106 Feature Engineering Jobs - Page 3

As a Senior AI/ML Engineer, you will be responsible for designing, developing, and deploying advanced AI models with a focus on generative AI, including transformer architectures such as GPT, BERT, T5, and other deep learning models utilized for text, image, or multimodal generation. You will work with extensive and complex datasets by cleaning, preprocessing, and transforming data to meet quality and relevance standards for generative model training. Additionally, you will collaborate with cross-functional teams to identify project objectives and create solutions using generative AI tailored to business needs. Your role will involve implementing, fine-tuning, and scaling generative AI models in production environments to ensure robust model performance and efficient resource utilization. You will also be responsible for developing pipelines and frameworks for efficient data ingestion, model training, evaluation, and deployment, including A/B testing and monitoring of generative models in production. It is essential to stay informed about the latest advancements in generative AI research, techniques, and tools, applying new findings to improve model performance, usability, and scalability. Furthermore, documenting and communicating technical specifications, algorithms, and project outcomes to technical and non-technical stakeholders with an emphasis on explainability and responsible AI practices. To qualify for this role, you should hold a Bachelor's or Master's degree in Computer Science, Data Science, AI/ML, or a related field. A relevant Ph.D. or research experience in generative AI would be advantageous. You should have 12-16 years of experience in machine learning, with at least 8 years in designing and implementing generative AI models or working specifically with transformer-based models. The ideal candidate will possess expertise in generative AI, transformer models, GANs, VAEs, text generation, and image generation. Strong knowledge of machine learning algorithms, deep learning, neural networks, and programming skills in Python and SQL are required. Familiarity with libraries such as Hugging Face Transformers, PyTorch, TensorFlow, and experience with MLOps tools like Docker, Kubernetes, MLflow, and Cloud Platforms (AWS, GCP, Azure) is essential. Additionally, proficiency in data engineering concepts such as data preprocessing, feature engineering, and data cleaning is preferred. Joining our team will provide you with an opportunity to work on technical challenges with global impact, vast opportunities for self-development through online university access and sponsored certifications, sponsored Tech Talks & Hackathons, and a generous benefits package including health insurance, retirement benefits, flexible work hours, and more. You will work in a supportive environment with forums to explore passions beyond work, offering an exciting opportunity to contribute to cutting-edge solutions while advancing your career in a dynamic and collaborative setting.,

As a Generative AI & LLM expert, you will be responsible for supporting the AI and ML team in designing, developing, fine-tuning, and deploying large language models and generative AI applications. This role offers a unique opportunity to work with state-of-the-art AI technologies and enhance your skills in machine learning, natural language processing, and deep learning. Your primary responsibilities will include architecting robust systems to integrate LLMs and support retrieval workflows, providing guidance on the use of Vector DBs and model deployment on cloud platforms, optimizing the fine-tuning process for business-specific LLM use cases, and designing applications with on-premise/cloud-based LLM, RAG, Langchain. Key skills required for this role include model training & fine-tuning, data preparation & preprocessing, prompt engineering, model evaluation & optimization, collaborating with cross-functional teams, documentation & reporting, managing and training LLM models, and generating embeddings and managing semantic search via Vector DBs. To qualify for this position, you should have completed a Bachelors or Masters degree in Computer Science, Data Science, Artificial Intelligence, or a related field. Additionally, you should have at least 7+ years of experience in building ML pipelines, feature engineering, or deploying models/LLMs on cloud platforms. Other skills considered include experience with machine learning pipelines, model optimization, feature engineering, proficiency in database indexing, familiarity with deploying ML models in cloud environments, leadership skills, and strategic thinking. If you are passionate about working with cutting-edge AI technologies and have a strong background in machine learning and deep learning, we encourage you to apply for this role in our Product Engineering category. You can submit your application by filling in your name, email, phone number, and attaching your resume. We look forward to potentially welcoming you to our team and collaborating on innovative AI projects.,

You will be responsible for assisting in building and validating machine learning models as well as performing data cleaning, transformation, and feature engineering. Additionally, you will conduct exploratory data analysis using Python or R, support model tuning, performance tracking, and documentation. Collaboration with the team to apply AI/ML solutions to business use cases will be a key part of your role. You will also prepare clear reports and visualizations to present findings effectively. Applexus is a global technology leader that offers business consulting and SAP services to customers in the retail, fashion, and consumer products industries. Established in 2005, Applexus prioritizes customer satisfaction by developing technology solutions that facilitate business transformation. Headquartered in Seattle, Washington, Applexus operates across various centers in North America (Seattle & Canada), the United Kingdom, and India (Trivandrum & Chennai). The company is dedicated to making a positive impact by serving communities worldwide.,

As a Data Scientist at WAC, you will play a crucial role in transforming intricate data into actionable insights that drive business strategies and foster innovation. Your primary responsibility will involve collaborating with diverse teams to create and implement data science solutions that align with our business objectives. Your tasks will include data exploration, where you will gather, cleanse, and preprocess data from a variety of sources to ensure its quality and reliability. Leveraging advanced statistical and machine learning techniques, you will conduct in-depth analyses to derive meaningful insights. Additionally, you will be responsible for developing, refining, and optimizing predictive models that tackle specific business challenges and opportunities. Creating visually engaging reports and dashboards to present findings to technical and non-technical stakeholders will be a key aspect of your role. You will also be involved in formulating and testing hypotheses, as well as designing and executing A/B tests to evaluate the impact of changes and enhancements. Your ability to communicate complex technical findings in a clear and understandable manner will be vital in supporting decision-makers. Collaboration will be integral to your work, as you will liaise with teams across the organization to grasp business goals and provide data-driven insights and recommendations. Continuous learning is encouraged, and staying abreast of the latest trends in data science, machine learning, and analytics will enable you to apply cutting-edge techniques and tools effectively. To qualify for this role, you should hold a Master's or Ph.D. degree in a relevant field such as Data Science, Statistics, Computer Science, or related disciplines. With a minimum of 4 years of experience in a Data Scientist or similar position, you must demonstrate proficiency in data analysis tools and languages like Python or R. A strong grasp of machine learning techniques and libraries, coupled with familiarity with data visualization tools such as Tableau or Power BI, is essential. Your problem-solving abilities, critical thinking skills, and aptitude for effective communication, especially in simplifying complex technical concepts for non-technical stakeholders, will be crucial. An understanding of data ethics and the responsible use of data is also expected from potential candidates. Thank you for your interest in joining Webandcrafts. We eagerly anticipate delving deeper into your application to assess your suitability for this role.,

As an AI/ML Engineer at Left Right Mind, you will be part of our dynamic team working on cutting-edge GenAI solutions and deploying large language models (LLMs) for real-world applications. Your primary responsibilities will include developing and deploying AI/ML models to address business challenges, optimizing LLMs for specific domains, and building end-to-end ML pipelines encompassing data preprocessing, training, and evaluation. Additionally, you will work with both structured and unstructured data to extract valuable insights and collaborate closely with engineers to bring models into production effectively. We expect you to stay abreast of the latest advancements in GenAI, RAG, and LLM research, leveraging tools such as LangGraph, Autogen, TensorFlow, and PyTorch. Experience with deploying solutions on cloud platforms like AWS, Azure, or GCP using Docker/Kubernetes will be beneficial. The ideal candidate should possess a minimum of 4 years of experience in AI/ML, demonstrate proficiency in Python programming and ML frameworks, and have hands-on experience with LLMs like OpenAI GPT, Gemini, or Claude. Moreover, familiarity with NLP, feature engineering, and model optimization, along with strong problem-solving and teamwork skills, are highly valued traits in this role. At Left Right Mind, we foster a culture of exploration, inquiry, and innovation. Our work is purpose-driven and fueled by curiosity. If you are passionate about pushing the boundaries of AI/ML and eager to contribute to impactful projects, we encourage you to apply by filling out the form: [Application Form](https://lnkd.in/dtdBVTHE). For any inquiries or additional information, feel free to contact varad.deshpande@leftrightmind.com.,

As a Data Engineer for our data-rich e-commerce platform catering to the life sciences sector, your primary responsibility will be to support infrastructure, develop data pipelines, and deploy pricing logic. You will play a crucial role in ensuring the usability and interface design of internal tools that facilitate experimentation, pricing configuration, and real-time monitoring. Your key responsibilities will include: - Building and maintaining ETL pipelines for pricing, shipping, and behavioral datasets - Collaborating with data scientists and product managers to facilitate model development and experimentation - Developing APIs or backend logic to implement dynamic pricing algorithms - Creating internal dashboards or tools with a strong focus on usability and performance - Ensuring data quality, reliability, and documentation across all systems - Performing feature engineering to support predictive and optimization algorithms - Aggregating and transforming high-dimensional datasets at scale to enhance modeling efficiency and robustness - Optimizing algorithm performance for real-time and large-scale deployment To excel in this role, you must possess: - Flexibility to thrive in a dynamic, startup-like environment and tackle diverse tasks with innovative solutions - 3+ years of experience in data engineering or backend development - Proficiency in Databricks and distributed data processing frameworks - Strong skills in Python, SQL, and cloud-based platforms such as AWS, BigQuery, and Snowflake - Demonstrated expertise in designing user-friendly internal tools and interfaces - Familiarity with experimentation systems and monitoring infrastructure - Experience in efficiently handling large-scale, high-dimensional datasets - Preferred domain knowledge in e-commerce, with a strong advantage for familiarity with the pharmaceutical or scientific supply sector This is a contract role with the potential for conversion to full-time, starting from August to December 2025. The preferred location for this position is Bangalore, with alternatives in Mumbai and Kathmandu. If you are looking to contribute to a cutting-edge platform and drive impactful changes in the life sciences industry, we welcome your application.,

As an AI Engineer at YASH Technologies, you will have the opportunity to utilize your 24 years of experience in the field to make a significant impact. You will be a part of a team that is dedicated to leveraging cutting-edge technologies to drive business transformation and deliver exceptional stakeholder experiences. Your primary responsibility will be to build and deploy machine learning models for classification, regression, and clustering tasks. You will also apply foundational GenAI concepts such as embeddings, summarization, and RAG, using tools like LangChain and vector databases. Additionally, you will be expected to prepare documentation and interpret results to drive actionable insights. To excel in this role, you must have strong hands-on experience in Python, Scikit-learn, and Pandas. Knowledge of model evaluation, feature engineering, and model tuning is essential, along with exposure to LangChain and vector databases. Basic familiarity with FastAPI or Flask is also preferred. At YASH, we believe in empowering our employees to shape their careers while working in a collaborative and inclusive environment. We provide career-oriented skilling models and opportunities for continuous learning, unlearning, and relearning at a rapid pace. Our Hyperlearning workplace is guided by principles such as flexible work arrangements, open collaboration, support for business goals, and a stable employment environment with an ethical corporate culture. Join us at YASH Technologies and be a part of a team that is driving positive changes in an increasingly virtual world.,

You are an experienced OCI AI Architect who will be responsible for leading the design and deployment of Gen AI, Agentic AI, and traditional AI/ML solutions on Oracle Cloud. Your role will involve a deep understanding of Oracle Cloud Architecture, Gen AI, Agentic and AI/ML frameworks, data engineering, and OCI-native services. The ideal candidate will possess a combination of deep technical expertise in AI/ML and Gen AI over OCI along with domain knowledge in Finance and Accounting. Your key responsibilities will include designing, architecting, and deploying AI/ML and Gen AI solutions on OCI using native AI services, building agentic AI solutions using frameworks such as LangGraph, CrewAI, and AutoGen, leading the development of machine learning AI/ML pipelines, and providing technical guidance on MLOps, model versioning, deployment automation, and AI governance. You will collaborate with functional SMEs, application teams, and business stakeholders to identify AI opportunities, advocate for OCI-native capabilities, and support customer presentations and solution demos. To excel in this role, you should have 10-15 years of experience in Oracle Cloud and AI, with at least 5 years of proven experience in designing, architecting, and deploying AI/ML & Gen AI solutions over OCI AI stack. Strong Python development experience, knowledge of LLMs such as Cohere and GPT, proficiency in AI/ML/Gen AI frameworks like TensorFlow, PyTorch, Hugging Face, and hands-on experience with OCI services are required. Additionally, skills in AI governance, Agentic AI frameworks, AI architecture principles, and leadership abilities are crucial for success. Qualifications for this position include Oracle Cloud certifications such as OCI Architect Professional, OCI Generative AI Professional, OCI Data Science Professional, as well as a degree in Computer Science or MCA. Any degree or diploma in AI would be preferred. Experience with front-end programming languages, Finance domain solutions, Oracle Cloud deployment, and knowledge of Analytics and Data Science would be advantageous. If you are a highly skilled and experienced OCI AI Architect with a passion for designing cutting-edge AI solutions on Oracle Cloud, we invite you to apply and join our team for this exciting opportunity.,

You are a highly skilled and motivated Senior Machine Learning Engineer with over 5 years of experience in ML model development, MLOps pipelines, Python programming, and hands-on exposure to Generative AI technologies. In this role, you will play a key role in designing, developing, and deploying scalable machine learning models and production-grade AI solutions in a collaborative, fast-paced environment. Your responsibilities will include developing and implementing ML models across various domains such as predictive modeling, NLP, and computer vision. You will also be responsible for building and maintaining end-to-end MLOps pipelines for scalable model training, validation, deployment, and monitoring. Working with GenAI frameworks like LangChain, LlamaIndex, or Hugging Face Transformers for building advanced solutions will be a crucial part of your role. Collaboration with data scientists, data engineers, and DevOps teams to operationalize ML solutions is essential. You will need to write clean, efficient, and well-documented Python code for data preprocessing, feature engineering, and model building. Evaluating model performance, iterative improvements based on experimentation and business feedback, ensuring solutions meet performance, reliability, and scalability requirements, participating in code reviews, sprint planning, and design discussions are all key aspects of this role. To be successful in this position, you should have 5+ years of hands-on experience in Machine Learning and Model Development. Strong proficiency in Python and related ML libraries such as scikit-learn, PyTorch, TensorFlow, Pandas, NumPy is required. Experience with MLOps tools like MLflow, Airflow, Kubeflow, SageMaker, or similar is essential. You should have a solid understanding of Generative AI techniques and experience deploying ML models using containerization (Docker), cloud platforms (AWS/GCP/Azure), and CI/CD workflows. Familiarity with version control (Git), agile methodologies, and collaborative development environments is necessary. Excellent problem-solving, debugging, and analytical skills are crucial for this role. Strong communication and collaboration abilities, comfortable working in a hybrid and globally distributed team, are also required. Nice to have skills include experience with LLMOps and tools like Weights & Biases, VectorDBs (e.g., FAISS, Pinecone, Chroma), a background in software engineering or DevOps, exposure to front-end integration for AI applications (e.g., Streamlit, Gradio), and previous experience working in a late-shift or client-aligned shift model. The shift timings for this role are 2:00 PM to 11:00 PM IST (Hybrid Model 2-3 days onsite per week in Chennai office).,

You have an exciting opportunity to join KPMG in India as a Data Science Manager/Senior Manager based in Gurgaon with 9-16 years of experience. In this role, you will lead AI/ML initiatives, drive GenAI strategy, architect scalable solutions, mentor teams, collaborate with stakeholders, and ensure responsible AI practices. Your responsibilities will include leading AI/ML projects from concept to production, guiding technical reviews, promoting best practices, and translating business needs into data-driven solutions. You should have 9+ years of experience in data science/software engineering, proficiency in Python, SQL, Docker, and cloud platforms, as well as hands-on experience with ML algorithms, feature engineering, and model deployment. KPMG in India is a reputable professional services firm known for its industry-focused and technology-enabled services. The firm operates from 14 cities across the country and is committed to quality, excellence, growth, innovation, and collaboration. If you are a data science professional with strong communication, leadership, and project management skills, this role might be the perfect fit for you. KPMG in India is an equal opportunity employer. Join us in our journey of providing informed and timely business advice to clients, helping them mitigate risks and seize opportunities in a rapidly evolving industry landscape.,

We are looking for a talented AI Developer to join our growing team. As an AI Developer, you will be responsible for designing, developing, and implementing AI solutions that meet our clients" needs. You will collaborate with cross-functional teams to integrate AI models into our products and services, leveraging cutting-edge technologies to drive innovation and deliver impactful results. Your responsibilities will include designing and developing AI models and algorithms to solve business problems, implementing machine learning and deep learning algorithms for various applications, collaborating with data scientists and engineers to preprocess data and build datasets for training models, integrating AI models into software applications and platforms, optimizing AI models for performance, scalability, and efficiency, conducting research to stay current with the latest advancements in AI and machine learning technologies, testing and validating AI models to ensure accuracy and reliability, deploying AI models into production environments, and monitoring their performance. Furthermore, you will collaborate with product managers and stakeholders to understand project requirements and propose AI solutions. Requirements: - Bachelor's degree in Computer Science, Engineering, Mathematics, or related field; Master's degree or PhD preferred. - Proficiency in programming languages such as Python, Java, or C++. - Hands-on experience with AI frameworks and libraries (e.g., TensorFlow, PyTorch, scikit-learn). - Strong understanding of machine learning algorithms and techniques (e.g., supervised learning, unsupervised learning, reinforcement learning). - Experience with data preprocessing, feature engineering, and model evaluation. - Knowledge of cloud platforms (e.g., AWS, Azure, GCP) and familiarity with deploying AI models in cloud environments. - Excellent problem-solving skills and ability to work independently as well as part of a team. - Strong communication skills and ability to collaborate effectively with cross-functional teams. Preferred Qualifications: - Experience with natural language processing (NLP) and computer vision applications. - Familiarity with big data technologies (e.g., Hadoop, Spark) for handling large-scale datasets. - Understanding of DevOps practices and experience with CI/CD pipelines. - Publications or contributions to the AI and machine learning community (e.g., research papers, open-source projects).,

At PwC, the focus is on leveraging data to drive insights and make informed business decisions in the field of data and analytics. Utilizing advanced analytics techniques is key to helping clients optimize their operations and achieve strategic goals. As a member of the data analysis team at PwC, you will be tasked with utilizing advanced analytical techniques to extract insights from large datasets and facilitate data-driven decision-making. Your role will involve leveraging skills in data manipulation, visualization, and statistical modeling to assist clients in solving complex business problems. PwC US - Acceleration Center is currently looking for a highly skilled and experienced GenAI Data Scientist to join the team at the Senior Associate level. In this role, you will be instrumental in developing and implementing machine learning models and algorithms for GenAI projects. The ideal candidate should possess a strong background in data science, particularly focusing on GenAI technologies, and have a solid understanding of statistical analysis, machine learning, data visualization, and application programming. As a candidate with 4+ years of hands-on experience, your responsibilities will include collaborating with cross-functional teams to understand business requirements and identify opportunities for applying GenAI technologies, developing and implementing machine learning models and algorithms for GenAI projects, performing data cleaning, preprocessing, and feature engineering, collaborating with data engineers for efficient data processing and integration into machine learning pipelines, validating and evaluating model performance, developing and deploying production-ready machine learning applications and solutions, utilizing object-oriented programming skills, employing Kubernetes for container orchestration and deployment, designing and building chatbots using GenAI technologies, communicating findings and insights to stakeholders through data visualizations, reports, and presentations, and staying up-to-date with the latest advancements in GenAI technologies. Requirements for this role include 3-5 years of relevant technical/technology experience with a focus on GenAI projects, strong programming skills in languages like Python, R, or Scala, proficiency in machine learning libraries and frameworks such as TensorFlow, PyTorch, or scikit-learn, experience with data preprocessing, feature engineering, and data wrangling techniques, a solid understanding of statistical analysis, hypothesis testing, and experimental design, familiarity with cloud computing platforms like AWS, Azure, or Google Cloud, knowledge of data visualization tools and techniques, strong problem-solving and analytical skills, excellent communication and collaboration abilities, and the ability to work in a fast-paced and dynamic environment. Preferred qualifications include experience with object-oriented programming languages like Java, C++, or C#, developing and deploying machine learning applications in production environments, understanding of data privacy and compliance regulations, and relevant certifications in data science or GenAI technologies. Nice-to-have skills encompass experience with Azure AI Search, Azure Doc Intelligence, Azure OpenAI, AWS Textract, AWS Open Search, AWS Bedrock, familiarity with LLM backed agent frameworks such as Autogen, Langchain, Semantic Kernel, etc., and experience in chatbot design and development. Candidates with a professional and educational background in any graduate / BE / B.Tech / MCA / M.Sc / M.E / M.Tech / Masters Degree / MBA are encouraged to apply for this position.,

As a Senior Developer/ Lead in Data Science at Material+, you will be responsible for leading the development and implementation of Generative AI models such as Azure OpenAI GPT and multi-agent system architecture. Your role will require a strong background in Python and AI/ML libraries like TensorFlow, PyTorch, and Scikit-learn. Experience with frameworks like LangChain, AutoGen, or similar for multi-agent systems will be essential, along with expertise in data preprocessing, feature engineering, and model evaluation techniques. It is preferred that you have a minimum of 4+ years of experience in a similar role as a Senior Developer/ Lead in Data Science. The ideal candidate should be well-versed in Big Data tools such as Spark, Hadoop, Databricks, and databases like SQL and NoSQL. Familiarity with ReactJS for developing responsive and interactive user interfaces would be a bonus. Material+ is looking for an immediate joiner located in Gurgaon or Bangalore. In addition to a challenging work environment, we offer professional development opportunities, mentorship, and a hybrid work mode with a remote-friendly workplace. We are committed to the well-being of our employees and provide benefits such as health and family insurance, ample leave days including maternity and paternity leaves, as well as wellness, meditation, and counseling sessions. Join us at Material+ where you can contribute to cutting-edge projects in Data Science while enjoying a supportive and inclusive work culture.,

YASH Technologies is looking to hire AI/ML Professionals, specifically for the role of Data Scientist with 24 years of experience on a full-time basis. As a Data Scientist at YASH, you will be part of a dynamic team, leveraging your advanced analytical and technical expertise to solve complex business problems and drive impactful data-driven decisions. Your responsibilities will include building and deploying ML models for classification, regression, and clustering tasks, applying foundational GenAI concepts, utilizing APIs and tools like LangChain and vector databases, as well as preparing documentation and interpreting results. The ideal candidate should possess strong hands-on experience in Python, Scikit-learn, and Pandas, along with knowledge of model evaluation, feature engineering, and model tuning. Exposure to LangChain, vector databases, and basic knowledge of FastAPI or Flask will be beneficial for this role. At YASH Technologies, you will have the opportunity to create a career path that aligns with your aspirations while working in an inclusive team environment. The company focuses on continuous learning, unlearning, and relearning through career-oriented skilling models and technology-driven solutions. The workplace at YASH is grounded on principles of flexible work arrangements, emotional positivity, trust, transparency, open collaboration, support for business goals, stable employment, and an ethical corporate culture.,

Are you passionate about the intersection of data, technology, and science, and excited by the potential of Real-World Data (RWD) and AI Do you thrive in collaborative environments and aspire to contribute to the discovery of groundbreaking medical insights If so, join the data42 team at Novartis! At Novartis, we reimagine medicine by leveraging state-of-the-art analytics and our extensive internal and external data resources. Our data42 platform grants access to high-quality, multi-modal preclinical and clinical data, along with RWD, creating the optimal environment for developing advanced AI/ML models and generating health insights. Our global team of data scientists and engineers utilizes this platform to uncover novel insights and guide drug development decisions. As an RWD SME / RWE Execution Data Scientist, you will focus on executing innovative methodologies and AI models to mine RWD on the data42 platform. You will be the go-to authority for leveraging diverse RWD modalities patterns crucial to understanding patient populations, biomarkers, and drug targets, accelerating the development of life-changing medicines. Duties and Responsibilities: - Collaborate with R&D stakeholders to co-create and implement innovative, repeatable, scalable, and automated data and technology solutions in line with data42 strategy. - Be a data Subject Matter Expert (SME), understand Real World Data (RWD) of different modalities, vocabularies (LOINC, ICD, HCPCS, etc.), non-traditional RWD (Patient reported outcomes, Wearables and Mobile Health Data) and where and how they can be used, including in conjunction with clinical data, omics data, pre-clinical data, and commercial data. - Contribute to data strategy implementation such as Federated Learning, tokenization, data quality frameworks, regulatory requirements (submission data to HL7 FHIR formats conversion, Sentinel initiative), conversion to common data models and standards (OMOP, FHIR, SEND, etc.), FAIR principles, and integration with enterprise catalog. - Define and execute advanced integrated and scalable analytical approaches and research methodologies (including industry trends) in support of exploratory and regulatory use of AI models for RWD analysis across the Research Development Commercial continuum by facilitating research questions. - Stay current with emerging applications and trends, driving the development of advanced analytic capabilities for data42 across the Real-world evidence generation lifecycle, from ideation to study design and execution. - Demonstrate high agility working across various cross-located and cross-functional associates across business domains (commercial, Development, Biomedical Research) or Therapeutic area divisions for our priority disease areas to execute complex and critical business problems with quantified business impact/ROI. Ideal Candidate Profile: - PhD or MSc. in a quantitative discipline (e.g., but not restricted to Computer Science, Physics, Statistics, Epidemiology) with proven expertise in artificial Intelligence / Machine Learning. - 8+ years of relevant experience in Data Science (or 4+ years post-qualification in case of PhD). - Extensive experience in Statistical and Machine Learning techniques: Regression, Classification, Clustering, Design of Experiments, Monte Carlo Simulations, Statistical Inference, Feature Engineering, Time Series Forecasting, Text Mining, and Natural Language Processing, LLMs, and multi-modal Generative AI. - Good to have skills: Stochastic models, Bayesian Models, Markov Chains, Optimization techniques including, Dynamic Programming Deep Learning techniques on structured and unstructured data, Recommender Systems. - Proficiency in tools and packages: Python, R(optional), SQL; exposure to dashboard or web-app building using PowerBI, R-Shiny, Flask, open source or proprietary software and packages is an advantage. - Knowledge in data standards e.g. OHDSI OMOP, and other data standards, FHIR HL7 for regulatory, and best practices. - Good to have: Foundry, big data programming, working knowledge of executing data science on AWS, DataBricks, or SnowFlake. - Strong in Matrix collaboration environments with good communication and collaboration skills with country/ regional/ global stakeholders in an individual contributor capacity. Novartis is committed to building an outstanding, inclusive work environment and diverse teams representative of the patients and communities we serve. Why Novartis: Helping people with disease and their families takes more than innovative science. It takes a community of smart, passionate people like you. Collaborating, supporting, and inspiring each other. Combining to achieve breakthroughs that change patients" lives. Ready to create a brighter future together Join our Novartis Network: Not the right Novartis role for you Sign up to our talent community to stay connected and learn about suitable career opportunities as soon as they come up. Benefits and Rewards: Read our handbook to learn about all the ways we'll help you thrive personally and professionally.,

As a Senior Analytics Consultant specializing in banking analytics, you will leverage your expertise in credit risk modeling, fraud detection, and marketing analytics to lead client-facing engagements. With over 5 years of experience in the banking sector, you will be responsible for designing and implementing advanced models, translating data insights into strategic recommendations, and ensuring compliance with regulatory standards. Your key responsibilities will include leading and managing analytics projects focused on credit risk, fraud analytics, or marketing analytics within the banking industry. You will collaborate with clients to define business problems, develop analytic frameworks, and deliver actionable solutions. Using your proficiency in analytical programming languages such as Python, R, or SAS, you will build and validate statistical and machine learning models to extract meaningful insights from large datasets. In addition to your technical skills, you will be expected to communicate complex analytical findings effectively through business-friendly presentations and reports. As a senior member of the team, you will also guide junior team members, contribute to knowledge sharing within the firm, and uphold a strong understanding of the banking regulatory environment, including standards like Basel II/III, CCAR, and AML. To qualify for this role, you should hold a Bachelors or Masters degree in Statistics, Economics, Mathematics, Computer Science, or a related quantitative discipline. You must have a minimum of 5 years of hands-on experience in banking analytics, strong proficiency in SQL, and a solid understanding of statistical modeling techniques and machine learning algorithms. Prior experience in a consulting or professional services environment, familiarity with cloud-based analytics platforms, and exposure to digital banking data sources are preferred qualifications. In return, you can expect high-impact projects with top banking institutions, a collaborative team culture that values intellectual curiosity, clear paths for career growth and leadership opportunities, and competitive compensation. Join us in shaping the future of banking analytics and making a significant impact in the industry.,

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

You should have hands-on experience in Machine Learning Model and deep learning development using python. You will be responsible for Data Quality Analysis and Data preparation, Exploratory Data Analysis, and visualization of data. Additionally, you will define validation strategies, preprocessing or feature engineering on a given dataset, and data augmentation pipelines. Text processing using Machine Learning and NLP for processing documents will also be part of your role. Your tasks will include training models, tuning their hyperparameters, analyzing model errors, and designing strategies to overcome them. You should have experience with python packages such as Numpy, Scipy, Scikit-learn, Theano, TensorFlow, Keras, PyTorch, Pandas, and Matplotlib. Experience in working on Azure open AI studio or openai using python or LLAMA or Langchain is required. Moreover, experience in working on Azure function and python flask/api development/streamlit, prompt engineering, conversational AI, and LLM models like word2Vec, Glove, spacy, BERT embedding models is preferred. You are expected to possess distinctive problem-solving, strategic, and analytical capabilities, as well as excellent time-management and organization skills. Strong knowledge in Programming languages like Python, reactjs, SQL, big data is essential. Excellent verbal and written communication skills are necessary for effective interaction between business and technical architects and developers. You should have 2 - 4 years of relevant experience and a Bachelors Degree in Computer Science, Computer Engineering, masters in computer application, MIS, or a related field. End-to-End development experience in deployment of the Machine Learning model using python and Azure ML studio is required. Exposure in developing client-based or web-based software solutions and Certification of Machine Learning and Artificial Intelligence will be beneficial. Good to have experience in power platform or power pages or Azure OpenAI studio. Grant Thornton INDUS comprises GT U.S. Shared Services Center India Pvt Ltd and Grant Thornton U.S. Knowledge and Capability Center India Pvt Ltd. Grant Thornton INDUS is the shared services center supporting the operations of Grant Thornton LLP, the U.S. member firm of Grant Thornton International Ltd. Established in 2012, Grant Thornton INDUS employs professionals across a wide range of disciplines including Tax, Audit, Advisory, and other operational functions. The culture at Grant Thornton INDUS promotes empowered people, bold leadership, and distinctive client service. Working at Grant Thornton INDUS offers an opportunity to be part of something significant and serves communities in India through inspirational and generous services to give back to the communities they work in. Grant Thornton INDUS has its offices in two locations in India Bengaluru and Kolkata.,

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

As a Senior Analytics Consultant in the banking sector, you will leverage your expertise in areas such as credit risk modeling, fraud detection, and marketing analytics to lead client-facing engagements. With over 5 years of experience, you will play a key role in designing and implementing advanced models, translating data insights into strategic recommendations, and ensuring compliance with regulatory standards. Your responsibilities will include leading and managing analytics projects focusing on credit risk, fraud analytics, and marketing analytics for banking clients. You will collaborate with clients to define business problems, develop analytic frameworks, build and validate statistical and machine learning models, and present complex analytical findings in a clear and business-friendly manner. Additionally, you will guide junior team members, contribute to knowledge sharing, and uphold regulatory standards in risk and fraud modeling. To excel in this role, you are required to have a Bachelor's or Master's degree in Statistics, Economics, Mathematics, Computer Science, or a related quantitative discipline. Your hands-on experience in banking analytics, proficiency in SQL and analytical programming languages such as Python, R, or SAS, strong understanding of statistical modeling techniques, and excellent communication skills will be essential. Preferred qualifications include prior consulting experience, familiarity with cloud-based analytics platforms, and exposure to regulatory model validation frameworks. Join us for high-impact projects with top banking institutions, a collaborative team culture, clear paths for career growth, and competitive compensation.,

YASH Technologies is a leading technology integrator specializing in helping clients reimagine operating models, enhance competitiveness, optimize costs, foster exceptional stakeholder experiences, and drive business transformation. At YASH, you will be part of a team of bright individuals working with cutting-edge technologies. Our purpose is to bring about real positive changes in an increasingly virtual world, transcending generational gaps and future disruptions. We are currently looking to hire AI/ML Professionals for the position of AI Engineer with 24 years of experience on a full-time basis. As a highly skilled and motivated Data Scientist at YASH, you will be responsible for leveraging your advanced analytical and technical expertise to solve complex business problems and drive data-driven decisions. Your role will involve designing, developing, and deploying sophisticated machine learning models, performing in-depth data analyses, and collaborating with cross-functional teams to deliver actionable insights. Responsibilities: - Building and deploying ML models for classification, regression, and clustering tasks. - Applying foundational GenAI concepts such as embeddings, summarization, and RAG. - Utilizing APIs and tools like LangChain, vector databases (e.g., Pinecone, FAISS). - Preparing documentation and interpreting results effectively. Required Skills: - Strong hands-on experience in Python, Scikit-learn, and Pandas. - Knowledge of model evaluation, feature engineering, and model tuning. - Exposure to LangChain and vector databases. - Basic familiarity with FastAPI or Flask. At YASH, you will have the opportunity to create a career path that aligns with your aspirations while working in an inclusive team environment. We believe in leveraging career-oriented skilling models and utilizing technology for continuous learning, unlearning, and relearning at a rapid pace and scale. Our workplace culture at YASH is grounded in four principles: - Flexible work arrangements, free spirit, and emotional positivity. - Agile self-determination, trust, transparency, and open collaboration. - Providing all necessary support for the realization of business goals. - Offering stable employment with a great atmosphere and an ethical corporate culture.,

At PwC, as a member of the data and analytics team, your primary focus will be on harnessing data to uncover insights and drive strategic decision-making for clients. Through the use of advanced analytics techniques, you will assist clients in optimizing their operations and achieving their business objectives. In this role, you will be responsible for utilizing your expertise in data manipulation, visualization, and statistical modeling to tackle complex business challenges through data analysis. PwC US - Acceleration Center is currently looking for a skilled GenAI Data Scientist to join our team at the Senior Associate level. As a GenAI Data Scientist, you will be instrumental in the development and implementation of machine learning models and algorithms for our GenAI projects. The ideal candidate should possess a strong background in data science, particularly focusing on GenAI technologies, and demonstrate proficiency in statistical analysis, machine learning, data visualization, and application programming. With a minimum of 4 years of hands-on experience, the successful candidate will have the following responsibilities: - Collaborate with cross-functional teams to understand business requirements and identify opportunities for applying GenAI technologies. - Develop and implement machine learning models and algorithms for GenAI projects. - Perform data cleaning, preprocessing, and feature engineering to prepare data for analysis. - Collaborate with data engineers to ensure efficient data processing and integration into machine learning pipelines. - Validate and evaluate model performance using appropriate metrics and techniques. - Develop and deploy production-ready machine learning applications and solutions. - Utilize object-oriented programming skills to build robust and scalable software components. - Implement Kubernetes for container orchestration and deployment. - Design and build chatbots using GenAI technologies. - Communicate findings and insights to stakeholders through data visualizations, reports, and presentations. - Keep abreast of the latest advancements in GenAI technologies and propose innovative solutions to enhance data science processes. Requirements for this role include: - 3-5 years of relevant technical/technology experience, with a specific focus on GenAI projects. - Proficiency in programming languages such as Python, R, or Scala. - Strong familiarity with machine learning libraries and frameworks like TensorFlow, PyTorch, or scikit-learn. - Experience in data preprocessing, feature engineering, and data wrangling techniques. - Solid grasp of statistical analysis, hypothesis testing, and experimental design. - Knowledge of cloud computing platforms such as AWS, Azure, or Google Cloud. - Proficiency in data visualization tools and techniques. - Excellent problem-solving and analytical skills. - Strong communication and collaboration abilities. - Capability to thrive in a fast-paced and dynamic work environment. Preferred qualifications include: - Experience with object-oriented programming languages such as Java, C++, or C#. - Experience in developing and deploying machine learning applications in production environments. - Understanding of data privacy and compliance regulations. - Relevant certifications in data science or GenAI technologies. Nice to have skills: - Experience with Azure AI Search, Azure Doc Intelligence, Azure OpenAI, AWS Textract, AWS Open Search, AWS Bedrock. - Familiarity with LLM-backed agent frameworks like Autogen, Langchain, Semantic Kernel, etc. - Proficiency in chatbot design and development. Professional and educational background: - Any graduate / BE / B.Tech / MCA / M.Sc / M.E / M.Tech / Masters Degree / MBA.,

This is a full-time position with D Square Consulting Services Pvt Ltd based in Bangalore and requires 6-8 years of experience. The work mode for this role is Onsite and the candidate who can join within 15 days may only apply. As an AI/ML Engineer, you will be responsible for leading the end-to-end design, development, and deployment of advanced AI/ML solutions for digital marketing and analytics. Your role will involve driving innovation, leveraging cutting-edge techniques, and standardizing multi-cloud model deployment through collaboration to deliver profound data insights. To qualify for this role, you should have a Bachelor's degree in Computer Science, Data Science, ML, Mathematics, Statistics, Economics, or related fields with an emphasis on quantitative methods. Additionally, you should possess 6-7 years of experience in software engineering with expertise in the full lifecycle of ML model development, deployment, and operationalization. Your ability to write robust, efficient, and scalable Python, Java, Spark, and SQL code following industry best practices is crucial. You should have extensive experience with major ML frameworks such as TensorFlow, PyTorch, Scikit-learn, advanced deep learning libraries, and strong knowledge of diverse ML algorithms. Experience in deploying and managing AI/ML models on major cloud platforms like Azure, AWS, GCP is required. Experience with LLMs and generative AI is highly desirable. In this role, you will lead cross-functional teams to deliver and scale complex AI/ML solutions, architect, design, develop, train, and evaluate high-performance AI/ML models. You will drive implementation, deployment, and maintenance of AI/ML solutions, oversee data exploration, preprocessing, feature engineering, and data pipeline development. Furthermore, you will establish strategies for continuous testing, validation, and monitoring of deployed AI/ML models, collaborate with senior stakeholders to translate business requirements into scalable AI solutions, and champion the adoption of the latest AI/ML technologies and best practices. Your problem-solving skills, communication abilities, and experience in classification, time series forecasting, customer lifetime value models, LLMs, and generative AI from Retail, eCommerce, or CPG industry will be beneficial in this role. Join us in fostering innovative thinking and continuous improvement in AI/ML technologies to maximize business value.,

Amplework Software is a full-stack development agency that specializes in providing end-to-end software development solutions to clients globally. The company is dedicated to delivering high-quality products that meet business requirements by utilizing advanced technologies. Their expertise includes custom software development, mobile applications, AI-driven solutions, and enterprise applications. By joining Amplework Software, you will become part of an innovative team that is focused on driving digital transformation through technology. As an Mid-Level Python and AI Engineer at Amplework Software, your responsibilities will include assisting in building and training machine learning models using frameworks like TensorFlow, PyTorch, and Scikit-Learn. You will have the opportunity to experiment with pre-trained AI models for NLP, Computer Vision, and Predictive Analytics. Additionally, you will work with both structured and unstructured data, conduct preprocessing, and engage in feature engineering. Collaboration with data scientists and software engineers to integrate AI solutions into real-world applications is a key aspect of this role. Continuously learning, experimenting, and optimizing models to enhance performance and efficiency is also part of the job. Ideal candidates for this position should possess a strong foundation in Python, basic machine learning concepts, and a willingness to learn. Required qualifications include a Bachelor's degree in Computer Science, Engineering, AI, or a related field, proficiency in Python with experience in writing optimized and clean code, strong problem-solving skills, and an understanding of machine learning concepts such as linear regression, classification, decision trees, and feature engineering. Experience with data processing libraries like Pandas, NumPy, and Matplotlib, as well as basic knowledge of AI models and neural networks using frameworks such as Scikit-Learn, TensorFlow, or PyTorch are also required. Preferred qualifications for this role include experience with Natural Language Processing (NLP) using transformers, BERT, GPT, or OpenAI APIs, basic understanding of AI model deployment using Flask, FastAPI, or TensorFlow Serving, experience with SQL or NoSQL databases for querying datasets in AI applications, and participation in AI-related competitions, hackathons, or open-source projects. In addition to technical skills, soft skills and work ethics are also important for this role. Candidates should have a strong analytical and problem-solving mindset, the ability to work collaboratively in a team, communicate technical concepts effectively, eagerness to learn and apply new AI techniques, and excellent English communication skills, both written and verbal. Candidates who prefer strictly rule-based programming without flexibility for AI experimentation may not be suitable for this position due to the requirement for strong problem-solving skills and quick learning abilities. A face-to-face interview will be conducted, and applicants should only apply if they are able to attend the interview at the office. Joining the Amplework Software team offers the opportunity to be part of a passionate and collaborative team, work on cutting-edge projects, make a real impact, enjoy competitive benefits, and experience a great working environment.,

At Lilly, you are part of a global healthcare leader that is committed to uniting caring with discovery to enhance the lives of people worldwide. With our headquarters in Indianapolis, Indiana, our dedicated team of 39,000 employees collaborates to discover and deliver life-changing medicines, enhance disease understanding and management, and contribute to our communities through philanthropy and volunteerism. Our focus is on making a positive impact on people's lives around the world. As part of our ongoing efforts, we are in the process of developing and internalizing a cutting-edge recommendation engine platform. This platform aims to streamline sales and marketing operations by analyzing diverse data sources, implementing advanced personalization models, and seamlessly integrating with other Lilly operations platforms. The goal is to provide tailored recommendations to our sales and marketing teams at the individual doctor level, enabling informed decision-making and enhancing customer experience. Responsibilities: - Utilize deep learning models to optimize Omnichannel Promotional Sequences for sales teams - Analyze large datasets to identify trends and relevant information for modeling decisions - Translate business problems into statistical problem statements and propose solution approaches - Collaborate with stakeholders to effectively communicate analysis findings - Preference for familiarity with pharmaceutical datasets and industry - Experience in code refactoring, model training, deployment, testing, and monitoring for drift - Optimize model hyperparameters and adapt to new ML techniques for business problem-solving Qualifications: - Bachelor's degree in Computer Science, Statistics, or related field (preferred) - 2-6 years of hands-on experience with data analysis, coding, and result interpretation - Proficiency in coding languages like SQL or Python - Prior experience with ML techniques for recommendation engine models in healthcare sectors - Expertise in Feature Engineering, Selection, and Model Validation on Big Data - Familiarity with cloud technology, particularly AWS, and tools like Tableau and Power BI At Lilly, we are committed to promoting workplace diversity and providing equal opportunities for all individuals, including those with disabilities. If you require accommodation during the application process, please complete the accommodation request form on our website. Join us at Lilly and be part of a team dedicated to making a difference in the lives of people worldwide.,