3292 Data Scientist Jobs - Page 3

Hello Visionary! We empower our people to stay resilient and relevant in a constantly changing world. We’re looking for people who are always searching for creative ways to grow and learn. People who want to make a real impact, now and in the future. Does that sound like you? Then it seems like you’d make a great addition to our vibrant team. We are seeking an experienced Data Scientist with a strong foundation in Python, Machine Learning, and Cloud-based Analytics. You will play a key role in building data-driven energy optimization solutions across buildings and campuses. From time-series analysis to predictive maintenance, you’ll work on impactful projects that accelerate energy efficiency and sustainability on a global scale. This position is for Pune Location. You’ll Make a Difference By: Collaborating with stakeholders to understand business objectives and develop data science strategies aligned with those objectives. Design, develop, and implement advanced machine learning and statistical models to solve complex business problems. Conduct exploratory data analysis, data cleansing, and feature engineering to prepare datasets for analysis. Exploring and utilize various data mining and machine learning techniques to extract valuable insights and patterns from large datasets. Developing predictive/prescriptive models, algorithms, and prototypes to support business. Having working knowledge of handling IOT and IIOT data and handling traditional use cases like anomaly detection for a multi-sensor system. Having hands-on experience in Forecasting using traditional ML and Deep Networks. Performing statistical analysis, hypothesis testing, and A/B testing to evaluate the effectiveness of models and algorithms. Communicate findings and insights to technical and non-technical stakeholders through reports, presentations, and data visualizations. Understanding CI/CD processes in product deployment and used it in delivery. Understanding of the Dockerization, REST APIs. Working knowledge on software development processes. Stay up to date with the latest trends and advancements in data science, machine learning, and AI You’ll Win Us Over If You Have: Advanced degree (Master's or Ph.D.) in a quantitative field such as Data Science, Computer Science, or Statistics, or Bachelors degree (BE. BTech, BS) with demonstrated equivalent practical experience. 5+ years of experience in data science and/or data analysis with a proven track record of developing ML models and algorithms. A masters or Ph.D. degree in Data Science, Computer Science, Statistics, or a related field. Strong programming skills in languages such as Python. Exposure to the industrial engineering domain is preferred. Knowledge of big data technologies such as Hadoop, Spark, or Hive is a plus. Proficient in the use of data science tools. A collaborative, team-oriented attitude with a proactive mindset. Join us and be yourself! We value your unique identity and perspective, recognizing that our strength comes from the diverse backgrounds, experiences, and thoughts of our team members. We are fully committed to providing equitable opportunities and building a workplace that reflects the diversity of society. We also support you in your personal and professional journey by providing resources to help you thrive. Come bring your authentic self and create a better tomorrow with us. Make your mark in our exciting world at Siemens. This role is based in Pune and is an Individual contributor role. You might be required to visit other locations within India and outside. In return, you'll get the chance to work with teams impacting - and the shape of things to come. We're Siemens. A collection of over 379,000 minds building the future, one day at a time in over 200 countries. Find out more about Siemens careers at: www.siemens.com/careers Job Id: DT1+OqdVT7LS5MLbIOv5IiP+/SADLv1FYBT7ocXg1NSFM6a+FRQu3Zx/YJgCYgTTfGqBXPoakPpGFWKtVsObzTqS2JaFeDYLRL5Of3+Nx2R4coCtx7LwlsEDUjml0NrTnNrT9/Sj9fQWndR70ybeziEUSsYiKpj+wI7Z

What will your day look like - Leading a dynamic team to deliver high impact risk solutions across credit risk (underwriting, exposure controls and line management). - Work with stakeholders across product management, data science, and engineering to build relationship with the partner teams and drive implementation of risk strategies - Manage challenging time constraints to ensure on-time delivery of projects. - Work closely with partner teams in identifying, evaluating, and recommending new data that helps in risk differentiation. - Analyze loss trends and simulate risk decisioning strategies that help optimize revenue, approval rates etc. - Work closely with data science team and recommends credit risk decisioning and model deployment strategy. - Build a risk scorecard that leverages both internal performance data and external performance data that will be leveraged for credit decisioning at both underwriting and account management reviews for existing customers. - Collates analysis and builds presentations that helps articulate the risk strategy for the leadership team. To Help Us Level Up, You Will Ideally Have : - Quantitative background in engineering, statistics, math, economics, business, or related disciplines. - 5+ years experience in analyzing data and using database query language (e. SQL) analysis and programming and developer tools such as Python, R, data bricks in a finance or analytics field. - 2+ years of experience in leading high performing team of analysts. - Experience in working with non-traditional data such as social media will be a big plus. - Prior model building experience is a plus but not critical. - Possesses an analytical mindset and strong problem-solving skills. - Attention to detail and ability to multitask. - Comfortable working in a fast-paced environment and dealing with ambiguity. - Possesses strong communication, interpersonal and presentation skills; and ability to engage and collaborate with multiple stakeholders across teams. - Extremely proactive communicator willing to raise flags when needed and keep team members informed of ongoing risk or fraud related activities.

We are seeking a highly skilled and experienced Senior Data Scientist to join our team. In this role, you will leverage advanced Natural Language Processing (NLP), Deep Learning, and traditional Machine Learning (ML) techniques to build and optimize our NLP-driven products and services. You will work closely with cross-functional teams to develop scalable, highperformance NLP models that solve complex language and data-related challenges. If you are passionate about advancing language understanding and have hands-on experience with the latest NLP frameworks, models, and techniques, we would love to speak with you! Responsibilities Model Development and Optimization: Design, build, and deploy NLP models, including transformer models (e.g., BERT, GPT, T5) and other SOTA architectures, as well as traditional machine learning algorithms (e.g., SVMs, Logistic Regression) for specific applications. Data Processing and Feature Engineering: Develop robust pipelines for text preprocessing, feature extraction, and data augmentation for structured and unstructured data. Model Fine-Tuning and Transfer Learning: Fine-tune large language models for specific applications, leveraging transfer learning techniques, domain adaptation, and a mix of deep learning and traditional ML models. Performance Optimization: Optimize model performance for scalability and latency, applying techniques such as quantization, ONNX formats etc. Research and Innovation: Stay updated with the latest research in NLP, Deep Learning, and Generative AI, applying innovative solutions and techniques (e.g., RAG applications, Prompt engineering, Self-supervised learning). Stakeholder Communication: Collaborate with stakeholdersto gather requirements, conduct due diligence, and communicate project updates effectively, ensuring alignment between technical solutions and business goals Evaluation and Testing: Establish metrics, benchmarks, and methodologies for model evaluation, including cross-validation, and error analysis, ensuring models meet accuracy, fairness, and reliability standards Deployment and Monitoring: Oversee the deployment of NLP models in production, ensuring seamless integration, model monitoring, and retraining processes. Requirements Minimum Qualifications Education: Bachelor s degree in computer science, or a related field. Experience: Minimum of 1 to 3 years of experience in NLP, Deep Learning, and ML, with a proven track record of developing and optimizing both LLM and traditional machine learning NLP models. Technical Skills Advanced NLP Techniques: Proficiency in transformer models (e.g., BERT, RoBERTa, GPT, T5), and experience with techniques like entity recognition (NER), text classification, summarization, question answering, and language generation. Programming: Strong programming skills in Python, with experience in NLP libraries such as Hugging Face Transformers, spaCy, NLTK, and Gensim. ML and DL Frameworks: Proficiency in ML and Deep Learning frameworks such as TensorFlow, PyTorch, and Scikit-learn Traditional ML Techniques: Familiarity with traditional ML models like SVMs, Logistic Regression, Decision Trees, and KNN etc Evaluation Metrics: Familiarity with NLP and ML evaluation metrics (e.g., BLEU, ROUGE, F1, accuracy, precision, recall) and experience designing experiments and tests. Soft Skills Communication Skills: Excellent verbal and written communication skills, capable of explaining technical concepts to both technical and non-technical stakeholders. Enthusiasm for Learning: A self-motivated individual with a passion for continuous learning and openness to exploring new technologies. Teamwork and Collaboration: A team player with the ability to work effectively in a collaborative, fast-paced environment EAIGG Draup is a Member of the Ethical AI Governance Group As an AI-first company, Draup has been a champion of ethical and responsible AI since day one. Our models adhere to the strictest data standards and are routinely audited for bias. Drive better decisions with unmatched, real-time data & agentic intelligence Thank you! Your submission has been received! Oops! Something went wrong while submitting the form. Cookies required to enable basic website functionality. Cookies used to deliver advertising that is more relevant to you and your interests. Cookies allowing the website to remember choices you make (such as your user name, language, or the region you are in). Cookies helping understand how this website performs, how visitors interact with the site, and whether there may be technical issues.

Role & responsibilities: Outline the day-to-day responsibilities for this role. Preferred candidate profile: Specify required role expertise, previous job experience, or relevant certifications. Perks and benefits: Mention available facilities and benefits the company is offering with this job.

JD • Total IT experience: 7 to 10 years in DWH is must • 2-4 years of experience in implementing NLP/GenAI projects • 1 year of experience in extract entities from Large Documents with greater than 100 pages - typically legal documents / Contract Documents /Claim Documents/medical documents • 6 months to 1 year of experience in processing large documents using GenAI APIs like Azure OpenAI,Amazon Bedrock, Google Gemini , Anthropic Claud • Thorough understanding of NLP terminologies like Sentiment Analysis/ Entity Extraction/Topic Modeling etc • Should have used Cloud Cognitive Services for key phrase extraction and document digitization like Azure Doc Intelligence, Google Doc Intelligence, AWS Textract etc • 6 months to 1 year of experience in building LLM Applications for Information Retrieval and a thorough understanding and implementation using LangChain/Vector DBs and deploying it in cloud • Shoud have understanding of GPT Architecture and open-source models like LlaMA/ Mistral etc. • Minimum 1 year of implementation experience using Classical NLP libraries like NLTK/SpaCY etc • Should be able to wtite modular code that can be productionized and well-commented coding standards and practices • Should have used advanced NLP frameworks like Keras/Transformers etc in real-time • Basic Understanding of Neural Networks for Text processing and exposure to algorithms like BERT/GPT/RNN etc • Good understanding of GenAI trends and recent model advancements • Good verbal and written communication skills • Solid understanding of REST API and frameworks like Flask and FastAPI

JD • Total IT experience: 7 to 10 years in DWH is must • 2-4 years of experience in implementing NLP/GenAI projects • 1 year of experience in extract entities from Large Documents with greater than 100 pages - typically legal documents / Contract Documents /Claim Documents/medical documents • 6 months to 1 year of experience in processing large documents using GenAI APIs like Azure OpenAI,Amazon Bedrock, Google Gemini , Anthropic Claud • Thorough understanding of NLP terminologies like Sentiment Analysis/ Entity Extraction/Topic Modeling etc • Should have used Cloud Cognitive Services for key phrase extraction and document digitization like Azure Doc Intelligence, Google Doc Intelligence, AWS Textract etc • 6 months to 1 year of experience in building LLM Applications for Information Retrieval and a thorough understanding and implementation using LangChain/Vector DBs and deploying it in cloud • Shoud have understanding of GPT Architecture and open-source models like LlaMA/ Mistral etc. • Minimum 1 year of implementation experience using Classical NLP libraries like NLTK/SpaCY etc • Should be able to wtite modular code that can be productionized and well-commented coding standards and practices • Should have used advanced NLP frameworks like Keras/Transformers etc in real-time • Basic Understanding of Neural Networks for Text processing and exposure to algorithms like BERT/GPT/RNN etc • Good understanding of GenAI trends and recent model advancements • Good verbal and written communication skills • Solid understanding of REST API and frameworks like Flask and FastAPI

JD • Total IT experience: 7 to 10 years in DWH is must • 2-4 years of experience in implementing NLP/GenAI projects • 1 year of experience in extract entities from Large Documents with greater than 100 pages - typically legal documents / Contract Documents /Claim Documents/medical documents • 6 months to 1 year of experience in processing large documents using GenAI APIs like Azure OpenAI,Amazon Bedrock, Google Gemini , Anthropic Claud • Thorough understanding of NLP terminologies like Sentiment Analysis/ Entity Extraction/Topic Modeling etc • Should have used Cloud Cognitive Services for key phrase extraction and document digitization like Azure Doc Intelligence, Google Doc Intelligence, AWS Textract etc • 6 months to 1 year of experience in building LLM Applications for Information Retrieval and a thorough understanding and implementation using LangChain/Vector DBs and deploying it in cloud • Shoud have understanding of GPT Architecture and open-source models like LlaMA/ Mistral etc. • Minimum 1 year of implementation experience using Classical NLP libraries like NLTK/SpaCY etc • Should be able to wtite modular code that can be productionized and well-commented coding standards and practices • Should have used advanced NLP frameworks like Keras/Transformers etc in real-time • Basic Understanding of Neural Networks for Text processing and exposure to algorithms like BERT/GPT/RNN etc • Good understanding of GenAI trends and recent model advancements • Good verbal and written communication skills • Solid understanding of REST API and frameworks like Flask and FastAPI

Data Science with NLP Experience Must.

Data Science with NLP Experience Must.

Data Science with NLP Experience Must.

Total IT experience: 7 to 10 years in DWH is must 2-4 years of experience in implementing NLP/GenAI projects 1 year of experience in extract entities from Large Documents with greater than 100 pages - typically legal documents / Contract Documents /Claim Documents/medical documents 6 months to 1 year of experience in processing large documents using GenAI APIs like Azure OpenAI,Amazon Bedrock, Google Gemini , Anthropic Claud Thorough understanding of NLP terminologies like Sentiment Analysis/ Entity Extraction/Topic Modeling etc Should have used Cloud Cognitive Services for key phrase extraction and document digitization like Azure Doc Intelligence, Google Doc Intelligence, AWS Textract etc 6 months to 1 year of experience in building LLM Applications for Information Retrieval and a thorough understanding and implementation using LangChain/Vector DBs and deploying it in cloud Shoud have understanding of GPT Architecture and open-source models like LlaMA/ Mistral etc. Minimum 1 year of implementation experience using Classical NLP libraries like NLTK/SpaCY etc Should be able to wtite modular code that can be productionized and well-commented coding standards and practices Should have used advanced NLP frameworks like Keras/Transformers etc in real-time Basic Understanding of Neural Networks for Text processing and exposure to algorithms like BERT/GPT/RNN etc Good understanding of GenAI trends and recent model advancements Good verbal and written communication skills Solid understanding of REST API and frameworks like Flask and FastAPI Role & responsibilities

Total IT experience: 7 to 10 years in DWH is must 2-4 years of experience in implementing NLP/GenAI projects 1 year of experience in extract entities from Large Documents with greater than 100 pages - typically legal documents / Contract Documents /Claim Documents/medical documents 6 months to 1 year of experience in processing large documents using GenAI APIs like Azure OpenAI,Amazon Bedrock, Google Gemini , Anthropic Claud Thorough understanding of NLP terminologies like Sentiment Analysis/ Entity Extraction/Topic Modeling etc Should have used Cloud Cognitive Services for key phrase extraction and document digitization like Azure Doc Intelligence, Google Doc Intelligence, AWS Textract etc 6 months to 1 year of experience in building LLM Applications for Information Retrieval and a thorough understanding and implementation using LangChain/Vector DBs and deploying it in cloud Shoud have understanding of GPT Architecture and open-source models like LlaMA/ Mistral etc. Minimum 1 year of implementation experience using Classical NLP libraries like NLTK/SpaCY etc Should be able to wtite modular code that can be productionized and well-commented coding standards and practices Should have used advanced NLP frameworks like Keras/Transformers etc in real-time Basic Understanding of Neural Networks for Text processing and exposure to algorithms like BERT/GPT/RNN etc Good understanding of GenAI trends and recent model advancements Good verbal and written communication skills Solid understanding of REST API and frameworks like Flask and FastAPI Role & responsibilities

JD: Total IT experience: 7 to 10 years in DWH is must • 2-4 years of experience in implementing NLP/GenAI projects • 1 year of experience in extract entities from Large Documents with greater than 100 pages - typically legal documents / Contract Documents /Claim Documents/medical documents • 6 months to 1 year of experience in processing large documents using GenAI APIs like Azure OpenAI,Amazon Bedrock, Google Gemini , Anthropic Claud • Thorough understanding of NLP terminologies like Sentiment Analysis/ Entity Extraction/Topic Modeling etc • Should have used Cloud Cognitive Services for key phrase extraction and document digitization like Azure Doc Intelligence, Google Doc Intelligence, AWS Textract etc • 6 months to 1 year of experience in building LLM Applications for Information Retrieval and a thorough understanding and implementation using LangChain/Vector DBs and deploying it in cloud • Shoud have understanding of GPT Architecture and open-source models like LlaMA/ Mistral etc. • Minimum 1 year of implementation experience using Classical NLP libraries like NLTK/SpaCY etc • Should be able to wtite modular code that can be productionized and well-commented coding standards and practices • Should have used advanced NLP frameworks like Keras/Transformers etc in real-time • Basic Understanding of Neural Networks for Text processing and exposure to algorithms like BERT/GPT/RNN etc • Good understanding of GenAI trends and recent model advancements • Good verbal and written communication skills • Solid understanding of REST API and frameworks like Flask and FastAPI

JD: Total IT experience: 7 to 10 years in DWH is must • 2-4 years of experience in implementing NLP/GenAI projects • 1 year of experience in extract entities from Large Documents with greater than 100 pages - typically legal documents / Contract Documents /Claim Documents/medical documents • 6 months to 1 year of experience in processing large documents using GenAI APIs like Azure OpenAI,Amazon Bedrock, Google Gemini , Anthropic Claud • Thorough understanding of NLP terminologies like Sentiment Analysis/ Entity Extraction/Topic Modeling etc • Should have used Cloud Cognitive Services for key phrase extraction and document digitization like Azure Doc Intelligence, Google Doc Intelligence, AWS Textract etc • 6 months to 1 year of experience in building LLM Applications for Information Retrieval and a thorough understanding and implementation using LangChain/Vector DBs and deploying it in cloud • Shoud have understanding of GPT Architecture and open-source models like LlaMA/ Mistral etc. • Minimum 1 year of implementation experience using Classical NLP libraries like NLTK/SpaCY etc • Should be able to wtite modular code that can be productionized and well-commented coding standards and practices • Should have used advanced NLP frameworks like Keras/Transformers etc in real-time • Basic Understanding of Neural Networks for Text processing and exposure to algorithms like BERT/GPT/RNN etc • Good understanding of GenAI trends and recent model advancements • Good verbal and written communication skills • Solid understanding of REST API and frameworks like Flask and FastAPI

JD: Total IT experience: 7 to 10 years in DWH is must • 2-4 years of experience in implementing NLP/GenAI projects • 1 year of experience in extract entities from Large Documents with greater than 100 pages - typically legal documents / Contract Documents /Claim Documents/medical documents • 6 months to 1 year of experience in processing large documents using GenAI APIs like Azure OpenAI,Amazon Bedrock, Google Gemini , Anthropic Claud • Thorough understanding of NLP terminologies like Sentiment Analysis/ Entity Extraction/Topic Modeling etc • Should have used Cloud Cognitive Services for key phrase extraction and document digitization like Azure Doc Intelligence, Google Doc Intelligence, AWS Textract etc • 6 months to 1 year of experience in building LLM Applications for Information Retrieval and a thorough understanding and implementation using LangChain/Vector DBs and deploying it in cloud • Shoud have understanding of GPT Architecture and open-source models like LlaMA/ Mistral etc. • Minimum 1 year of implementation experience using Classical NLP libraries like NLTK/SpaCY etc • Should be able to wtite modular code that can be productionized and well-commented coding standards and practices • Should have used advanced NLP frameworks like Keras/Transformers etc in real-time • Basic Understanding of Neural Networks for Text processing and exposure to algorithms like BERT/GPT/RNN etc • Good understanding of GenAI trends and recent model advancements • Good verbal and written communication skills • Solid understanding of REST API and frameworks like Flask and FastAPI

About the Role Love deep data? Love discussing solutions instead of problems? Then you could be our next Data Scientist. In a nutshell, your primary responsibility will be enhancing the productivity and utilisation of the generated data. Other things you will do are: -Work closely with the business stakeholders -Transform scattered pieces of information into valuable data -Share and present your valuable insights with peers What You Will Do Develop models and run experiments to infer insights from hard data Improve our product usability and identify new growth opportunities Understand reseller preferences to provide them with the most relevant products Designing discount programs to help our resellers sell more Help resellers better recognise end-customer preferences to improve their revenue Use data to identify bottlenecks that will help our suppliers meet their SLA requirements Model seasonal demand to predict key organisational metrics Mentor junior data scientists in the team What You Will Need Bachelor's/Master's degree in computer science (or similar degrees) 2-4 years of experience as a Data Scientist in a fast-paced organization, preferably B2C Familiarity with Neural Networks, Machine Learning, etc Familiarity with tools like SQL, R, Python, etc. Strong understanding of Statistics and Linear Algebra Strong understanding of hypothesis/model testing and ability to identify common model testing errors Experience designing and running A/B tests and drawing insights from them Proficiency in machine learning algorithms Excellent analytical skills to fetch data from reliable sources to generate accurate insights Experience in tech and product teams is a plus Bonus points for: -Experience in working on personalization or other ML problems -Familiarity with Big Data tech stacks like Apache Spark, Hadoop, Redshift

Bachelor's/Master's degree in computer science (or similar degrees) 2-4 years of experience as a Data Scienti st in a fast-paced organizati on, preferably B2C Familiarity with Neural Networks, Machine Learning, etc Familiarity with tools like SQL, R, Python, etc. Strong understanding of Stati sti cs and Linear Algebra Strong understanding of hypothesis/model testi ng and ability to identi fy common model testi ng errors Experience designing and running A/B tests and drawing insights from them Proficiency in machine learning algorithms Excellent analyti cal skills to fetch data from reliable sources to generate accurate insights Experience in tech and product teams is a plus Bonus points for: -Experience in working on personalizati on or other ML problems -Familiarity with Big Data tech stacks like Apache Spark, Hadoop, Redshif if interested please contact at deblina.s@wengerwatson.com

Job Role Responsibility Description : We are looking for passionate, Strong experience with an entrepreneur mindset to join us as Hardcore Full Stack Data Scientist end-to-end single-handed multi-hat role who is already working in applied AI in ML, deep Learning, ANN, and CNN platform specifically working as single-handed doers or in a small Data Science Team with full end to end ownership of Data Science work commitment delivery as Data Scientist working in any reputed AI Data Science is driven Tech startup preferably in Healthcare. Required Skillsets : - Needs to have statistical, mathematical, and predictive modeling as well as business strategy skills to build the algorithms necessary to ask the right questions and find the right answers. - Need to be able to communicate their findings, orally and visually. - Need to understand how the products are developed and even more important, as big data touches the privacy of consumers, they need to have a set of ethical responsibilities.- - Need to have a natural desire to go beneath the surface of a problem. - Confident and self-secure as they more often than not will have to deal with situations where there is a lot of unknown. - Good knowledge & experience in Artificial Neural Network ( ANN ), AI conversational Chatbot & Needs to be able to write the required Algorithm and coding programming. - Preferably in different programming languages such as Python, Tensor Flow, Keras, AWS (ML and DL), Numpy, and Pytorch. In addition the need to be familiar with disciplines as follows : - Natural Language Processing, Machine learning, Conceptual modeling, Statistical analysis, Predictive Modeling, and Hypothesis testing. Data scientists should have at least some of the following capabilities : - Cleaning data, formatting data, Having the ability to query databases & perform statistical analysis, building AI Data Modelling, validating the AI Model, and deployment. - Being able to develop or program databases. - Having a good understanding of design & architecture principles. Qualification : B.Tech / M.Tech in CSE / Electrical / Electronics & Communication/ Maths & Computing /Statistics /BioTech/BioStat / Clinical Engineering in Data Science / Machine Learning from Top-rated Tech University / Top rated IIT /IIIT. Mandatory Requirement : Experience : - Post last qualification of at least 0 to 7 Years of strong experience exclusive in real Industry Projects in applied AI ML & Deep Learning Data Science in an early-stage AI Health startup at the role and designation as a single-handed full-stack Principal Data Scientist / Sr. Data Scientist. - Hardcore in ANN /Deep Learning /Machine Learning/NLP with at least 2-20 good Applied AI-oriented Applied Research Projects & applications with hardcore experience working on ANN, CNN, RNN, and deep learning in Digital Health startups to solve specific complex problems.

Job posting may be removed earlier if the position is filled or if a sufficient number of applications are received. Meet the Team We are a dynamic and innovative team of Data Engineers, Data Architects, and Data Scientists based in Bangalore, India. Our mission is to harness the power of data to provide actionable insights that empower executives to make informed, data-driven decisions. By analyzing and interpreting complex datasets, we enable the organization to understand the health of the business and identify opportunities for growth and improvement. Your Impact We are seeking a highly experienced and skilled Senior Data Scientist to join our dynamic team. The ideal candidate will possess deep expertise in machine learning models, artificial intelligence (AI), generative AI, and data visualization. Proficiency in Tableau and other visualization tools is essential. This role requires hands-on experience with databases such as Snowflake and Teradata, as well as advanced knowledge in various data science and AI techniques. The successful candidate will play a pivotal role in driving data-driven decision-making and innovation within our organization. Key Responsibilities Design, develop, and implement advanced machine learning models to solve complex business problems. Apply AI techniques and generative AI models to enhance data analysis and predictive capabilities. Utilize Tableau and other visualization tools to create insightful and actionable dashboards for stakeholders. Manage and optimize large datasets using Snowflake and Teradata databases. Collaborate with cross-functional teams to understand business needs and translate them into analytical solutions. Stay updated with the latest advancements in data science, machine learning, and AI technologies. Mentor and guide junior data scientists, fostering a culture of continuous learning and development. Communicate complex analytical concepts and results to non-technical stakeholders effectively. Key Technologies & Skills: Machine Learning ModelsSupervised learning, unsupervised learning, reinforcement learning, deep learning, neural networks, decision trees, random forests, support vector machines (SVM), clustering algorithms, etc. AI TechniquesNatural language processing (NLP), computer vision, generative adversarial networks (GANs), transfer learning, etc. Visualization ToolsTableau, Power BI, Matplotlib, Seaborn, Plotly, etc. DatabasesSnowflake, Teradata, SQL, NoSQL databases. Programming LanguagesPython (essential), R, SQL. Python LibrariesTensorFlow, PyTorch, scikit-learn, pandas, NumPy, Keras, SciPy, etc. Data ProcessingETL processes, data warehousing, data lakes. Cloud PlatformsAWS, Azure, Google Cloud Platform. Minimum Qualifications Bachelor's or Master's degree in Computer Science, Statistics, Mathematics, Data Science, or a related field. Minimum of [X] years of experience as a Data Scientist or in a similar role. Proven track record in developing and deploying machine learning models and AI solutions. Strong expertise in data visualization tools, particularly Tableau. Extensive experience with Snowflake and Teradata databases. Excellent problem-solving skills and the ability to work independently and collaboratively. Exceptional communication skills with the ability to convey complex information clearly. Preferred Qualifications (Provide up to five (5) bullet points these can include soft skills) Excellent communication and collaboration skills to work effectively in cross-functional teams. Ability to translate business requirements into technical solutions. Strong problem-solving skills and the ability to work with complex datasets. Experience in statistical analysis and machine learning techniques. Understanding of business domains such as sales, financials, marketing, and telemetry.

Data Scientist with 5+ years of experience.

Role : MLOps Engineer Location : Remote(INDIA) Contract : 6-12 Months Interview : Video MLOps Engineer Skillset: Kubernetes, AKS, Azure cloud, Azure DevOps, Databricks Nice to have: MLOps, ML Infrastructure deployments Description: We are looking for an experienced Machine Learning Operations Engineer who has experience working with design, development and implementation of AI/ML applications and managing the lifecycle of Machine Learning models. The role of an MLOps Engineer is at intersection of Data Scientist, Data Engineer, and DevOps Engineer. You'll be working in a team of engineers that takes on a wide array of responsibilities that encompass building all the infrastructure necessary to take a trained ML Model , integrate and deploy, making it available to other applications. Job Responsibilities: Design and deploy scalable infrastructure for ML workloads using cloud platforms and containerization technologies (e.g., Docker, Kubernetes) Work with teams to design and build cloud hosted, automated pipelines that run, monitor, and retrain ML Models for business applications Design and implement Model and Pipeline validation procedures alongside teams of Data Scientists, Data Engineers, and other ML Engineers Optimize and refactor development code so that it can be moved to production Build Data, Feature Engineering Pipelines for new and existing models Assemble configurations and specifications to automatically build environments in production Create and develop in CI/CD Pipelines which allow for controlled and continuous enhancement of existing work and new features during both development and production phases

Lead end-to-end development of ML/DL models from data preprocessing to model deployment. Design and implement advanced solutions using computer vision, NLP, and generative AI models (e.g., Transformers, GANs). Apply and experiment with agentic AI approaches to build autonomous decision-making systems. Collaborate with engineering, product, and business stakeholders to align AI solutions with business outcomes. Work with large-scale datasets and implement MLOps pipelines for automated training, evaluation, and deployment on cloud (Azure preferred). Stay up to date with the latest AI research and apply state-of-the-art techniques in production systems. Mentor junior data scientists and contribute to AI knowledge sharing across teams. Required Skills & Qualifications: 8+ years of industry experience in data science, ML, or AI, with demonstrated project ownership. Proficiency in Python and frameworks like TensorFlow, PyTorch, OpenCV, scikit-learn, etc. Strong background in generative models (e.g., LLMs, GANs, VAEs) and foundational ML techniques. Expertise in computer vision, including object detection, image classification, and segmentation. Experience in implementing agentic AI systems using modern orchestration tools and frameworks. Hands-on experience with Azure AI services (e.g., Azure ML, Cognitive Services, Azure OpenAI, Azure Blob for data handling). Solid understanding of MLOps practices (CI/CD, version control, model registry, monitoring). Strong analytical, problem-solving, and communication skills. Preferred Qualifications: Master s in Computer Science, Data Science, or a related field. Experience working in cloud-native AI environments (Azure, AWS, or GCP). Exposure to vector search engines, knowledge graphs, and retrieval-augmented generation (RAG). Publications, patents, or active participation in AI communities or open-source contributions.

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

Role & responsibilities The objective of the position The primary responsibility of this position is to ensure data quality, generate data insights, and ongoing refinement of algorithms, rule engines, and models for improving business decision-making and outcomes. Major Deliverables Ensuring Data Quality: Processing, cleansing, and verifying the integrity of data used for analysis through Involvement in Designing Digital Data Collection Strategy Reporting Missing and Incorrect Data Outlier Analysis etc. Should involve and suggest procedures for the collection, editing, and verification of data. Data-driven decision-making and analytics. Support development and continual improvement of credit decision-making algorithms and rule engines using advanced statistical methods and ML Explore data for insights, use statistical analysis and machine learning algorithms to identify relationships and trends in data and support business decision-making Develop propensity and predictive models Data Visualization & Communication: Not only interpret data but also effectively communicate findings to other stakeholders using relevant tools (e.g. Visualization tools like Tableau / powerBI etc.) so they can make data-informed decisions. Cross-functional Engagement: Collaborate with both IT and business stakeholders to ascertain business needs and identify opportunities for leveraging company data to drive business solutions. Preferred candidate profile Good understanding of Statistical Concepts in data science. Experience in BFSI industry/domain. Well-versed with the business processes Database Knowledge and experience in RDBMS concepts preferably SQL/MySQL Strong knowledge on ML/DL Data models, Data Sets, and ability to utilize data from varied sources for Analysis. Strong Expertise in Statistical techniques, predictive and prescriptive analysis, Regression, Classification, Yolo, and Computer vision. Minimum 1 year of professional experience in Deep learning, Computer vision, and NLP. Strong knowledge in Programming languages preferably Python. Know how to use automated ML tools and Azure Cloud Services. Basic knowledge of Generative AI and LLms. Experience in server Deployment with Flask, Django Frameworks Qualification Postgraduate with educational background in Mathematics/Statistics/Data Analytics. Academics in Data Analytics or equivalent programmers will be an added advantage.

Role & responsibilities Role: Data Scientist Location: Bangalore/Chennai Experience Level: Bachelors/Master’s degree in Data Science, Computer Science, Statistics, Mathematics, or a related field from a reputed institute. Position overview: We are seeking a Data Scientist with a strong background in Machine Learning, Natural Language Processing (NLP), Generative AI, and Retrieval-Augmented Generation (RAG). The ideal candidate will possess 1+ years of hands-on experience in developing and deploying advanced data-driven solutions. You will play a key role in our AI-CoE team, contributing to cutting-edge projects that drive innovation and business value. A special focus area for this role would be to build AI enabled products that would result in the creation of monetizable product differentiators for Tata Communications products and services. Detailed job description & Key Responsibilities: Develop, Test, and Deploy machine learning models for various business and Telco use cases. Perform data preprocessing, feature engineering and ML/DL model evaluation. Optimize and fine-tune models for performance and scalability. Good understanding of NLP concepts and projects involving entity recognition, text classification, and language modelling like GPT/Llama/Claude/Grok Build and refine RAG models to improve information retrieval and answer generation systems. Integrate RAG methods into existing applications to enhance data accessibility and user experience. Work closely with cross-functional teams including software engineers, product managers, and domain experts. Communicate technical concepts to non-technical stakeholders effectively. Document processes, methodologies, and model development for internal and external stakeholders. Skills: Strong knowledge of probability and statistics. Working knowledge of machine learning and deep learning skills. Strong knowledge of programming knowledge – Python, SQL and commonly used frameworks & tools – PyTorch, Sci-kit, NumPy, Gen AI tools like langchain/llamaIndex Working knowledge of MLOPs principles and implementing projects with Big Data in batch and streaming mode. Excellent problem-solving skills and a proactive attitude. Strong communication and teamwork abilities. Ability to manage multiple projects and meet deadlines Interview will involve coding tests.