2627 Data Science Jobs - Page 42

Job Description With excellent analytical and problem-solving skills, you should understand business problems of the customers, translate them into scope of work and technical specifications for developing into Data Science projects. Efficiently utilize cutting edge technologies in AI, Generative AI areas and implement solutions for business problems. Good exposure technology platforms for Data Science, AI, Gen AI, cloud with implementation experience. Ability to provide end to end technical solutions leveraging latest AI, Gen AI tools, frameworks for the business problems. This Job requires the following: Designing, developing, and implementing end-to-end machine learning production pipelines (data exploration, sampling, training data generation, feature engineering, model building, and performance evaluation) Deep experience in predictive analytics and statistical modeling Deep experience in successfully making use of the following: Logistic Regression Multivariate Regression, Support Vector Machines, Stochastic Processes, Decision Trees, Lifetime analysis, common clustering algorithms, Optimization, CNN Essential Qualifications B-Tech or BE - computer / IT or MCA or MSC- Computer Science along with necessary certifications is preferred Technical Qualifications (Essential) At least 2 to 3 ML apps deployed in production At least 1 to 2 Gen AI apps in production. Experience in Computer vision is a must. Core ML experience is a must Hands-on programming experience Hands-on technical design experience Hands-on prompt engineering experience At least 3 Data Science, AI Projects designed, developed and delivered to production At least 1 Generative AI Project designed, developed and delivered to production Primary Skills Hands-on coding experience in Python, PyTorch, Spark/PySpark, SQL, TensorFlow, NLP Frameworks and similar tools/frameworks Good understanding of business and domain of the applications Hands-on experience in design and development of Gen AI applications using Open Source LLMs and cloud platforms Hands-on experience in design and development of API based applications for AI and Data Science Projects Expertise in GenAI concepts, RAG and Models fine-tuning techniques Understand the concepts of major AI models such as OpenAI, Llama, Hugging Face, Mistral AI etc., and implementation experience Understanding of DevOps pipelines for deployment Good understanding of Data Engineering lifecycle data pipelines, data warehouse, data lake Secondary Skills End to end data engineering project experience using Databricks and Azure Data platform Knowledge of any configuration management tools is desirable Familiarity with containerization and container orchestration services like Docker and Kubernetes Description of Responsibility Sills / Competencies requirement Functional & Technical Responsibilities Understand customers requirements (Business, Functional, Non-Functional etc.,), conduct feasibility study and develop technical specifications for Data Science, AI and Gen AI Projects Design and implement scalable solutions for Data Science, AI and Gen AI Projects using major technology and computing platforms (open source and cloud) Possess excellent analytical and problem-solving skills and be able to understand various forms of data, patterns and derive insights. Should be able to develop efficient Prompts to automate project activities using LLM tools and provide end to end solutions Provide Generative AI solutions for the business/automation requirements using open source LLMs (Open AI, Llama, Mistral etc.,) Collaborate internal and external stakeholders for deriving solution that requires cross functional teams and smoother execution of the projects Provide technical solutions to sales, pre-sales teams for the proposals Develop and guide team members in implementation of solutions related to Data Science, AI and Gen AI Projects Expert knowledge of data modeling and understanding of different data structures Experience with design of AI/ML solutions either as standalone or integrated with other applications Research Orientation Proactive & Clear Communication Collaboration Solution Orientation Solution Articulation Accountability Adaptability / Flexibility Analytical Skills Listening Skills Customer Service Orientation

Responsibilities: Design and develop AI models and algorithms. Build and train ML systems. Process large datasets. Deploy models to production. Collaborate with teams to integrate AI solutions. Ensure model accuracy. Stay updated with AI trends. Health insurance Leave encashment Maternity leaves Paternity leaves Course reimbursements Capability building program Prevention of sexual harrassment policy

ABOUT THE ROLE Role Description: The Data Scientist is responsible for developing and implementing AI-driven solutions to enhance cybersecurity measures within the organization. This role involves leveraging data science techniques to analyze security data, detect threats, and automate security processes. The Data Scientist will work closely with cybersecurity teams to identify data-driven automation opportunities, strengthening the organizations security posture . Roles & Responsibilities: Develop analytics to address security concerns, enhancements, and capabilities to improve the organization's security posture. Collaborate with Data Engineers to translate security-focused algorithms into effective solutions. Work in technical teams in development, deployment, and application of applied analytics, predictive analytics, and prescriptive analytics. Perform exploratory and targeted data analyses using descriptive statistics and other methods to identify security patterns and anomalies. Design and implement security-focused analytics pipelines leveraging MLOps practices. Collaborate with data engineers on data quality assessment, data cleansing, and the development of security-related data pipelines. Contribute to data engineering efforts to refine data infrastructure and ensure scalable, efficient security analytics. Generate reports, annotated code, and other projects artifacts to document, archive, and communicate your work and outcomes. Share and discuss findings with team members practicing SAFe Agile delivery model. Functional Skills: Basic Qualifications: Masters degree and 1 to 3 years of experience with one or more analytic software tools or languages (e.g., SAS, SPSS, R, Python) OR Bachelors degree and 3 to 5 years of experience with one or more analytic software tools or languages (e.g., SAS, SPSS, R, Python) OR Diploma and 7 to 9 years of experience with one or more analytic software tools or languages (e.g., SAS, SPSS, R, Python) Preferred Qualifications: Experience with one or more analytic software tools or languages (e.g., SAS, SPSS, R, Python) Demonstrated skill in the use of applied analytics, descriptive statistics, feature extraction and predictive analytics on industrial datasets Strong foundation in machine learning algorithms and techniques Experience in statistical techniques and hypothesis testing, experience with regression analysis, clustering and classification Good-to-Have Skills: Proficiency in Python and relevant ML libraries (e.g., TensorFlow, PyTorch, Scikit-learn) Outstanding analytical and problem-solving skills; Ability to learn quickly; Excellent communication and interpersonal skills Experience with data engineering and pipeline development Experience in analyzing time-series data for forecasting and trend analysis Experience with AWS, Azure, or Google Cloud Experience with Databricks platform for data analytics and MLOps Experience with Generative AI models (e.g., GPT, DALLE, Stable Diffusion) and their applications in cybersecurity and data analysis Experience working in Product team's environment Experience working in an Agile environment Professional Certifications: Any AWS Developer certification (preferred) Any Python and ML certification (preferred) Any SAFe Agile certification (preferred) Soft Skills: Initiative to explore alternate technology and approaches to solving problems Skilled in breaking down problems, documenting problem statements, and estimating efforts Excellent analytical and troubleshooting skills Strong verbal and written communication skills Ability to work effectively with global, virtual teams High degree of initiative and self-motivation Ability to manage multiple priorities successfully Team-oriented, with a focus on achieving team goals.

What you will do In this vital role you will identify trends, root causes, and potential improvements in our products and processes, ensuring that patient voices are heard and addressed with utmost precision. As the Sr Associate Data Scientist at Amgen, you will be responsible for developing and deploying basic machine learning, operational research, semantic analysis, and statistical methods to uncover structure in large data sets. This role involves creating analytics solutions to address customer needs and opportunities. Collect, clean, and manage large datasets related to product performance and patient complaints. Ensure data integrity, accuracy, and accessibility for further analysis. Develop and maintain databases and data systems for storing patient complaints and product feedback. Analyze data to identify patterns, trends, and correlations in patient complaints and product issues. Use advanced statistical methods and machine learning techniques to uncover insights and root causes. Develop analytics or predictive models to foresee potential product issues and patient concerns to address customer needs and opportunities. Prepare comprehensive reports and visualizations to communicate findings to key collaborators. Present insights and recommendations to cross-functional teams, including product development, quality assurance, and customer service. Collaborate with regulatory and compliance teams to ensure adherence to healthcare standards and regulations. Find opportunities for product enhancements and process improvements based on data analysis. Work with product complaint teams to implement changes and monitor their impact. Stay abreast of industry trends, emerging technologies, and standard methodologies in data science and healthcare analytics. Evaluate data to support product complaints. Work alongside software developers and software engineers to translate algorithms into commercially viable products and services. Work in technical teams in development, deployment, and application of applied analytics, predictive analytics, and prescriptive analytics. Perform exploratory and targeted data analyses using descriptive statistics and other methods. Work with data engineers on data quality assessment, data cleansing and data analytics Generate reports, annotated code, and other projects artifacts to document, archive, and communicate your work and outcomes. Basic Qualifications: Masters degree and 1 to 3 years of Data Science and with one or more analytic software tools or languages, and data visualization tools experience OR Bachelors degree and 3 to 5 years of Data Science and with one or more analytic software tools or languages, and data visualization tools experience OR Diploma and 7 to 9 years of Data Science and with one or more analytic software tools or languages, and data visualization tools experience Preferred Qualifications: Demonstrated skill in the use of applied analytics, descriptive statistics, feature extraction and predictive analytics on industrial datasets. Experience in statistical techniques and hypothesis testing, experience with regression analysis, clustering and classification. Experience in analyzing time-series data for forecasting and trend analysis. Experience with Data Bricks platform for data analytics. Experience working with healthcare data, including patient complaints, product feedback, and regulatory requirements.

Job description We are having a F2F weekend drive for the requirement of a Data Scientist + Gen AI at our LTIM Bangalore Whitefield office. Date - 14th June 2025 Experience - 6+ Years Mandatory Skills - Data Science, Gen AI, Python, RAG and Azure/AWS, AI/ML, NLP Location - LTIMindtree Bangalore Whitefield Office Secondary - (Any) Machine Learning, Deep Learning, ChatGPT, Langchain, Prompt, vector stores, RAG, llama, Computer vision, Deep learning, Machine learning, OCR, Transformer, regression, forecasting, classification, hyper parameter tunning, MLOps, Inference, Model training, Model Deployment Generic JD- More than 6 years of experience in Data Engineering, Data Science and AI / ML domain Excellent understanding of machine learning techniques and algorithms, such as GPTs, CNN, RNN, k-NN, Naive Bayes, SVM, Decision Forests, etc. Experience using business intelligence tools (e.g. Tableau, PowerBI) and data frameworks (e.g. Hadoop) Experience in Cloud native skills. Knowledge of SQL and Python; familiarity with Scala, Java or C++ is an asset Analytical mind and business acumen and Strong math skills (e.g. statistics, algebra) Experience with common data science toolkits, such as TensorFlow, KERAs, PyTorch, PANDAs, Microsoft CNTK, NumPy etc. Deep expertise in at least one of these is highly desirable. Experience with NLP, NLG and Large Language Models like BERT, LLaMa, LaMDA, GPT, BLOOM, PaLM, DALL-E, etc. Great communication and presentation skills. Should have experience in working in a fast-paced team culture. Experience with AIML and Big Data technologies like AWS SageMaker, Azure Cognitive Services, Google Colab, Jupyter Notebook, Hadoop, PySpark, HIVE, AWS EMR etc. Experience with NoSQL databases, such as MongoDB, Cassandra, HBase, Vector databases Good understanding of applied statistics skills, such as distributions, statistical testing, regression, etc. Should be a data-oriented person with analytical mind and business acumen.

Job Title: AI Engineer Consultant Key Responsibilities: We are seeking a highly skilled and experienced AI Engineer Consultant to join our Business Development (BD) team and provide Subject Matter Expertise (SME) in Artificial Intelligence. The ideal candidate will have at least 7 years of experience in AI development and deployment, along with the ability to bridge technical expertise and business requirements. This role requires an individual who can help shape business solutions by collaborating with cross-functional teams, understanding market needs, and translating them into scalable, technical AI solutions. Consulting Expertise: Provide AI/ML subject matter expertise to the BD team, helping to define and refine business requirements and solutions that align with client needs. Technical Leadership: Lead the development and implementation of AI models, algorithms, and frameworks, ensuring they meet business objectives and technical feasibility. Collaborative Solution Design: Work closely with both technical and non-technical stakeholders to translate business goals into actionable AI solutions. Help refine technical specifications based on client and internal feedback. Client Interaction: Act as a technical advisor during client discussions, helping explain complex AI concepts in a clear, accessible manner. Business Requirements Gathering: Collaborate with the BD team to gather and prioritize business requirements, turning them into scalable AI solutions that can be effectively marketed and deployed. Proposal Support: Provide support in crafting proposals, RFP responses, and project documentation that reflect a deep understanding of AI technologies and their business applications. Qualifications: Experience: At least 7 years of hands-on experience in AI, machine learning, and data science, with a strong portfolio of successful projects in these domains. Technical Skills: Expertise in AI/ML algorithms, programming languages (Python, R, Java, etc.), data analysis tools, and frameworks (TensorFlow, PyTorch, Scikit-learn, etc.). Business Acumen: Strong ability to translate complex technical information into clear business requirements and solutions. Experience in client-facing roles is a plus. Problem-Solving: Ability to quickly analyze problems and design practical, cost-effective AI solutions. Communication Skills: Excellent communication skills, both written and verbal. Experience explaining complex AI concepts to non-technical stakeholders and decision-makers. Consulting Experience: Previous experience working in a consulting or advisory role, especially in helping businesses adopt AI-driven solutions. Desirable Skills: Experience with AI applications in industries such as healthcare, finance, or retail. Familiarity with cloud platforms (AWS, Google Cloud, Azure) and deployment of AI solutions in cloud environments. Advanced degree (MS, PhD) in AI, Machine Learning, Data Science, or related fields is a plus. This is an exciting opportunity for a results-driven professional. If you have a passion, we encourage you to apply. Apply Now: Drop your resume on 8308907577 or kmaran@sevenmentor.com . References are highly appreciated!

ABOUT THE ROLE Role Description: We are seeking an accomplished and visionary Data Scientist/ GenAI developer to join Amgens Enterprise Data Management team. As part of MDM team, you will be responsible for design ing , develop ing , and deploy ing Generative AI and ML models to power data-driven decisions across business domains. This role is ideal for an AI practitioner who thrives in a collaborative environment and brings a strategic mindset to applying advanced AI techniques to solve real-world problems. To succeed in this role, the candidate must have strong AI/ML, Data Science , GenAI experience along with MDM knowledge, hence the candidates having only MDM experience are not eligible for this role. Candidate must have AI/ML, data science and GenAI experience on technologies like ( PySpark / PyTorch , TensorFlow, LLM , Autogen , Hugging FaceVectorDB , Embeddings, RAGs etc ), along with knowledge of MDM (Master Data Management) Roles & Responsibilities: Develop enterprise-level GenAI applications using LLM frameworks such as Langchain, Autogen, and Hugging Face. Design and develop intelligent pipelines using PySpark, TensorFlow, and PyTorch within Databricks and AWS environments. Implement embedding models andmanage VectorStores for retrieval-augmented generation (RAG) solutions. Integrate and leverage MDM platforms like Informatica and Reltio to supply high-quality structured data to ML systems. Utilize SQL and Python for data engineering, data wrangling, and pipeline automation. Build scalable APIs and services to serve GenAI models in production. Lead cross-functional collaboration with data scientists, engineers, and product teams to scope, design, and deploy AI-powered systems. Ensure model governance, version control, and auditability aligned with regulatory and compliance expectations. Basic Qualifications and Experience: Masters degree with 4 - 6 years of experience in Business, Engineering, IT or related field OR Bachelors degree with 6 - 9 years of experience in Business, Engineering, IT or related field OR Diploma with 10 - 12 years of experience in Business, Engineering, IT or related field Functional Skills: Must-Have Skills: 6+ years of experience working in AI/ML or Data Science roles, including designing and implementing GenAI solutions. Extensive hands-on experience with LLM frameworks and tools such as Langchain, Autogen, Hugging Face, OpenAI APIs, and embedding models. Strong programming background with Python, PySpark, and experience in building scalable solutions using TensorFlow, PyTorch, and SK-Learn. Proven track record of building and deploying AI/ML applications in cloud environments such as AWS. Expertise in developing APIs, automation pipelines, and serving GenAI models using frameworks like Django, FastAPI, and DataBricks. Solid experience integrating and managing MDM tools (Informatica/Reltio) and applying data governance best practices. Guide the team on development activities and lead the solution discussions Must have core technical capabilities in GenAI, Data Science space Good-to-Have Skills: Prior experience in Data Modeling, ETL development, and data profiling to support AI/ML workflows. Working knowledge of Life Sciences or Pharma industry standards and regulatory considerations. Proficiency in tools like JIRA and Confluence for Agile delivery and project collaboration. Familiarity with MongoDB, VectorStores, and modern architecture principles for scalable GenAI applications. Professional Certifications : Any ETL certification (e.g. Informatica) Any Data Analysis certification (SQL) Any cloud certification (AWS or AZURE) Data Science and ML Certification Soft Skills: Strong analytical abilities to assess and improve master data processes and solutions. Excellent verbal and written communication skills, with the ability to convey complex data concepts clearly to technical and non-technical stakeholders. Effective problem-solving skills to address data-related issues and implement scalable solutions. Ability to work effectively with global, virtual teams.

We're hiring a Lead AI Engineer (Remote/Nashik) to build & lead AI/ML & LLM solutions. 7+ yrs exp, strong in Python, LLMs, AWS, MLOps, vector DBs. Bonus: voice AI, agents, open-source. Team Leading Experience is Mandatory Apply: hr@insnapsys.com. Work from home House rent allowance

Machine Learning, Deep Learning models, Data Science. (Important);-R / python programming (mandatory) ;- Fast API development ;- deployment of models experience ; - any cloud Azure (good to have - for this requirement); - basics of Generative AI , NLP (optional - Good to have) GIS data, Geospatial data, Google Maps, ArcGIS, Demand pattern analysis 5 to 15 Yrs Bangalore

Job Summary Person at this position takes ownership of a module and associated quality and delivery. Person at this position provides instructions, guidance and advice to team members to ensure quality and on time delivery. Person at this position is expected to be able to instruct and review the quality of work done by technical staff. Person at this position should be able to identify key issues and challenges by themselves, prioritize the tasks and deliver results with minimal direction and supervision. Person at this position has the ability to investigate the root cause of the problem and come up alternatives/ solutions based on sound technical foundation gained through in-depth knowledge of technology, standards, tools and processes. Person has the ability to organize and draw connections among ideas and distinguish between those which are implementable. Person demonstrates a degree of flexibility in resolving problems/ issues that atleast to in-depth command of all techniques, processes, tools and standards within the relevant field of specialisation. Roles & Responsibilities Responsible for requirement analysis and feasibility study including system level work estimation while considering risk identification and mitigation. Responsible for design, coding, testing, bug fixing, documentation and technical support in the assigned area. Responsible for on time delivery while adhering to quality and productivity goals. Responsible for traceability of the requirements from design to delivery Code optimization and coverage. Responsible for conducting reviews, identifying risks and ownership of quality of deliverables. Responsible for identifying training needs of the team. Expected to enhance technical capabilities by attending trainings, self-study and periodic technical assessments. Expected to participate in technical initiatives related to project and organization and deliver training as per plan and quality. Expected to be a technical mentor for junior members. Person may be given additional responsibility of managing people based on discretion of Project Manager. Education and Experience Required Engineering graduate, MCA, etc Experience: 5-8 years Competencies Description Data Science TCB is applicable to one who 1) Analyses data to arrive at patterns/Insights/models 2) Come up with models based on the data to provide recommendations, predictive analytics etc 3) Provides implementation of the models in R, Matlab etc 4) Can understand and apply machine learning/AI techniques Platforms- Unix Tools- R, Matlab, Spark Machine Learning, Python-ML, SPSS, SAS Languages- R, Perl, Python, Scala Specialization- COGNITIVE ANALYTICS INCLUDING COMPUTER VISION, AI and ML, STATISTICS

ABOUT THE ROLE Role Description: We are seeking an accomplished and visionary Data Scientist/ GenAI developer to join Amgens Enterprise Data Management team. As part of MDM team, you will be responsible for design ing , develop ing , and deploy ing Generative AI and ML models to power data-driven decisions across business domains. This role is ideal for an AI practitioner who thrives in a collaborative environment and brings a strategic mindset to applying advanced AI techniques to solve real-world problems. To succeed in this role, the candidate must have strong AI/ML, Data Science , GenAI experience along with MDM knowledge, hence the candidates having only MDM experience are not eligible for this role. Candidate must have AI/ML, data science and GenAI experience on technologies like ( PySpark / PyTorch , TensorFlow, LLM , Autogen , Hugging FaceVectorDB , Embeddings, RAGs etc ), along with knowledge of MDM (Master Data Management) Roles & Responsibilities: Develop enterprise-level GenAI applications using LLM frameworks such as Langchain, Autogen, and Hugging Face. Design and develop intelligent pipelines using PySpark, TensorFlow, and PyTorch within Databricks and AWS environments. Implement embedding models andmanage VectorStores for retrieval-augmented generation (RAG) solutions. Integrate and leverage MDM platforms like Informatica and Reltio to supply high-quality structured data to ML systems. Utilize SQL and Python for data engineering, data wrangling, and pipeline automation. Build scalable APIs and services to serve GenAI models in production. Lead cross-functional collaboration with data scientists, engineers, and product teams to scope, design, and deploy AI-powered systems. Ensure model governance, version control, and auditability aligned with regulatory and compliance expectations. Basic Qualifications and Experience: Masters degree with 4 - 6 years of experience in Business, Engineering, IT or related field OR Bachelors degree with 6 - 9 years of experience in Business, Engineering, IT or related field OR Diploma with 10 - 12 years of experience in Business, Engineering, IT or related field Functional Skills: Must-Have Skills: 6+ years of experience working in AI/ML or Data Science roles, including designing and implementing GenAI solutions. Extensive hands-on experience with LLM frameworks and tools such as Langchain, Autogen, Hugging Face, OpenAI APIs, and embedding models. Strong programming background with Python, PySpark, and experience in building scalable solutions using TensorFlow, PyTorch, and SK-Learn. Proven track record of building and deploying AI/ML applications in cloud environments such as AWS. Expertise in developing APIs, automation pipelines, and serving GenAI models using frameworks like Django, FastAPI, and DataBricks. Solid experience integrating and managing MDM tools (Informatica/Reltio) and applying data governance best practices. Guide the team on development activities and lead the solution discussions Must have core technical capabilities in GenAI, Data Science space Good-to-Have Skills: Prior experience in Data Modeling, ETL development, and data profiling to support AI/ML workflows. Working knowledge of Life Sciences or Pharma industry standards and regulatory considerations. Proficiency in tools like JIRA and Confluence for Agile delivery and project collaboration. Familiarity with MongoDB, VectorStores, and modern architecture principles for scalable GenAI applications. Professional Certifications : Any ETL certification (e.g. Informatica) Any Data Analysis certification (SQL) Any cloud certification (AWS or AZURE) Data Science and ML Certification Soft Skills: Strong analytical abilities to assess and improve master data processes and solutions. Excellent verbal and written communication skills, with the ability to convey complex data concepts clearly to technical and non-technical stakeholders. Effective problem-solving skills to address data-related issues and implement scalable solutions. Ability to work effectively with global, virtual teams We will ensure that individuals with disabilities are provided with reasonable accommodation to participate in the job application or interview process, to perform essential job functions, and to receive other benefits and privileges of employment. Please contact us to request accommodation.

Role & responsibilities As an AI Solution Architect, you will be responsible for designing, developing, and implementing AI solutions that address complex business challenges. You will work closely with cross-functional teams to ensure the successful integration of AI technologies into our products and services. Preferred candidate profile Bachelors degree in computer science, Engineering, Data Science, or a related field or equivalent experience. Advanced degrees and certifications in AI, Machine Learning, or related areas are preferred. 7+ years of experience in Product, Artificial Intelligence (AI). Demonstrated experience in AI consulting, AI solution design, implementation, and deployment. Familiarity with AI industry trends and use cases. Experience in a client-facing role is necessary. 5+ years of experience. Understanding business processes related to Asset Management, Retail, Advisory, Retirement, Wealth, Insurance. Experience in product lifecycle processes, including product research, market research, competitive analysis, planning positioning, roadmap development, requirements definition, and product launches and go-to-market strategies. Experience in project management, with the ability to manage multiple projects simultaneously and deliver results within deadlines. Comprehensive knowledge of AI technologies, including machine learning algorithms, data analytics, natural language processing, and computer vision. Proficiency in programming languages such as Python, R, or Java. Strong analytical and problem-solving abilities to evaluate client requirements and develop effective AI strategies. Excellent written and verbal communication skills, with the ability to convey business needs to technical solutions and articulate to stakeholders. Job Level - Individual Contributor Work Shift Timings - 2:00 PM - 11:00 PM IST

We only hire from Top Tier Universities including IITs, BITS, DCE/NSIT, ISI, Top NITs etc. This role is only suitable for candidates with between 1 to 4 years experience. People with more than 4 years of experience need not apply. This is an URGENT requirement. We are hiring for a UK based Fintech company (name is kept confidential). The company is seeking an early stage Data Scientist to join the team and support the design, development, and Machine Learning and AI use-cases. Your work will directly support strategic initiatives and improve business outcomes. Job Summary : We are seeking a motivated Data Scientist to join our Data and AI team. The ideal candidate will assist in analysing complex datasets, building predictive models, and contributing to data-driven decision-making. This entry-level role is perfect for someone eager to apply their technical skills and grow in a collaborative, innovative environment. Key Responsibilities : Collect, clean, and preprocess structured and unstructured data from various sources Perform exploratory data analysis (EDA) to identify trends, patterns, and insights Develop, test, and deploy basic machine learning models under senior team guidance Create visualisations and dashboards to communicate findings to stakeholders Collaborate with cross-functional teams (e.g., product, engineering) to support business objectives Assist in maintaining data pipelines and ensuring data quality Stay updated on industry trends and emerging tools in data science Qualifications : Bachelors degree in data science, Computer Science, Statistics, Mathematics, or a related field 1-3 years of experience in data science or a related role (internships or academic projects count) Proficiency in Python for data analysis (e.g., pandas, NumPy, scikit-learn) Strong analytical and problem-solving skills Excellent communication skills to explain technical concepts to non-technical audiences. Understanding of machine learning algorithms (e.g., regression, classification, clustering). Nice to Have: Internship or project experience in data science or analytics Exposure to Gen AI architectures (RAG, MCP etc.) Experience working with cloud platforms (e.g., AWS, GCP, Azure) Experience with SQL for data querying Knowledge of version control (e.g., Git)

Design & develop end-to-end machine learning models & GenAI workflows Fetch & process data from BigQuery & various sources for model development Build & deploy models using Python & frameworks like Scikit Learn, XGBoost/CatBoost, TensorFlow & Gemini Required Candidate profile 4+ years of experience in the Data Science domain and should have hands on exp in Python, Machine Learning and/or Generative AI (Artificial Intelligence) This is an Individual contributor role

5+ years of experience in Python programing and performance tuning and optimization. Experience on ML engineering, Knowledge on Feast, Kubeflow and MLFlow. Deep understanding on NumPy , Pandas, data frames etc. Working knowledge on bigdata environment and data science model added advantage. Strong analytical and problem-solving skills, with attention to detail and ability to work in a fast-paced environment Excellent communication and collaboration skills, with ability to work with cross-functional teams Knowledge of machine learning and data science concepts

Job Details: We are seeking a highly motivated and enthusiastic Junior Data Scientist with 2-3 years of experience to join our data science team. This role offers an exciting opportunity to contribute to both traditional Machine Learning projects for our commercial IoT platform and cutting-edge Generative AI initiatives. Experience 2-3 years of hands-on experience with machine learning Exposure to Generative AI concepts and techniques, such as Large Language Models (LLMs), RAG Architecture Experience in manufacturing and with an IoT platform is preferable Role and Responsibilities: Key Objectives Machine Learning (ML): Assist in the development and implementation of machine learning models using frameworks such as TensorFlow, PyTorch, or scikit-learn. Help with Python development to integrate models with the overall application Monitor and evaluate model performance using appropriate metrics and techniques. Generative AI: Build Gen AI-based tools for various business use cases by fine-tuning and adapting pre-trained generative models Support the exploration and experimentation with Generative AI models Research & Learning: Stay up-to-date with the latest advancements and help with POCs Proactively research and propose new techniques and tools to improve our data science capabilities. Collaboration and Communication: Work closely with cross-functional teams, including product managers, engineers, and business stakeholders, to understand requirements and deliver impactful solutions. Communicate findings, model performance, and technical concepts to both technical and non-technical audiences. Technical Competencies Programming: Proficiency in Python, with experience in libraries like numpy, pandas, and matplotlib for data manipulation and visualization. ML Frameworks: Experience with TensorFlow, PyTorch, or scikit-learn. Cloud & Deployment: Basic understanding of cloud platforms such as Databricks, Google Cloud Platform (GCP), or Microsoft Azure for model deployment. Data Processing & Evaluation: Knowledge of data preprocessing, feature engineering, and evaluation metrics such as accuracy, F1-score, and RMSE.

About this role: Wells Fargo is seeking a senior Software Engineer - Adobe Experience Platform (AEP) In this role, you will: Lead moderately complex initiatives and deliverables within technical domain environments Contribute to large scale planning of strategies Design, code, test, debug, and document for projects and programs associated with technology domain, including upgrades and deployments Review moderately complex technical challenges that require an in-depth evaluation of technologies and procedures Resolve moderately complex issues and lead a team to meet existing client needs or potential new clients needs while leveraging solid understanding of the function, policies, procedures, or compliance requirements Collaborate and consult with peers, colleagues, and mid-level managers to resolve technical challenges and achieve goals Lead projects and act as an escalation point, provide guidance and direction to less experienced staff Required Qualifications: 4+ years of Software Engineering experience, or equivalent demonstrated through one or a combination of the following: work experience, training, military experience, education Desired Qualifications : 4+years of overall IT experience and at least 3 years of experience in developing digital marketing / digital analytics solutions using Adobe products. Minimum 2 years experience in Adobe Experience Cloud products and recent experience with Adobe Experience Platform or similar CDP Good knowledge of Data Science workspace and building intelligent Services on AEP Strong knowledge of datasets in Adobe Experience Platform, load data into Platform through data source connectors, APIs, and streaming ingestion connectors Experience in creating all required Adobe XDM (Experience Data Model) in JSON based on approved data model for all loading data files. Knowledge on utilizing Adobe Experience Platform (AEP) UI & POSTMAN to automate all customer schema data lake & profile design setups within each sandbox environment. Experience in configuration within Adobe Experience Platform all necessary identities & privacy settings and creating new segments within AEP to meet customer use cases. Test/Validate the segments with the required destinations. Managing customer data by using Real-Time Customer Data Platform (RTCDP), and analyze customer data by using Customer Journey Analytics (CJA) Experience with creating connection, data views, and dashboard in CJA Hands-on experience in configuration and integration of Adobe Marketing Cloud modules like Audience Manager, Analytics, Campaign and Target Adobe Experience Cloud tool certifications (Adobe Campaign, Adobe Experience Platform, Adobe Target, Adobe Analytics) are desirable. Proven ability to communicate in both verbal and writing in a high performance, collaborative environment. Experience with data analysis, modeling, and mapping to coordinate closely with Data Architect(s) Build the necessary schemas, workflows to ingest customers data, transform the data & load the data into AEP successfully. Build Audiences (segmentations) and create necessary pipeline for Destination activation.

Role Purpose The purpose of the role is to create exceptional architectural solution design and thought leadership and enable delivery teams to provide exceptional client engagement and satisfaction. Do 1.Develop architectural solutions for the new deals/ major change requests in existing deals Creates an enterprise-wide architecture that ensures systems are scalable, reliable, and manageable. Provide solutioning of RFPs received from clients and ensure overall design assurance Develop a direction to manage the portfolio of to-be-solutions including systems, shared infrastructure services, applications in order to better match business outcome objectives Analyse technology environment, enterprise specifics, client requirements to set a collaboration solution design framework/ architecture Provide technical leadership to the design, development and implementation of custom solutions through thoughtful use of modern technology Define and understand current state solutions and identify improvements, options & tradeoffs to define target state solutions Clearly articulate, document and sell architectural targets, recommendations and reusable patterns and accordingly propose investment roadmaps Evaluate and recommend solutions to integrate with overall technology ecosystem Works closely with various IT groups to transition tasks, ensure performance and manage issues through to resolution Perform detailed documentation (App view, multiple sections & views) of the architectural design and solution mentioning all the artefacts in detail Validate the solution/ prototype from technology, cost structure and customer differentiation point of view Identify problem areas and perform root cause analysis of architectural design and solutions and provide relevant solutions to the problem Collaborating with sales, program/project, consulting teams to reconcile solutions to architecture Tracks industry and application trends and relates these to planning current and future IT needs Provides technical and strategic input during the project planning phase in the form of technical architectural designs and recommendation Collaborates with all relevant parties in order to review the objectives and constraints of solutions and determine conformance with the Enterprise Architecture Identifies implementation risks and potential impacts 2.Enable Delivery Teams by providing optimal delivery solutions/ frameworks Build and maintain relationships with executives, technical leaders, product owners, peer architects and other stakeholders to become a trusted advisor Develops and establishes relevant technical, business process and overall support metrics (KPI/SLA) to drive results Manages multiple projects and accurately reports the status of all major assignments while adhering to all project management standards Identify technical, process, structural risks and prepare a risk mitigation plan for all the projects Ensure quality assurance of all the architecture or design decisions and provides technical mitigation support to the delivery teams Recommend tools for reuse, automation for improved productivity and reduced cycle times Leads the development and maintenance of enterprise framework and related artefacts Develops trust and builds effective working relationships through respectful, collaborative engagement across individual product teams Ensures architecture principles and standards are consistently applied to all the projects Ensure optimal Client Engagement Support pre-sales team while presenting the entire solution design and its principles to the client Negotiate, manage and coordinate with the client teams to ensure all requirements are met and create an impact of solution proposed Demonstrate thought leadership with strong technical capability in front of the client to win the confidence and act as a trusted advisor 3.Competency Building and Branding Ensure completion of necessary trainings and certifications Develop Proof of Concepts (POCs),case studies, demos etc. for new growth areas based on market and customer research Develop and present a point of view of Wipro on solution design and architect by writing white papers, blogs etc. Attain market referencability and recognition through highest analyst rankings, client testimonials and partner credits Be the voice of Wipros Thought Leadership by speaking in forums (internal and external) Mentor developers, designers and Junior architects in the project for their further career development and enhancement Contribute to the architecture practice by conducting selection interviews etc 4.Team Management Resourcing Anticipating new talent requirements as per the market/ industry trends or client requirements Hire adequate and right resources for the team Talent Management Ensure adequate onboarding and training for the team members to enhance capability & effectiveness Build an internal talent pool and ensure their career progression within the organization Manage team attrition Drive diversity in leadership positions Performance Management Set goals for the team, conduct timely performance reviews and provide constructive feedback to own direct reports Ensure that the Performance Nxt is followed for the entire team Employee Satisfaction and Engagement Lead and drive engagement initiatives for the team Track team satisfaction scores and identify initiatives to build engagement within the team Mandatory Skills: AI Cognitive.

Location: Any / Remote / Work From Home Employment Type: Full-time Job Summary: We are seeking skilled and innovative AI Engineers with a minimum 2-4 years of experience in developing and deploying AI solutions . The ideal candidate should have practical knowledge in AWS , Amazon Bedrock , LLMs , Claude AI , and Custom AI Development . You will contribute to the design and implementation of cutting-edge Generative AI (GenAI) and Mainstream AI applications across diverse business domains. This is an excellent opportunity to work with emerging technologies in an agile, fast-paced environment with full ownership of AI engineering pipelines. Key Responsibilities: Develop custom machine learning models and fine-tune foundation models for enterprise use Design and implement LLM-based and Generative AI solutions tailored to client use cases Work with OpenAI, Anthropic, HuggingFace models and their APIs to build secure, scalable AI systems Perform prompt engineering and experiment with parameter tuning and context optimization Build APIs and backend services to integrate AI models into product workflows Collaborate with product, data, and DevOps teams to deliver end-to-end AI-powered solutions Ensure best practices for AI model governance, security, performance, and ethical use Stay current with advancements in LLMs, vector databases (e.g., Pinecone, FAISS), and GenAI tooling Document architecture, experiments, and processes clearly and effectively Participate in peer reviews, client meetings, and cross-functional planning discussions Required Qualifications: Minimum 2-4 years of professional experience in AI/ML , with specific focus on LLMs and GenAI Strong experience working on AWS Bedrock , Lambda, and related services Proficiency in Python , including experience with libraries like HuggingFace, LangChain, etc. Familiarity with Anthropic , OpenAI , or other foundation models in production settings Experience with custom AI model development and model fine-tuning Good understanding of cloud-native AI deployments and API integrations Ability to apply prompt engineering techniques to optimize LLM responses Exposure to vector databases and RAG pipelines Strong problem-solving, communication, and team collaboration skills Preferred Qualifications (STRONG PLUS): Hands-on experience with LangChain, RAG pipelines, or agent frameworks Familiarity with AWS Sagemaker, DynamoDB, Lambda, or other AI tooling in AWS Knowledge of Docker or Kubernetes for containerizing AI workloads Understanding of MLOps principles and tools (MLflow, SageMaker Pipelines, etc.) Contributions to open-source AI projects or published GenAI applications AI/ML certifications Familiarity with enterprise use cases in biotech, healthcare, or manufacturing What We Offer: Remote work option Competitive salary package Exciting projects in the field of LLMs, AI, and cloud-native development Continuous learning opportunities in Generative AI and cloud AI tools A collaborative and fast-paced environment with a forward-thinking team Access to state-of-the-art tools and flexible project ownership How to Apply: Please submit your resume and cover letter outlining your relevant experience and why you'd be a great fit for Arocom. We differentiate candidates based on professionalism. We admire the new age methods like a video resume. If you have one please share the URL along with your resume. Your privacy is important to us, so we will not be contacting candidates by phone. If your application is selected, we will email you a link to schedule your interview at your convenient time. Please check your emails regularly, including your SPAM folder. Arocom encourages work from home and has a Bring Your Own Device (BYOD) policy. Employees / Consultants working from home are expected to use their personal laptops/desktops for work-related tasks.

We are seeking a highly skilled and motivated Senior Data Scientist with 56 years of experience to drive the development of intelligent AI systems. This role requires extensive hands-on experience with Large Language Models (LLMs) , strong background in Agentic AI , Machine Learning , and Python programming . You will work on designing autonomous agents, building scalable ML pipelines, and integrating advanced LLM-powered solutions into real-world products. Key Responsibilities: Architect and implement agentic AI systems that use LLMs for autonomous reasoning, planning, and multi-step task execution. Lead the development, fine-tuning, evaluation, and deployment of Large Language Models (LLMs) using frameworks like Hugging Face Transformers, LangChain, LLM orchestration tools, and vector databases. Develop ML models using supervised, unsupervised, and reinforcement learning techniques, and integrate them into production environments. Design and build end-to-end machine learning pipelines, including data ingestion, feature engineering, training, and deployment. Optimize model performance and latency in real-world applications and implement model monitoring and retraining strategies. Collaborate with cross-functional teams including product, engineering, and business to translate AI capabilities into product features. Mentor junior data scientists and contribute to the team's technical excellence and innovation. Required Skills & Experience: 56 years of professional and relevant experience in data science, AI, or machine learning roles. Proven hands-on experience with LLMs, including fine-tuning, prompt engineering, and RAG (Retrieval-Augmented Generation) pipelines. Deep expertise in Python and ML libraries such as scikit-learn, PyTorch, TensorFlow, and transformers. Strong understanding of agentic AI principles, autonomous agents, and task orchestration. Experience with cloud platforms (AWS, GCP, or Azure) and scalable infrastructure for deploying AI models. Exposure to API development, ML model serving, and integration with real-time systems. Excellent communication and collaboration skills in cross-functional environments. Educational Qualification: Bachelor of Technology (B.Tech) in Computer Science, Data Science, Artificial Intelligence, or a related field from a recognized institution. Preferred Qualifications: Contributions to open-source AI/ML projects or research publications related to LLMs or agent-based systems. Familiarity with LangChain, AutoGPT, CrewAI, or other agent orchestration frameworks. Experience with vector databases (e.g., FAISS, Pinecone) and knowledge of semantic search. Understanding of multi-agent collaboration, goal decomposition, and planning architectures.

Position Summary LLMOps(Large language model operations) Engineer will play a pivotal role in building and maintaining the infrastructure and pipelines for our cutting-edge Generative AI applications, establishing efficient and scalable systems for LLM research, evaluation, training, and fine-tuning. Engineer will be responsible for managing and optimizing large language models (LLMs) across various platforms This position is uniquely tailored for those who excel in crafting pipelines, cloud infrastructure, environments, and workflows. Your expertise in automating and streamlining the ML lifecycle will be instrumental in ensuring the efficiency, scalability, and reliability of our Generative AI models and associated platform. LLMOps engineers expertise will ensure the smooth deployment, maintenance, and performance of these AI platforms and powerful large language models. You will follow Site Reliability Engineering & MLOps principles and will be encouraged to contribute your own best practices and ideas to our ways of working. Reporting to the Head of Cloud Native operations, you will be an experienced thought leader, and comfortable engaging senior managers and technologists. You will engage with clients, display technical leadership, and guide the creation of efficient and complex products/solutions. Key Responsibilities Technical & Architectural Leadership Contribute to the technical delivery of projects, ensuring a high quality of work that adheres to best practices, brings innovative approaches and meets client expectations. Project types include following (but not limited to): Solution architecture, Proof of concepts (PoCs), MVP, design, develop, and implementation of ML/LLM pipelines for generative AI models, data management & preparation for fine tuning, training, deployment, and monitoring. Automate ML tasks across the model lifecycle. Contribute to HCL thought leadership across the Cloud Native domain with an expert understanding of advanced AI solutions using Large Language Models (LLM) & Natural Language Processing (NLP) techniques and partner technologies. Collaborate with cross-functional teams to integrate LLM and NLP technologies into existing systems. Ensure the highest levels of governance and compliance are maintained in all ML and LLM operations. Stay abreast of the latest developments in ML and LLM technologies and methodologies, integrating these innovations to enhance operational efficiency and model effectiveness. Collaborate with global peers from partner ecosystems on joint technical projects. This partner ecosystem includes Google, Microsoft, Nvidia, AWS, IBM, Red Hat, Intel, Cisco, and Dell VMware etc. Service Delivery Provide a technical hands-on contribution. Create scalable infra to support enterprise loads (distributed GPU compute, foundation models, orchestrating across multiple cloud vendors, etc.) Ensuring the reliable and efficient platform operations. Apply data science, machine learning, deep learning, and natural language processing methods to analyse, process, and improve the models data and performance. Understanding of Explainability & Biased Detection concepts. Create and optimize prompts and queries for retrieval augmented generation and prompt engineering techniques to enhance the models capabilities and user experience w.r.t Operations & associated platforms. Client-facing influence and guidance, engaging in consultative client discussions and performing a Trusted Advisor role. Provide effective support to HCL Sales and Delivery teams. Support sales pursuits and enable HCL revenue growth. Define the modernization strategy for client platform and associated IT practices, create solution architecture and provide oversight of the client journey. Innovation & Initiative Always maintain hands-on technical credibility, keep in front of the industry, and be prepared to show and lead the way forward to others. Engage in technical innovation and support HCLs position as an industry leader. Actively contribute to HCL sponsorship of leading industry bodies such as the CNCF and Linux Foundation. Contribute to thought leadership by writing Whitepapers, blogs, and speaking at industry events. Be a trusted, knowledgeable internal innovator driving success across our global workforce. Client Relationships Advise on best practices related to platform & Operations engineering and cloud native operations, run client briefings and workshops, and engage technical leaders in a strategic dialogue. Develop and maintain strong relationships with client stakeholders. Perform a Trusted Advisor role. Contribute to technical projects with a strong focus on technical excellence and on-time delivery. Mandatory Skills & Experience Expertise in designing and optimizing machine-learning operations, with a preference for LLMOps. Proficient in Data Science, Machine Learning, Python, SQL, Linux/Unix shell scripting. Experience on Large Language Models and Natural Language Processing (NLP), and experience with researching, training, and fine-tuning LLMs. Contribute towards fine-tune Transformer models for optimal performance in NLP tasks, if required. Implement and maintain automated testing and deployment processes for machine learning models w.r.t LLMOps. Implement version control, CI/CD pipelines, and containerization techniques to streamline ML and LLM workflows. Develop and maintain robust monitoring and alerting systems for generative AI models ensuring proactive identification and resolution of issues. Research or engineering experience in deep learning with one or more of the following: generative models, segmentation, object detection, classification, model optimisations. Experience implementing RAG frameworks as part of available-ready products. Experience in setting up the infrastructure for the latest technology such as Kubernetes, Serverless, Containers, Microservices etc. Experience in scripting programming to automate deployments and testing, worked on tools like Terraform and Ansible. Scripting languages like Python, bash, YAML etc. Experience on CI/CD opensource and enterprise tool sets such as Argo CD, Jenkins. Experience with the GitHub/DevOps Lifecycle Experience in at least one of the Observability solutions (Prometheus, EFK stacks, ELK stacks, Grafana, Dynatrace, AppDynamics) Experience in at-least one of the clouds for example - Azure/AWS/GCP Significant experience on microservices-based, container-based or similar modern approaches of applications and workloads. You have exemplary verbal and written communication skills (English). Able to interact and influence at the highest level, you will be a confident presenter and speaker, able to command the respect of your audience. Desired Skills & Experience Bachelor level technical degree or equivalent experience; Computer Science, Data Science, or Engineering background preferred; masters degree desired. Experience in LLMOps or related areas, such as DevOps, data engineering, or ML infrastructure. Hands-on experience in deploying and managing machine learning and large language model pipelines in cloud platforms (e.g., AWS, Azure) for ML workloads. Familiar with data science, machine learning, deep learning, and natural language processing concepts, tools, and libraries such as Python, TensorFlow, PyTorch, NLTK etc. Experience in using retrieval augmented generation and prompt engineering techniques to improve the models quality and diversity to improve operations efficiency. Proven experience in developing and fine-tuning Language Models (LLMs). Stay up-to-date with the latest advancements in Generative AI, conduct research, and explore innovative techniques to improve model quality and efficiency. The perfect candidate will already be working within a System Integrator, Consulting or Enterprise organisation with 8+ years of experience in a technical role within the Cloud domain. Deep understanding of core practices including SRE, Agile, Scrum, XP and Domain Driven Design. Familiarity with the CNCF open-source community. Enjoy working in a fast-paced environment using the latest technologies, love Labs dynamic and high-energy atmosphere, and want to build your career with an industry leader.

Experience working in large Software Development Teams Knowledge and experience in Agile Delivery mechanisms Work with business stakeholders, SCRUM masters, Designers and testers in SCRUM team. Proficient in English language with ability to lead stakeholder conversations. Experience in generating insights through data and articulating stories addressing business problems. Total Experience Expected: 6-8 years Mandatory Technical Skills: Proficiency in SQL- Windows Function, Python for data analysis. Experience with data visualization tools like Tableau Total Experience Expected: 04-06 years

Who We Are Applied Materials is the global leader in materials engineering solutions used to produce virtually every new chip and advanced display in the world. We design, build and service cutting-edge equipment that helps our customers manufacture display and semiconductor chips- the brains of devices we use every day. As the foundation of the global electronics industry, Applied enables the exciting technologies that literally connect our world- like AI and IoT. If you want to work beyond the cutting-edge, continuously pushing the boundaries of"science and engineering to make possible"the next generations of technology, join us to Make Possible® a Better Future. What We Offer Location: Bangalore,IND At Applied, we prioritize the well-being of you and your family and encourage you to bring your best self to work. Your happiness, health, and resiliency are at the core of our benefits and wellness programs. Our robust total rewards package makes it easier to take care of your whole self and your whole family. Were committed to providing programs and support that encourage personal and professional growth and care for you at work, at home, or wherever you may go. Learn more about our benefits . Youll also benefit from a supportive work culture that encourages you to learn, develop and grow your career as you take on challenges and drive innovative solutions for our customers."We empower our team to push the boundaries of what is possible"”while learning every day in a supportive leading global company. Visit our Careers website to learn more about careers at Applied. Job Expectations The candidate will be responsible for leading a team of data scientists who provide analytics services for Applied Materials installed base. The deliverables include developing new service capabilities, piloting them, and commercializing them in partnership with Engineering and Service Product Managers. The team will work with field engineers and product engineering teams to understand the requirements, bring forward creative ideas, develop proofs-of-concept, architect, design, develop, and modify algorithms into production code, provide production support, and train end-users. The skill sets in the team include descriptive statistical analysis, predictive statistical analysis using AI/ML, data visualization and analytics process automation, data cleansing, complex image processing, and text processing. Candidate should be willing to learn and adopt semiconductor industry as their career domain. Key Responsibilities Responsible for managing completion of assignments, projects and programs to support Applieds service business. Scope of algorithm development includes research, design, code development, implementation, and proliferation. Execute projects as needed to support the business. Review and monitor progress to milestones on development programs. Develop roadmaps for algorithmic development programs. Oversee algorithmic concept and feasibility for algorithmic modules, including problem statement definition, data gathering, literature review, concept selection, risks, and implementation constraints. Oversee documentation of algorithmic development and deployment, including integration into required systems, user testing, and user training. Oversee software and hardware implementation. Interact with internal and external customers to define gaps, identify opportunities, define program scope and deliverables, and proliferate solutions to the user base. Present to management for project reviews, interact with project stakeholders, run regular cadence meetings and work in alignment with team and organization goals. Responsible for technical development of team, objective setting, and performance management. Develop growth plan for the team, including identification of new areas of impact. Preferred programming and data science skills includePython, C++, Unix, Image Processing, Deep Learning, AI/ML, NLP, GenAI, Text Mining, Database Design and Management, Web Scraping, GPU Optimization. Proficient in business processes and software such as Microsoft Word/ Excel/ Powerpoint/ Teams, Atlassian JIRA and Confluence. Highly organized and detail-oriented. Ability to build and maintain positive and productive inter-departmental working relationships. Ability to work in a cross-functional organization and multitask on multiple projects. Drive team members to deliver programs on time and on budget. Excellent oral and written communication, organizational, analytical, and interpersonal skills. Interest in building a career in the semiconductor industry. Functional Knowledge Demonstrates comprehensive understanding of concepts and principles within own job family and knowledge of other related job families. Business Expertise Applies in-depth understanding of how own discipline integrates within the segment/function. Leadership Manages multiple related teams, sets organizational priorities and allocates resources. Problem Solving Identifies and resolves complex technical, operational and organizational problems. Impact Impacts the business results of a team or area by supporting and funding of projects, products, services and/or technologies and developing policies and plans. Guided by business unit, department or sub-functional business plans. Interpersonal Skills Influences others internally and externally, including senior management. Position requires understanding of Applied Materials global Standards of Business Conduct and compliance with these standards at all times. This includes demonstrating the highest level of ethical conduct reflecting Applied Materials core values. Education Bachelors, Masters, or Ph.D. Degree in Computer Science, Mathematics, or Engineering with a concentration in data science or AI/ML. Experience 15 years of experience Computer Science/ Mathematics/ Engineering background with 15 years of experience in performing statistical analysis, designing and developing Image Processing/ Computer Vision Algorithms, handling and analyzing large volumes of data. Semiconductor background is an added advantage. Prior team leadership experience is required. Additional Information Time Type: Full time Employee Type: Assignee / Regular Travel: Yes, 20% of the Time Relocation Eligible: Yes Applied Materials is an Equal Opportunity Employer. Qualified applicants will receive consideration for employment without regard to race, color, national origin, citizenship, ancestry, religion, creed, sex, sexual orientation, gender identity, age, disability, veteran or military status, or any other basis prohibited by law.

We are seeking an accomplished and visionary Data Scientist/ GenAI Lead to join Amgens Enterprise Data Management team. As MDM Data Science/Manager, you will lead the design, development, and deployment of Generative AI and ML models to power data-driven decisions across business domains. This role is ideal for an AI practitioner who thrives in a collaborative environment and brings a strategic mindset to applying advanced AI techniques to solve real-world problems. To succeed in this role, the candidate must have strong AI/ML, Data Science , GenAI experience along with MDM knowledge, hence the candidates having only MDM experience are not eligible for this role. Candidate must have AI/ML, data science and GenAI experience on technologies like ( PySpark / PyTorch , TensorFlow, LLM , Autogen , Hugging FaceVectorDB , Embeddings, RAGs etc ), along with knowledge of MDM (Master Data Management) Roles & Responsibilities: Drive development of enterprise-level GenAI applications using LLM frameworks such as Langchain, Autogen, and Hugging Face. Architect intelligent pipelines using PySpark, TensorFlow, and PyTorch within Databricks and AWS environments. Implement embedding models andmanage VectorStores for retrieval-augmented generation (RAG) solutions. Integrate and leverage MDM platforms like Informatica and Reltio to supply high-quality structured data to ML systems. Utilize SQL and Python for data engineering, data wrangling, and pipeline automation. Build scalable APIs and services to serve GenAI models in production. Lead cross-functional collaboration with data scientists, engineers, and product teams to scope, design, and deploy AI-powered systems. Ensure model governance, version control, and auditability aligned with regulatory and compliance expectations. Basic Qualifications and Experience: Masters degree with 8 - 10 years of experience in Data Science, Artificial Intelligence, Computer Science, or related fields OR Bachelors degree with 10 - 14 years of experience in Data Science, Artificial Intelligence, Computer Science, or related fields OR Diploma with 14 - 16 years of hands-on experience in Data Science, AI/ML technologies, or related technical domains Functional Skills: Must-Have Skills: 10+ years of experience working in AI/ML or Data Science roles, including designing and implementing GenAI solutions. Extensive hands-on experience with LLM frameworks and tools such as Langchain, Autogen, Hugging Face, OpenAI APIs, and embedding models. Strong programming background with Python, PySpark, and experience in building scalable solutions using TensorFlow, PyTorch, and SK-Learn. Proven track record of building and deploying AI/ML applications in cloud environments such as AWS. Expertise in developing APIs, automation pipelines, and serving GenAI models using frameworks like Django, FastAPI, and DataBricks. Solid experience integrating and managing MDM tools (Informatica/Reltio) and applying data governance best practices. Guide the team on development activities and lead the solution discussions Must have core technical capabilities in GenAI, Data Science space Good-to-Have Skills: Prior experience in Data Modeling, ETL development, and data profiling to support AI/ML workflows. Working knowledge of Life Sciences or Pharma industry standards and regulatory considerations. Proficiency in tools like JIRA and Confluence for Agile delivery and project collaboration. Familiarity with MongoDB, VectorStores, and modern architecture principles for scalable GenAI applications. Professional Certifications : Any ETL certification (e.g. Informatica) Any Data Analysis certification (SQL) Any cloud certification (AWS or AZURE) Data Science and ML Certification Soft Skills: Strong analytical abilities to assess and improve master data processes and solutions. Excellent verbal and written communication skills, with the ability to convey complex data concepts clearly to technical and non-technical stakeholders. Effective problem-solving skills to address data-related issues and implement scalable solutions. Ability to work effectively with global, virtual teams

Req ID: 284544 We are currently seeking a Systems Integration Advisor -Technical Architecture-Cloud Services-AWS to join our team in Bangalore, Karntaka (IN-KA), India (IN). : We are seeking a highly skilled and motivated Mid-Level AI/DS Specialist to join our dynamic team at NTT Data. The ideal candidate will have a strong background in artificial intelligence and data science, with expertise in natural language processing (NLP), generative AI (Gen-AI), and conversational AI. The candidate should be well-versed with the Microsoft AI platform, OpenAI, Databricks, Python, and common data science libraries and tools. Additionally, the candidate should be capable of fine-tuning large language models (LLMs) and familiar with AI/ML engineering and prompt engineering. Key Responsibilities: Develop and implement AI/DS solutions to enhance business processes and customer experiences. Utilize NLP, Gen-AI, and conversational AI techniques to build and optimize AI models. Work with the Microsoft AI platform, OpenAI, and Databricks to develop and deploy AI solutions. Write efficient and scalable code in Python, leveraging common data science libraries and tools. Fine-tune LLM models to meet specific project requirements. Collaborate with cross-functional teams to integrate AI/DS solutions into existing systems. Stay updated with the latest advancements in AI/DS and apply them to ongoing projects. Conduct prompt engineering to improve the performance and accuracy of AI models. Qualifications: Bachelor's or Master's degree in Computer Science, Data Science, AI, or a related field. Proven experience in AI/DS, with a focus on NLP, Gen-AI, and conversational AI. Proficiency in the Microsoft AI platform, OpenAI, Databricks, and Python. Strong knowledge of common data science libraries and tools. Experience in fine-tuning LLM models. Familiarity with AI/ML engineering and prompt engineering. Excellent problem-solving skills and attention to detail. Strong communication and collaboration skills.