stored in your browser s local storage. This includes cookies necessary for the websites operation. Additionally, you can freely decide and change any time whether you accept cookies or choose to opt out of cookies to improve websites performance, as well as cookies used to display content tailored to your interests. Your experience of the site and the services we are able to offer may be impacted if you do not accept all cookies. Modify Cookie Preferences Reject All Cookies Accept All Cookies Search by Keyword Full / Part Time Select how often (in days) to receive an alert: Select how often (in days) to receive an alert: We are seeking a Data Scientist with strong manufacturing domain knowledge to turn raw OT and IT data into actionable insights. You will explore data patterns, identify value drivers, and prototype use cases like yield improvement, quality prediction, or energy optimization. This role requires strong collaboration with plant engineers and digital product owners to ensure data science solutions are practical and measurable. Key job function 1)Analyze data from OT (sensors, PLCs, SCADA) and IT (MES, ERP) systems 2) Build models for predictive quality, maintenance, and process analytics 3) Prototype and test advanced analytics use cases in manufacturing settings 4) Work with engineers to validate results and co-develop improvements 5) Create compelling data stories and visuals for business impact using Power BI or Python 6) Partner with AI/ML specialists to prepare data and build training pipelines When you visit any website, it may store or retrieve information on your browser, mostly in the form of cookies. Because we respect your right to privacy, you can choose not to allow some types of cookies. However, blocking some types of cookies may impact your experience of the site and the services we are able to offer. These cookies are required to use this website and cant be turned off. Provider Description Enabled SAP as service provider We use the following session cookies, which are all required to enable the website to function: "route" is used for session stickiness "careerSiteCompanyId" is used to send the request to the correct data center "JSESSIONID" is placed on the visitors device during the session so the server can identify the visitor "Load balancer cookie" (actual cookie name may vary) prevents a visitor from bouncing from one instance to another Functional Cookies These cookies provide a better customer experience on this site, such as by remembering your login details, optimizing video performance, or providing us with information about how our site is used. You may freely choose to accept or decline these cookies at any time. Note that certain functionalities that these third-parties make available may be impacted if you do not accept these cookies. Advertising Cookies These cookies serve ads that are relevant to your interests. You may freely choose to accept or decline these cookies at any time. Note that certain functionality that these third parties make available may be impacted if you do not accept these cookies.

We are hiring a Data Scientist with knowledge of AI, NLP, and Deep Learning. You should know how to work with data, build ML models, and understand text. Experience with Python, and deep learning tools like TensorFlow is needed. Ai/Ml, Data Scientist, Deep Learning, Nlp

We are looking for a skilled Senior Data Scientist with expertise in NLP and Machine Learning to join our team at Harmony Data Integration Technologies. The ideal candidate will have a strong background in developing innovative data solutions and driving business growth through data-driven insights. Roles and Responsibility Design, develop, and deploy advanced NLP models to extract valuable insights from large datasets. Collaborate with cross-functional teams to identify business problems and develop data-driven solutions. Develop and maintain complex machine learning models using various algorithms and techniques. Work closely with stakeholders to understand business requirements and deliver high-quality results. Stay updated with industry trends and emerging technologies in NLP and machine learning. Lead the development of predictive analytics solutions to drive business growth. Job Requirements Strong proficiency in programming languages such as Python, R, or Java. Experience with NLP libraries such as NLTK, spaCy, or Stanford CoreNLP. Knowledge of machine learning frameworks such as scikit-learn, TensorFlow, or PyTorch. Excellent understanding of statistical concepts and data modeling techniques. Strong analytical and problem-solving skills with attention to detail. Ability to work collaboratively in a team environment and communicate complex ideas effectively.

About this role : In Gartner s Services Data Science team, we innovate the way our team helps clients receive value, so technology leaders will be able to make smarter decisions in a different way. We are searching for a talented associate data scientist to join our team. You will have access to the best facilities, technology and expertise within the industry and will work on challenging business problems. This is an excellent opportunity to be part of a new venture, in a start-up environment where you can truly develop your skill set and knowledge and bring impact to the team. What you ll do : Here is a sample of some initiatives that our associate data scientists work on Designing and implementing state of the art Large Language Model (LLM) based agents that seamlessly synthesize complex information and initiate important actions in a business workflow. Using NLP models and advanced Generative AI techniques to derive actionable insights from unstructured text data, such as call transcripts and emails. Evaluating the performance of the models, continuously optimizing them for better accuracy and relevance Building various recommendation tools like client interest predictor and personalized content recommenders to drive higher client value delivery Develop customer churn prediction models that proactively identify at-risk clients, leverage statistical and machine learning techniques to extract actionable insights from client retention data. Build tools to process structured and unstructured data Engineering features and signals to train ML model from diverse data collection Collaborate with cross-functional teams to integrate data science solutions into existing systems and user workflows, ensuring seamless data accessibility and usability. What you ll need : BS/MS/PhD in Computer Science or other technology, Math, Physics, Statistics or Economics (focus on Natural Language Processing, Information Retrieval a plus) 1+ years experience in data science methodologies as applied to live initiatives or software development 1+ years of experience in python coding and statistical analysis Working experience in several of the following: Prompt Engineering and working with LLMs Machine Learning and statistical techniques Data mining and recommendation systems Natural Language Processing and Information Retrieval Handling large volumes of data User behavior modeling What we offer : A collaborative, positive culture. You ll work with people who are as enthusiastic, smart and driven as you are. You ll be managed by the best too. Limitless growth and learning opportunities. We offer the excitement of a fast-paced entrepreneurial workplace and the professional growth opportunities of an established global organization.

We are looking for a highly motivated and talented Junior Data Scientist to join our team at AGR Knowledge Services Pvt Ltd. The ideal candidate will have 2-4 years of experience in the field. Roles and Responsibility Collaborate with cross-functional teams to design and develop data-driven solutions. Analyze complex data sets to identify trends and patterns, providing actionable insights. Develop and maintain databases, data systems, and data pipelines. Design and implement machine learning models and algorithms to solve business problems. Work closely with stakeholders to understand business needs and develop targeted solutions. Stay up-to-date with industry trends and emerging technologies in data science. Job Requirements Strong foundation in statistics, mathematics, and computer science. Proficiency in programming languages such as Python, R, or SAS. Experience with data analysis tools such as SQL, Excel, or Tableau. Knowledge of machine learning algorithms and deep learning techniques. Excellent communication and problem-solving skills. Ability to work in a fast-paced environment and meet deadlines.

Role Description As a Senior Data Science and Modeling Specialist at Incedo, you will be responsible for developing and deploying predictive models and machine learning algorithms to support business decision-making. You will work with data scientists, data engineers, and business analysts to understand business requirements and develop data-driven solutions. You will be skilled in programming languages such as Python or R and have experience in data science tools such as TensorFlow or Keras. You will be responsible for ensuring that models are accurate, efficient, and scalable. Roles & Responsibilities: Developing and implementing machine learning models and algorithms to solve complex business problems Conducting data analysis and modeling using statistical and data analysis tools Collaborating with other teams to ensure the consistency and integrity of data Providing guidance and mentorship to junior data science and modeling specialists Presenting findings and recommendations to stakeholders Technical Skills Skills Requirements: Proficiency in statistical analysis techniques such as regression analysis, hypothesis testing, or time-series analysis. Knowledge of machine learning algorithms and techniques such as supervised learning, unsupervised learning, or reinforcement learning. Experience with data wrangling and data cleaning techniques using tools such as Python, R, or SQL. Understanding of big data technologies such as Hadoop, Spark, or Hive. Must have excellent communication skills and be able to communicate complex technical information to non-technical stakeholders in a clear and concise manner. Must understand the company's long-term vision and align with it. Provide leadership, guidance, and support to team members, ensuring the successful completion of tasks, and promoting a positive work environment that fosters collaboration and productivity, taking responsibility of the whole team. Qualifications 4-6 years of work experience in relevant field B.Tech/B.E/M.Tech or MCA degree from a reputed university. Computer science background is preferred

Role Description : As a Software Engineer - Data Science and Modeling at Incedo, you will be responsible for developing and deploying predictive models and machine learning algorithms to support business decision-making. You will work with data scientists, data engineers, and business analysts to understand business requirements and develop data-driven solutions. You will be skilled in programming languages such as Python or R and have experience in data science tools such as TensorFlow or Keras. You will be responsible for ensuring that models are accurate, efficient, and scalable. Roles & Responsibilities: Developing and implementing machine learning models and algorithms to solve complex business problems Conducting data analysis and modeling using statistical and data analysis tools Collaborating with other teams to ensure the consistency and integrity of data Providing guidance and mentorship to junior data science and modeling specialists Presenting findings and recommendations to stakeholders Technical Skills Skills Requirements: Proficiency in statistical analysis techniques such as regression analysis, hypothesis testing, or time-series analysis. Knowledge of machine learning algorithms and techniques such as supervised learning, unsupervised learning, or reinforcement learning. Experience with data wrangling and data cleaning techniques using tools such as Python, R, or SQL. Understanding of big data technologies such as Hadoop, Spark, or Hive. Must have excellent communication skills and be able to communicate complex technical information to non-technical stakeholders in a clear and concise manner. Must understand the company's long-term vision and align with it. Qualifications 3-5 years of work experience in relevant field B.Tech/B.E/M.Tech or MCA degree from a reputed university. Computer science background is preferred

Role Description : As a Technical Lead - Data Science and Modeling at Incedo, you will be responsible for developing and deploying predictive models and machine learning algorithms to support business decision-making. You will work with data scientists, data engineers, and business analysts to understand business requirements and develop data-driven solutions. You will be skilled in programming languages such as Python or R and have experience in data science tools such as TensorFlow or Keras. You will be responsible for ensuring that models are accurate, efficient, and scalable. Roles & Responsibilities: Developing and implementing machine learning models and algorithms to solve complex business problems Conducting data analysis and modeling using statistical and data analysis tools Collaborating with other teams to ensure the consistency and integrity of data Providing guidance and mentorship to junior data science and modeling specialists Presenting findings and recommendations to stakeholders Technical Skills Skills Requirements: Proficiency in statistical analysis techniques such as regression analysis, hypothesis testing, or time-series analysis. Knowledge of machine learning algorithms and techniques such as supervised learning, unsupervised learning, or reinforcement learning. Experience with data wrangling and data cleaning techniques using tools such as Python, R, or SQL. Understanding of big data technologies such as Hadoop, Spark, or Hive. Must have excellent communication skills and be able to communicate complex technical information to non-technical stakeholders in a clear and concise manner. Must understand the company's long-term vision and align with it. Should be open to new ideas and be willing to learn and develop new skills. Should also be able to work well under pressure and manage multiple tasks and priorities. Qualifications 7-9 years of work experience in relevant field B.Tech/B.E/M.Tech or MCA degree from a reputed university. Computer science background is preferred

We are looking for a highly motivated and talented Junior Data Scientist to join our team at AGR Knowledge Services Pvt Ltd. The ideal candidate will have 2-4 years of experience in the field. Roles and Responsibility Collaborate with cross-functional teams to design and develop data-driven solutions. Analyze complex data sets to identify trends and patterns, providing actionable insights. Develop and maintain databases, data systems, and data pipelines. Design and implement machine learning models and algorithms to solve business problems. Work closely with stakeholders to understand business needs and develop targeted solutions. Stay up-to-date with industry trends and emerging technologies in data science. Job Requirements Strong foundation in statistics, mathematics, and computer science. Proficiency in programming languages such as Python, R, or SAS. Experience with data analysis tools such as SQL, Excel, or Tableau. Knowledge of machine learning algorithms and deep learning techniques. Excellent communication and problem-solving skills. Ability to work in a fast-paced environment and meet deadlines.

Role Description : As a Technical Lead - Data Science and Modeling at Incedo, you will be responsible for developing and deploying predictive models and machine learning algorithms to support business decision-making. You will work with data scientists, data engineers, and business analysts to understand business requirements and develop data-driven solutions. You will be skilled in programming languages such as Python or R and have experience in data science tools such as TensorFlow or Keras. You will be responsible for ensuring that models are accurate, efficient, and scalable. Roles & Responsibilities: Developing and implementing machine learning models and algorithms to solve complex business problems Conducting data analysis and modeling using statistical and data analysis tools Collaborating with other teams to ensure the consistency and integrity of data Providing guidance and mentorship to junior data science and modeling specialists Presenting findings and recommendations to stakeholders Technical Skills : Proficiency in statistical analysis techniques such as regression analysis, hypothesis testing, or time-series analysis. Knowledge of machine learning algorithms and techniques such as supervised learning, unsupervised learning, or reinforcement learning. Experience with data wrangling and data cleaning techniques using tools such as Python, R, or SQL. Understanding of big data technologies such as Hadoop, Spark, or Hive. Must have excellent communication skills and be able to communicate complex technical information to non-technical stakeholders in a clear and concise manner. Must understand the company's long-term vision and align with it. Should be open to new ideas and be willing to learn and develop new skills. Should also be able to work well under pressure and manage multiple tasks and priorities. Qualifications 7-9 years of work experience in relevant field B.Tech/B.E/M.Tech or MCA degree from a reputed university. Computer science background is preferred

Role Description : As a Senior Data Science and Modeling Specialist at Incedo, you will be responsible for developing and deploying predictive models and machine learning algorithms to support business decision-making. You will work with data scientists, data engineers, and business analysts to understand business requirements and develop data-driven solutions. You will be skilled in programming languages such as Python or R and have experience in data science tools such as TensorFlow or Keras. You will be responsible for ensuring that models are accurate, efficient, and scalable. Roles & Responsibilities: Developing and implementing machine learning models and algorithms to solve complex business problems Conducting data analysis and modeling using statistical and data analysis tools Collaborating with other teams to ensure the consistency and integrity of data Providing guidance and mentorship to junior data science and modeling specialists Presenting findings and recommendations to stakeholders Technical Skills : Proficiency in statistical analysis techniques such as regression analysis, hypothesis testing, or time-series analysis. Knowledge of machine learning algorithms and techniques such as supervised learning, unsupervised learning, or reinforcement learning. Experience with data wrangling and data cleaning techniques using tools such as Python, R, or SQL. Understanding of big data technologies such as Hadoop, Spark, or Hive. Must have excellent communication skills and be able to communicate complex technical information to non-technical stakeholders in a clear and concise manner. Must understand the company's long-term vision and align with it. Provide leadership, guidance, and support to team members, ensuring the successful completion of tasks, and promoting a positive work environment that fosters collaboration and productivity, taking responsibility of the whole team. Qualifications 4-6 years of work experience in relevant field B.Tech/B.E/M.Tech or MCA degree from a reputed university. Computer science background is preferred

Role Description : As a Technical Lead - Data Science and Modeling at Incedo, you will be responsible for developing and deploying predictive models and machine learning algorithms to support business decision-making. You will work with data scientists, data engineers, and business analysts to understand business requirements and develop data-driven solutions. You will be skilled in programming languages such as Python or R and have experience in data science tools such as TensorFlow or Keras. You will be responsible for ensuring that models are accurate, efficient, and scalable. Roles & Responsibilities: Developing and implementing machine learning models and algorithms to solve complex business problems Conducting data analysis and modeling using statistical and data analysis tools Collaborating with other teams to ensure the consistency and integrity of data Providing guidance and mentorship to junior data science and modeling specialists Presenting findings and recommendations to stakeholders Technical Skills : Proficiency in statistical analysis techniques such as regression analysis, hypothesis testing, or time-series analysis. Knowledge of machine learning algorithms and techniques such as supervised learning, unsupervised learning, or reinforcement learning. Experience with data wrangling and data cleaning techniques using tools such as Python, R, or SQL. Understanding of big data technologies such as Hadoop, Spark, or Hive. Must have excellent communication skills and be able to communicate complex technical information to non-technical stakeholders in a clear and concise manner. Must understand the company's long-term vision and align with it. Should be open to new ideas and be willing to learn and develop new skills. Should also be able to work well under pressure and manage multiple tasks and priorities. Qualifications 7-9 years of work experience in relevant field B.Tech/B.E/M.Tech or MCA degree from a reputed university. Computer science background is preferred

Research Innovation: o Stay up-to-date with the latest advancements in deep learning, LLMs, and statistical methods. o Conduct experiments to explore new techniques and improve existing models. o Perform applied research and experimentation, validate model performance for accuracy, robustness champion responsible AI practices Deep Learning LLM Development: o Design, implement, and optimize deep learning models and frameworks (e.g., TensorFlow, PyTorch, JAX). o Develop and fine-tune large language models (LLMs) for specific use cases, including natural language processing (NLP) tasks. o Experiment with state-of-the-art architectures (e.g., Transformers, GPT, BERT) to solve complex problems. o Knowledge of Agentic frameworks (Crew AI , llama index etc). o Good knowledge of GenAI framework Statistical Modelling Analysis: o Apply advanced statistical methods to analyse data, validate models, and interpret results. o Develop probabilistic models and leverage Bayesian inference techniques where applicable. o Ensure models are statistically robust and generalize well to real-world data. Data Preprocessing Feature Engineering: o Clean, preprocess, and transform large datasets for training and evaluation. o Perform feature engineering and dimensionality reduction to improve model performance. Model Deployment Optimization: o Deploy deep learning models and LLMs into production environments. o Optimize models for inference speed, memory usage, and scalability. o Implement monitoring and evaluation systems to track model performance over time. Collaboration Leadership: o Work closely with cross-functional teams, including data scientists, engineers, and product managers. o Mentor junior team members and provide technical guidance. Requirements and skills 7+ years in applying AI/ML principles to real world applications Broad NLP knowledge: tokenisation, part-of-speech tagging, dependency parsing, syntactic parsing, word sense disambiguation, topic modeling; contextual text mining, Word embedding Experience Computer Vision: o Construction, Feature detection, Segmentation, Classification o object detection, tracking, localisation, classification, recognition, scene understanding Experience to Deep Learning - CNNs, LSTMs, network architecture, network tuning, transfer learning, multi-task learning Machine Learning experience - Algorithm Evaluation, Preparation, Analysis, Modeling and Execution. Experience to Open source NLP libraries e.g. NLTK, Regex, Stanford NLP, OpenNLP/CoreNLP Very strong grasp of IT concepts with a strong algorithms/data structures background Demonstrated history of building prototypes to win business confidence. Experience in using Keras, Tensorflow, Caffe and/or other neural network development frameworks. Experience with common data science toolkits, such as Scikit, NumPy, R libraries - Excellence in at least one of these is mandatory. Proficiency with any one NoSQL databases such as MongoDB, Cassandra, HBase. Should have prior experience in developing APIs, services using either C# or Java. Experience in Develop, implement, and optimize machine learning models using the Microsoft AI Platform (Azure Machine Learning, Cognitive Services, etc.) Excellent understanding of machine learning techniques and algorithms, such as SVM, Decision Forests, k-NN, Naive Bayes etc. Experience in selecting features, building and optimizing classifiers using machine learning techniques. Should have good awareness on entire machine learning/ predictive modeling implementation. Additional Qualifications: Experience with deep learning frameworks such as TensorFlow, PyTorch, or Keras. Knowledge of natural language processing (NLP) and computer vision techniques. Familiarity with DevOps practices and CI/CD pipelines for machine learning models. Microsoft Azure certifications (e.g., Azure Data Scientist Associate, Azure AI Engineer Associate). Research business domain and develop use-cases to support enterprise wide AI solutions. Monitor and maintain deployed models, ensuring scalability, performance, and accuracy. Prior experience with data visualization tools, such as D3.js, GGplot, etc.. Good knowledge on statistics skills, such as distributions, statistical testing, regression, etc.. Adequate presentation and communication skills to explain results and methodologies to non-technical stakeholders. Basic understanding of the banking industry is value add

Overview We are PepsiCo PepsiCo is one of the world's leading food and beverage companies with more than $79 Billion in Net Revenue and a global portfolio of diverse and beloved brands. We have a complementary food and beverage portfolio that includes 22 brands that each generate more than $1 Billion in annual retail sales. PepsiCo's products are sold in more than 200 countries and territories around the world. PepsiCo's strength is its people. We are over 250,000 game changers, mountain movers and history makers, located around the world, and united by a shared set of values and goals. We believe that acting ethically and responsibly is not only the right thing to do, but also the right thing to do for our business. At PepsiCo, we aim to deliver top-tier financial performance over the long term by integrating sustainability into our business strategy, leaving a positive imprint on society and the environment. We call this Winning with Pep+ Positive . For more information on PepsiCo and the opportunities it holds, visit www.pepsico.com. PepsiCo Data Analytics & AI Overview: With data deeply embedded in our DNA, PepsiCo Data, Analytics and AI (DA&AI) transforms data into consumer delight. We build and organize business-ready data that allows PepsiCo’s leaders to solve their problems with the highest degree of confidence. Our platform of data products and services ensures data is activated at scale. This enables new revenue streams, deeper partner relationships, new consumer experiences, and innovation across the enterprise. The Data Science Pillar in DA&AI will be the organization where Data Scientist and ML Engineers report to in the broader D+A Organization. Also DS will lead, facilitate and collaborate on the larger DS community in PepsiCo. DS will provide the talent for the development and support of DS component and its life cycle within DA&AI Products. And will support “pre-engagement” activities as requested and validated by the prioritization framework of DA&AI. Data Scientist-Gurugram and Hyderabad The role will work in developing Machine Learning (ML) and Artificial Intelligence (AI) projects. Specific scope of this role is to develop ML solution in support of ML/AI projects using big analytics toolsets in a CI/CD environment. Analytics toolsets may include DS tools/Spark/Databricks, and other technologies offered by Microsoft Azure or open-source toolsets. This role will also help automate the end-to-end cycle with Machine Learning Services and Pipelines. Responsibilities Delivery of key Advanced Analytics/Data Science projects within time and budget, particularly around DevOps/MLOps and Machine Learning models in scope Collaborate with data engineers and ML engineers to understand data and models and leverage various advanced analytics capabilities Ensure on time and on budget delivery which satisfies project requirements, while adhering to enterprise architecture standards Use big data technologies to help process data and build scaled data pipelines (batch to real time) Automate the end-to-end ML lifecycle with Azure Machine Learning and Azure/AWS/GCP Pipelines. Setup cloud alerts, monitors, dashboards, and logging and troubleshoot machine learning infrastructure Automate ML models deployments Qualifications Minimum 3years of hands-on work experience in data science / Machine learning Minimum 3year of SQL experience Experience in DevOps and Machine Learning (ML) with hands-on experience with one or more cloud service providers. BE/BS in Computer Science, Math, Physics, or other technical fields. Data Science - Hands on experience and strong knowledge of building machine learning models - supervised and unsupervised models Programming Skills - Hands-on experience in statistical programming languages like Python and database query languages like SQL Statistics - Good applied statistical skills, including knowledge of statistical tests, distributions, regression, maximum likelihood estimators Any Cloud - Experience in Databricks and ADF is desirable Familiarity with Spark, Hive, Pig is an added advantage Model deployment experience will be a plus Experience with version control systems like GitHub and CI/CD tools Experience in Exploratory data Analysis Knowledge of ML Ops / DevOps and deploying ML models is required Experience using MLFlow, Kubeflow etc. will be preferred Experience executing and contributing to ML OPS automation infrastructure is good to have Exceptional analytical and problem-solving skills

We're hiring an AI Lead Engineer! Design and deploy LLM-powered, RAG-based solutions with LangChain, vector DBs, and cloud-native tools. Ideal for hands-on builders passionate about real-world AI impact.

About Loadshare: LoadShare is one of India’s most innovative and resilient logistics platforms, transforming how goods move across the country. Founded in 2017, we’ve grown to become a pan-India, multi-category last-mile network with a unique presence in both Tier 1 metros and deep Tier 2/3 towns. What sets us apart: • Scale with depth: We handle ~400K deliveries/day across food, e-commerce (B2C), B2B retail, and digital commerce, powered by a 20,000+ rider network. • Strong financials, stronger ambition: With 430 Cr in FY25 revenue and support from global investors (Tiger Global, Matrix, BII, Stellaris, BeeNext), we have a long runway and a path to profitability • Dual-engine model : We not only operate India’s most flexible last-mile delivery network, but also license our in-house logistics tech platform that processes an additional 20 lac orders/day — one of the few in India to enable asset cross-utilization across verticals • Strategic partner to India’s digital economy: We work with every major digital commerce player (ecomm, quick commerce, food, mobility) , and are expanding wallet share and capabilities within existing giants while co-creating new models with emerging platforms and brands. • Built to scale profitably : We’re not chasing GMV at all costs. We’re building the most capital-efficient, tech-enabled logistics engine in the country. We’re now building for our next phase: a 5X scale-up over the next 5 years, anchored in sharper client focus, deeper solutions, and new growth engines. Founders/ Founding team: Raghu Talluri (CEO) - Formerly at Myntra, McKinsey Pramod Nair (CTO) - Formerly at Freecharge, Snapdeal, MartMobi Rakib Ahmed (Co Founder, Head EComm/ Trucking/Warehousing) - Formerly at ICICI Prudential, Co founder Lunate Eco Overall 500+ employees on roll The Role: Where Business Meets Data Science We’re looking for a Senior Data Scientist to join our Hyperlocal Business Unit —the fastest growing part of LoadShare. This isn’t your typical ML role. You'll be at the intersection of real-time rider allocation, business margins, customer experience, and fair pay to gig workers. You'll have full ownership and freedom to rethink how orders get assigned, how riders move, and how we balance profitability with empathy and excellence. Your mission, should you choose to accept: Make our allocation engine smarter and faster, using data science, machine learning, and a bit of madness. Every 0.1% improvement you drive scales across lacs of deliveries and thousands of riders. Roles and Responsibilities What You’ll Work On Rider Allocation Engine: Improve how we assign orders to riders using ML, optimization, and predictive modeling to improve margins, reduce wait times, and increase batchability. Rider Earnings vs. Business Margins: Build models that find the sweet spot between paying riders fairly and hitting profitability goals—without compromising on customer experience. Demand-Supply Matching: Create algorithms to anticipate demand, shape rider shifts across space and time, and reduce delivery failures in hotspots and dark zones. CX & SLA Optimization: Use historical data to predict SLA risks and proactively re-route or re-assign in real-time. Experimentation & Impact: Design A/B tests to validate everything you ship. What you build, you own. Scale ML in Production: Work with engineering to ship robust, real-time data science solutions that touch live operations daily. Why This Role is Cool Real-World Impact: Your models will affect lacs of orders and thousands of livelihoods every single day. Freedom to Experiment : You get a playground with real data, full support from leadership, and space to try bold ideas. Full Stack Data Science: From ideation to shipping models to influencing business decisions, you’ll do it all. Tech + Ops Fusion: See your work directly improve operations, rider morale, and customer happiness—in days, not quarters. Incredible Team: Work with some of the sharpest minds in logistics, ops, and engineering. Quick Commerce Revolution: You get to be in the foreground of the QC revolution, shaping how 3Ps help solve the stress. What We’re Looking For 4+ years of experience in Data Science/ML/OR solving complex real-world problems Strong in Python, SQL, and ML frameworks. Good grounding in optimization, statistics, experimentation, and business sense Curious mind, strong communication skills, and a bias for action. Bonus Points If You Have Worked on last-mile logistics, food delivery, or hyperlocal services Built real-time systems or worked closely with engineering on model deployment Experience with geospatial data, ETA models, or dynamic pricing Passion for making tech more inclusive for gig workers and emerging markets Ready to Redefine Hyperlocal Logistics? Join us. Help build a system that delivers millions of packages, changes thousands of lives, and sets the gold standard for modern intracity logistics—using data.

Data Management : Collect, validate, and maintain data from various departments including inventory, sales, procurement, and finance. Design and develop automation scripts using Google Apps Script . Build custom Google Sheet dashboards and reports with real-time data integration. Integrate Google Workspace with third-party APIs (e.g., WhatsApp, Slack, payment gateways, or internal systems). Reporting : Generate and distribute daily, weekly, and monthly sales reports. Create customized dashboards for different departments (e.g. showroom performance, online sales, vendor performance). Develop management reports (MIS reports) on inventory levels, procurement trends, and customer analytics. ERP / POS Systems : Work closely with ERP or POS systems used in jewelry retail (e.g. , Sionic, Tally,CRM, ) to extract meaningful reports. Job Type: Full-time Pay: ₹45,000.00 - ₹55,000.00 per month Benefits: Paid sick time Provident Fund Work from home Schedule: Day shift Supplemental Pay: Yearly bonus Work Location: In person

Ability to design and implement workflows of Linear and Logistic Regression, Ensemble Models (Random Forest, Boosting) using R/Python Demonstrable competency in Probability and Statistics, ability to use ideas of Data Distributions, Hypothesis Testing and other Statistical Tests. Must have experience in dealing with outliers, denoising data and handling the impact of pandemic like situations. Should be able to perform EDA of raw data & feature engineering wherever applicable Demonstrable competency in Data Visualisation using the Python/R Data Science Stack. Should be able to leverage cloud platforms for training and deploying large scale solutions. Should be able to train and evaluate ML model using various machine learning and deep learning algorithm. Retrain and maintain model accuracy in deployment. Should be able to package & deploy large scale models on on-premise systems using multiple approaches including docker. Should be able to take complete ownership of the assigned project Experience of working in Agile environments Well versed with JIRA or equivalent project tracking tool Knowledge of cloud platforms (AWS, Azure and GCP) Exposure to No SQL databases (MongoDB, Cassandra, Cosmos DB, HBase) Forecasting experience in products like SAP, Oracle, Power BI, Qlik, etc. Proficiency in Excel (Power Pivot, Power Query, Macros, Charts) An experience with large data sets and distributed computing (Hive/Hadoop/Spark) Transfer learning using state of art models in different spaces – vision, NLP and speech. - Integration with external services and Cloud API. Working with data annotation approaches and tools for text, images and videos

Hi Everyone, Experience : 6-9yrs Work Mode: Hybrid Work location : Chennai/Bangalore/Pune Location Notice Period : Immediate - 30 days Role : Data Scientist Skills and Experience: 5 year with Data science and ML exposure Key Accountabilities & Responsibilities Support the Data Science team with the development of advanced analytics/machine learning/artificial intelligence initiatives Analyzing large and complex datasets to uncover trends and insights. Supporting the development of predictive models and machine learning workflows. Performing exploratory data analysis to guide product and business decisions. Collaborating with cross-functional teams, including product, marketing, and engineering. Assisting with the design and maintenance of data pipelines. Clearly documenting and communicating analytical findings to technical and non-technical stakeholders. Basic Qualifications: Qualificiation in Data Science, Statistics, Computer Science, Mathematics, or a related field. Proficiency in Python and key data science libraries (e.g., pandas, NumPy, scikit-learn). Operational understanding of machine learning principles and statistical modeling. Experience with SQL for data querying. Strong communication skills and a collaborative mindset. Preferred Qualifications Exposure to cloud platforms such as AWS, GCP, or Azure. Familiarity with data visualization tools like Tableau, Power BI, or matplotlib. Participation in personal data science projects or online competitions (e.g., Kaggle). Understanding of version control systems like Git. Kindly, share the following details : Updated CV Relevant Skills Total Experience Current Company Current CTC Expected CTC Notice Period Current Location Preferred Location

Our vision is to transform how the world uses information to enrich life for all . Micron Technology is a world leader in innovating memory and storage solutions that accelerate the transformation of information into intelligence, inspiring the world to learn, communicate and advance faster than ever. Roles & responsibilities can include but are not limited to: Broad knowledge and experience in: Strong desire to grow career as Data Scientist in highly automated industrial manufacturing doing analysis and machine learning on terabytes and petabytes of diverse datasets. Ability to extract data from different databases via SQL and other query languages and applying data cleansing, outlier identification, and missing data techniques. Ability to apply latest mathematical and statistical techniques to analyze data and uncover patterns. Interested to build web application as part of job scope. Knowledge in Cloud based Analytics and Machine Learning Modeling Knowledge in building APIs for application integration. Knowledge in the areas: statistical modeling, feature extraction and analysis, feature engineering, supervised/unsupervised/semi-supervised learning. Data Analysis and Validation skills Strong software development skills. Above average skills in: Programming Fluency in Python Knowledge in statistics, Machine learning and other advanced analytical methods Knowledge in javascript, AngularJS 2.0, Tableau will be added advantage. Knowledge in OOPS background is added advantage. Understanding of pySpark and/or libraries for distributed and parallel processing is added advantage. Knowledge in Tensorflow, and/or other statistical software including scripting capability for automating analyses Knowledge with time series data, images, semi-supervised learning, and data with frequently changing distributions is a plus Understanding of Manufacturing Execution Systems (MES) is a plus Demonstrated ability to: Work in a dynamic, fast-paced, work environment Self-motivated with the ability to work under minimal direction To adapt to new technologies and learn quickly A passion for data and information with strong analytical, problem solving, and organizational skills Work in multi-functional groups, with diverse interests and requirements, to a common objective Communicate very well with distributed teams (written, verbal and presentation) Education Requirement & eligibility: Bachelor’s or Master’s degree in Computer science, Electrical/Electronic Engineering. CGPA requirements = 7.0 CGPA & Above Location: Sanand Gujarat About Micron Technology, Inc. We are an industry leader in innovative memory and storage solutions transforming how the world uses information to enrich life for all . With a relentless focus on our customers, technology leadership, and manufacturing and operational excellence, Micron delivers a rich portfolio of high-performance DRAM, NAND, and NOR memory and storage products through our Micron® and Crucial® brands. Every day, the innovations that our people create fuel the data economy, enabling advances in artificial intelligence and 5G applications that unleash opportunities — from the data center to the intelligent edge and across the client and mobile user experience. To learn more, please visit micron.com/careers All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, veteran or disability status. To request assistance with the application process and/or for reasonable accommodations, please contact hrsupport_india@micron.com Micron Prohibits the use of child labor and complies with all applicable laws, rules, regulations, and other international and industry labor standards. Micron does not charge candidates any recruitment fees or unlawfully collect any other payment from candidates as consideration for their employment with Micron. AI alert : Candidates are encouraged to use AI tools to enhance their resume and/or application materials. However, all information provided must be accurate and reflect the candidate's true skills and experiences. Misuse of AI to fabricate or misrepresent qualifications will result in immediate disqualification. Fraud alert: Micron advises job seekers to be cautious of unsolicited job offers and to verify the authenticity of any communication claiming to be from Micron by checking the official Micron careers website in the About Micron Technology, Inc.

We are PepsiCo PepsiCo is one of the world's leading food and beverage companies with more than $79 Billion in Net Revenue and a global portfolio of diverse and beloved brands. We have a complementary food and beverage portfolio that includes 22 brands that each generate more than $1 Billion in annual retail sales. PepsiCo's products are sold in more than 200 countries and territories around the world. PepsiCo's strength is its people. We are over 250,000 game changers, mountain movers and history makers, located around the world, and united by a shared set of values and goals. We believe that acting ethically and responsibly is not only the right thing to do, but also the right thing to do for our business. At PepsiCo, we aim to deliver top-tier financial performance over the long term by integrating sustainability into our business strategy, leaving a positive imprint on society and the environment. We call this Winning with Pep+ Positive . For more information on PepsiCo and the opportunities it holds, visit www.pepsico.com. PepsiCo Data Analytics & AI Overview: With data deeply embedded in our DNA, PepsiCo Data, Analytics and AI (DA&AI) transforms data into consumer delight. We build and organize business-ready data that allows PepsiCo’s leaders to solve their problems with the highest degree of confidence. Our platform of data products and services ensures data is activated at scale. This enables new revenue streams, deeper partner relationships, new consumer experiences, and innovation across the enterprise. The Data Science Pillar in DA&AI will be the organization where Data Scientist and ML Engineers report to in the broader D+A Organization. Also DS will lead, facilitate and collaborate on the larger DS community in PepsiCo. DS will provide the talent for the development and support of DS component and its life cycle within DA&AI Products. And will support “pre-engagement” activities as requested and validated by the prioritization framework of DA&AI. Data Scientist-Gurugram and Hyderabad The role will work in developing Machine Learning (ML) and Artificial Intelligence (AI) projects. Specific scope of this role is to develop ML solution in support of ML/AI projects using big analytics toolsets in a CI/CD environment. Analytics toolsets may include DS tools/Spark/Databricks, and other technologies offered by Microsoft Azure or open-source toolsets. This role will also help automate the end-to-end cycle with Machine Learning Services and Pipelines. Responsibilities Delivery of key Advanced Analytics/Data Science projects within time and budget, particularly around DevOps/MLOps and Machine Learning models in scope Collaborate with data engineers and ML engineers to understand data and models and leverage various advanced analytics capabilities Ensure on time and on budget delivery which satisfies project requirements, while adhering to enterprise architecture standards Use big data technologies to help process data and build scaled data pipelines (batch to real time) Automate the end-to-end ML lifecycle with Azure Machine Learning and Azure/AWS/GCP Pipelines. Setup cloud alerts, monitors, dashboards, and logging and troubleshoot machine learning infrastructure Automate ML models deployments Qualifications Minimum 3years of hands-on work experience in data science / Machine learning Minimum 3year of SQL experience Experience in DevOps and Machine Learning (ML) with hands-on experience with one or more cloud service providers BE/BS in Computer Science, Math, Physics, or other technical fields. Data Science – Hands on experience and strong knowledge of building machine learning models – supervised and unsupervised models Programming Skills – Hands-on experience in statistical programming languages like Python and database query languages like SQL Statistics – Good applied statistical skills, including knowledge of statistical tests, distributions, regression, maximum likelihood estimators Any Cloud – Experience in Databricks and ADF is desirable Familiarity with Spark, Hive, Pig is an added advantage Model deployment experience will be a plus Experience with version control systems like GitHub and CI/CD tools Experience in Exploratory data Analysis Knowledge of ML Ops / DevOps and deploying ML models is required Experience using MLFlow, Kubeflow etc. will be preferred Experience executing and contributing to ML OPS automation infrastructure is good to have Exceptional analytical and problem-solving skills