106 Feature Engineering Jobs - Page 4

Job Title: Machine Learning Engineer Location: Bhubaneswar Experience: 4-8 Years Job Description: We are looking for a talented Machine Learning Engineer with 4-8 years of experience to join our team. The ideal candidate will have a strong background in designing, developing, and deploying machine learning models and algorithms to solve complex business problems. You will be responsible for analyzing large datasets, identifying patterns, and creating predictive models to drive business insights and optimization. Key Responsibilities: Develop, implement, and optimize machine learning algorithms to solve business problems. Analyze large datasets to extract valuable insights and patterns for decision-making. Collaborate with cross-functional teams to integrate machine learning solutions into business processes. Conduct model training, evaluation, and fine-tuning to improve accuracy and performance. Stay up-to-date with the latest trends and advancements in machine learning and AI. Must-Have Skills: Strong experience in machine learning frameworks and libraries (TensorFlow, Scikit-learn, Keras, etc.). Proficiency in programming languages like Python or R. Hands-on experience in data preprocessing, feature engineering, and model selection. Knowledge of algorithms for classification, regression, and clustering. Strong understanding of statistics, mathematics, and data modeling. If you are passionate about machine learning and eager to apply your skills to impactful projects, apply now to join our growing team! Job Type: Full-time Schedule: Day shift Morning shift Work Location: In person,

We are Brainlabs, the High-Performance media agency, on a mission to become the world's biggest and best independent media agency. We plan and buy media that delivers profitable and sustained business impact. Our formula for success lies in our Superteams of Brainlabbers, fueled by data and enabled by technology. At Brainlabs, we prioritize our culture above all else. Our shared principles, philosophies, and values, as documented in The Brainlabs Handbook, have shaped our unique culture from the agency's inception. To further enhance and evolve our culture, The Brainlabs Handbook has been refined into The Brainlabs Culture Code. The Brainlabs Culture Code comprises 12 codes that define what it means to be a Brainlabber. It embodies our collective commitment to continuous development, fostering a company where Brainlabbers can excel, build relationships, and achieve success together. As a Specialist in Data Science at Brainlabs, you will report to the Manager, Data Science and operate from our Bengaluru office under an adaptive working model. In this role, you will be a pivotal member of our Data Science team, focusing on developing and deploying machine learning models to tackle intricate business challenges. Your responsibilities will include working with extensive datasets, constructing scalable data pipelines, and collaborating with diverse teams to deliver impactful solutions. If you are enthusiastic about machine learning, data-driven problem-solving, and cutting-edge technology, this position is tailored for you! Your key responsibilities will include developing and maintaining web scraping infrastructure, enhancing data quality through cleaning and transformation, designing and implementing various machine learning models, optimizing model performance, aiding in production deployment, identifying and resolving operational issues, collaborating with engineering and DevOps teams, understanding cross-functional requirements, and effectively communicating technical concepts to stakeholders. To excel in this role, you should possess a Bachelor's or Master's degree in Computer Science, Data Science, or a related field, along with 2-5 years of experience in machine learning model development and deployment. Proficiency in Python and relevant libraries, practical experience in web scraping, familiarity with cloud platforms, and strong communication and collaboration skills are essential. Success in this role will be measured by your ability to efficiently develop and deploy machine learning models with tangible business impact, implement smooth and scalable data pipelines, continuously monitor and optimize model performance, collaborate effectively with cross-functional teams, and communicate technical concepts clearly and insightfully. The recruitment process involves a comprehensive interview series, including skills assessments with our team, to ensure that the role aligns with both your career aspirations and our organizational needs. We understand the challenges of job searching and aim to find the best fit for both you and Brainlabs.,

Position Summary. Drives the execution of multiple business plans and projects by identifying customer and operational needs; developing and communicating business plans and priorities; removing barriers and obstacles that impact performance; providing resources; identifying performance standards; measuring progress and adjusting performance accordingly; developing contingency plans; and demonstrating adaptability and supporting continuous learning. Provides supervision and development opportunities for associates by selecting and training; mentoring; assigning duties; building a team-based work environment; establishing performance expectations and conducting regular performance evaluations; providing recognition and rewards; coaching for success and improvement; and ensuring diversity awareness. Promotes and supports company policies, procedures, mission, values, and standards of ethics and integrity by training and providing direction to others in their use and application; ensuring compliance with them; and utilizing and supporting the Open Door Policy. Ensures business needs are being met by evaluating the ongoing effectiveness of current plans, programs, and initiatives; consulting with business partners, managers, co-workers, or other key stakeholders; soliciting, evaluating, and applying suggestions for improving efficiency and cost-effectiveness; and participating in and supporting community outreach events. What you'll do. About Team Ever wondered what would a convergence of online and offline advertising systems looks like Ever wondered how we can bridge the gap between sponsored search, display, video ad formats Ever thought how we can write our own ad servers which serve billions of requests in near real time Our Advertising Technology team is building an end-to-end advertising platform that is key to Walmarts overall growth strategy. We use cutting edge machine learning, data mining and optimization algorithms to ingest, model and analyze Walmarts proprietary online and in-store data, encompassing 95% of American households. Importantly, we build smart data systems that deliver relevant retail ads and experiences that connect our customers with the brands and products they love. Your Opportunity We are looking for a versatile principal data scientist who has a strong expertise in machine learning, deep learning with good software engineering skills and significant exposure to building ML solutions; including Gen AI solutions scratch up & leading data science engagement. The opportunities that will come with this role are As a seasoned SME in MLE, you will get to work on & take a lead in scaling & deployment for the most challenging of our data science solutions (including , but definitely not limited to Gen-AI solutions) across a broad spectrum of advertising domain. Influence the best practices that we should follow as we scale & deploy our solutions across a diverse set of product. Train and mentor our pool of data scientists in data sciences and MLE skills Contribute to the Tech org via patents, publications & open source contributions. What You Will Do Design large-scale AI/ML products/systems impacting millions of customers Develop highly scalable, timely, highly-performant, instrumented, and accurate data pipelines Drive and ensure that MLOps practices are being followed in solutions Enable data governance practices and processes by being a passionate adopter and ambassador. Drive data pipeline efficiency, data quality, efficient feature engineering, maintenance of different DBs (like Vector DBs, Graph DBs, feature stores, caching mechanism) Lead and inspire a team of scientists and engineers solving AI/ML problems through R&D while pushing the state-of-the-art Lead the team to develop production-level code for the implementation of AI/ML solutions using best practices to handle high-scale and low-latency requirements Deploy batch and real-time ML solutions, model results consumption and integration pipelines. Work with the customer-centric mindset to deliver high-quality business-driven analytic solutions. Drive proactive optimisation of code and deployments, improving efficiency, cost and resource optimisation. Design model architecture, optimal Tech stack and model choices, integration with larger engineering ecosystem, drive best-practices of model integrations working closely with Software Engineering leaders Consult with business stakeholders regarding algorithm-based recommendations and be a thought-leader to deploy these & drive business actions. Closely partners with the Senior Managers & Director of Data Science, Engineering and product counterparts to drive data science adoption in the domain Collaborate with multiple stakeholders to drive innovation at scale Build a strong external presence by publishing your team's work in top-tier AI/ML conferences and developing partnerships with academic institutions Adhere to Walmart's policies, procedures, mission, values, standards of ethics and integrity Adopt Walmart's quality standards, develop/recommend process standards and best practices across the retail industry. Drive data pipeline efficiency, data quality, efficient feature engineering, maintenance of different DBs (like Vector DBs, Graph DBs, feature stores, caching mechanism). Deploy batch and real-time ML solutions, model results consumption and integration pipelines. Design model architecture, Optimal Tech stack and model choices, integration with larger engineering ecosystem, drive best-practices of model integrations working closely with Software Engineering leaders. Drive proactive optimisation of code and deployments, improving efficiency, cost and resource optimisation. What You Will Bring Bachelors with > 13 years or Master's with > 12 years OR Ph.D. with > 10 years of relevant experience. Educational qualifications should be in Engineering / Data sciences. Strong experience working with state-of-the-art supervised and unsupervised machine learning algorithms on real-world problems. Experienced in architecting solutions with Continuous Integration and Continuous Delivery in mind. Strong experience in real time ML solution deployment Experience with deployment patterns for Distributed Systems. Strong Python coding and package development skills. Experience with Big Data and analytics in general leveraging technologies like Hadoop, Spark, and MapReduce. Ability to work in a big data ecosystem - expert in SQL/Hive/Spark. About Walmart Global Tech: Imagine working in an environment where one line of code can make life easier for hundreds of millions of people and put a smile on their face. Thats what we do at Walmart Global Tech. Were a team of 15,000+ software engineers, data scientists and service professionals within Walmart, the worlds largest retailer, delivering innovations that improve how our customers shop and empower our 2.3 million associates. To others, innovation looks like an app, service, or some code, but Walmart has always been about people. People are why we innovate, and people power our innovations. Being human led is our true disruption. Flexible, hybrid work: We use a hybrid way of working that is primarily in office coupled with virtual when not onsite. Our campuses serve as a hub to enhance collaboration, bring us together for purpose and deliver on business needs. This approach helps us make quicker decisions, remove location barriers across our global team and be more flexible in our personal lives. Benefits: Beyond our great compensation package, you can receive incentive awards for your performance. Other great perks include a host of best-in-class benefits maternity and parental leave, PTO, health benefits, and much more. Equal Opportunity Employer: Walmart, Inc. is an Equal Opportunity Employer By Choice. We believe we are best equipped to help our associates, customers and the communities we serve live better when we really know them. That means understanding, respecting and valuing diversity- unique styles, experiences, identities, ideas and opinions while being inclusive of all people. Minimum Qualifications. Outlined below are the required minimum qualifications for this position. If none are listed, there are no minimum qualifications. Minimum Qualifications:Option 1: Bachelors degree in Statistics, Economics, Analytics, Mathematics, Computer Science, Information Technology or related field and 5 years" experience in an analytics related field. Option 2: Masters degree in Statistics, Economics, Analytics, Mathematics, Computer Science, Information Technology or related field and 3 years" experience in an analytics related field. Option 3: 7 years" experience in an analytics or related field. Preferred Qualifications. Outlined below are the optional preferred qualifications for this position. If none are listed, there are no preferred qualifications. Primary Location. G, 1, 3, 4, 5 Floor, Building 11, Sez, Cessna Business Park, Kadubeesanahalli Village, Varthur Hobli , India R-1925040,

Ready to shape the future of work At Genpact, we don&rsquot just adapt to change&mdashwe drive it. AI and digital innovation are redefining industries, and we&rsquore leading the charge. Genpact&rsquos , our industry-first accelerator, is an example of how we&rsquore scaling advanced technology solutions to help global enterprises work smarter, grow faster, and transform at scale. From large-scale models to , our breakthrough solutions tackle companies most complex challenges. If you thrive in a fast-moving, tech-driven environment, love solving real-world problems, and want to be part of a team that&rsquos shaping the future, this is your moment. Genpact (NYSE: G) is an advanced technology services and solutions company that delivers lasting value for leading enterprises globally. Through our deep business knowledge, operational excellence, and cutting-edge solutions - we help companies across industries get ahead and stay ahead. Powered by curiosity, courage, and innovation , our teams implement data, technology, and AI to create tomorrow, today. Get to know us at and on , , , and . Inviting applications for the role of Consultant, Senio r Data Scientist ! In this role, you will have a strong background in Gen AI implementations, data engineering, developing ETL processes, and utilizing machine learning tools to extract insights and drive business decisions. The Data Scientist will be responsible for analysing large datasets, developing predictive models, and communicating findings to various stakeholders Responsibilities Develop and maintain machine learning models to identify patterns and trends in large datasets. Utilize Gen AI and various LLMs to design & develop production ready use cases. Collaborate with cross-functional teams to identify business problems and develop data-driven solutions. Communicate complex data findings and insights to non-technical stakeholders in a clear and concise manner. Continuously monitor and improve the performance of existing models and processes. Stay up to date with industry trends and advancements in data science and machine learning. Design and implement data models and ETL processes to extract, transform, and load data from various sources. Good hands own experience in AWS bedrock models, Sage maker, Lamda etc Data Exploration & Preparation - Conduct exploratory data analysis and clean large datasets for modeling. Business Strategy & Decision Making - Translate data insights into actionable business strategies. Mentor Junior Data Scientists - Provide guidance and expertise to junior team members. Collaborate with Cross-Functional Teams - Work with engineers, product managers, and stakeholders to align data solutions with business goals. Qualifications we seek in you! Minimum Qualifications Bachelor%27s / Master%27s degree in computer science , Statistics, Mathematics, or a related field. Relevant years of experience in a data science or analytics role. Strong proficiency in SQL and experience with data warehousing and ETL processes. Experience with programming languages such as Python & R is a must . (either one ) Familiarity with machine learning tools and libraries such as Pandas, scikit-learn and AI libraries. Having excellent knowledge in Gen AI, RAG, LLM Models & strong understanding of prompt engineering. Proficiency in Az Open AI & AWS Sagemaker implementation. Good understanding statistical techniques such and advanced machine learning Experience with data warehousing and ETL processes. Proficiency in SQL and database management. Familiarity with cloud-based data platforms such as AWS, Azure, or Google Cloud. Experience with Azure ML Studio is desirable. Knowledge of different machine learning algorithms and their applications. Familiarity with data preprocessing and feature engineering techniques. Preferred Qualifications/ Skills Experience with model evaluation and performance metrics. Understanding of deep learning and neural networks is a plus. Certified in AWS Machine learning , AWS Infra engineer is a plus Why join Genpact Be a transformation leader - Work at the cutting edge of AI, automation, and digital innovation Make an impact - Drive change for global enterprises and solve business challenges that matter Accelerate your career - Get hands-on experience, mentorship, and continuous learning opportunities Work with the best - Join 140,000+ bold thinkers and problem-solvers who push boundaries every day Thrive in a values-driven culture - Our courage, curiosity, and incisiveness - built on a foundation of integrity and inclusion - allow your ideas to fuel progress Come join the tech shapers and growth makers at Genpact and take your career in the only direction that matters: Up. Let&rsquos build tomorrow together. Genpact is an Equal Opportunity Employer and considers applicants for all positions without regard to race, color , religion or belief, sex, age, national origin, citizenship status, marital status, military/veteran status, genetic information, sexual orientation, gender identity, physical or mental disability or any other characteristic protected by applicable laws. Genpact is committed to creating a dynamic work environment that values respect and integrity, customer focus, and innovation. Furthermore, please do note that Genpact does not charge fees to process job applications and applicants are not required to pay to participate in our hiring process in any other way. Examples of such scams include purchasing a %27starter kit,%27 paying to apply, or purchasing equipment or training.

Job Description Design and develop machine learning models tailored to mechanical engineering challenges, including predictive modelling, simulation optimisation, and failure analysis. Utilise deep learning and other advanced ML techniques to improve the accuracy and efficiency of CAE simulations. Preprocess and analyse large datasets from CAE simulations, experimental tests, and manufacturing processes for modelling. Train, validate, and fine-tune machine learning models using real-world engineering data. Optimise models for performance, scalability, and robustness in production environments. Collaborate with CAE engineers to integrate ML models into existing simulation workflows (e.g., FEA, CFD, structural analysis). Automate repetitive simulation tasks and enable predictive analytics for design optimisation. Work closely with mechanical engineers, data scientists, and software developers to identify business challenges and develop data-driven solutions. Deploy machine learning models into production environments and monitor their performance. Maintain and update models to ensure reliability and continuous improvement. Stay abreast of the latest advancements in machine learning, AI, and CAE technologies. Apply innovative approaches to solve complex engineering problems. Requirements Bachelors or Master’s degree in Mechanical Engineering, Computer Science, or a related field Proven 2-3 years of experience in developing and deploying machine learning models, preferably in mechanical engineering or CAE domain Hands-on experience with CAE tools such as ANSYS, Abaqus, or similar FEA/CFD software Strong programming skills in Python, R, or Java Proficiency in machine learning frameworks (TensorFlow, PyTorch, scikit-learn) Experience with data preprocessing, feature engineering, and statistical analysis Solid understanding of mathematics, statistics, and problem-solving skills Excellent analytical thinking and ability to tackle complex engineering challenges Strong communication and teamwork skills to collaborate across disciplines Preferred: Experience with physics-informed machine learning and digital twin technologies Preferred: Familiarity with automation of CAE workflows and predictive modelling for product design Benefits Challenging job and a chance to team up with a young and dynamic professional group Chance to build yourself as WE grow. Remuneration that stays competitive and attractive to retain the best. Opportunity to join an organization experiencing year on year growth.

AI / Machine Learning / Data Science part time Work from Home (Any where in world) Warm Greetings from Excel Online Classes, We are a team of industry professionals running an institute that provides comprehensive online IT training, technical support, and development services. We are currently seeking AI / Machine Learning / Data Science Experts who are passionate about technology and can collaborate with us in their free time. If you're enthusiastic, committed, and ready to share your expertise, we would love to work with you! Were hiring for the following services: Online Training Online Development Online Technical Support Conducting Online Interviews Corporate Training Proof of Concept (POC) Projects Research & Development (R&D) We are looking for immediate joiners who can contribute in any of the above areas. If you're interested, please fill out the form using the link below: https://docs.google.com/forms/d/e/1FAIpQLSdvut0tujgMbBIQSc6M7qldtcjv8oL1ob5lBc2AlJNRAgD3Cw/viewform We also welcome referrals! If you know someone—friends, colleagues, or connections—who might be interested in: Teaching, developing, or providing tech support online Sharing domain knowledge (e.g., Banking, Insurance, etc.) Teaching foreign languages (e.g., Spanish, German, etc.) Learning or brushing up on technologies to clear interviews quickly Upskilling in new tools or frameworks for career growth Please feel free to forward this opportunity to them. For any queries, feel free to contact us at: excel.onlineclasses@gmail.com Thank you & Best Regards, Team Excel Online Classes excel.onlineclasses@gmail.com

Strong expertise in deploying machine learning models in real-world environments. Hands-on experience in Automated Valuation Models (AVM) , LangChain , and LLM-powered applications . Proficiency with Python-based data science tools like Pandas , NumPy , Scikit-learn , XGBoost , and LightGBM . Skilled in feature engineering , data intelligence extraction , and handling structured, semi-structured, and unstructured data . Experience integrating models into APIs and production environments.

Strong expertise in deploying machine learning models in real-world environments. Hands-on experience in Automated Valuation Models (AVM) , LangChain , and LLM-powered applications . Proficiency with Python-based data science tools like Pandas , NumPy , Scikit-learn , XGBoost , and LightGBM . Skilled in feature engineering , data intelligence extraction , and handling structured, semi-structured, and unstructured data . Experience integrating models into APIs and production environments.

Strong expertise in deploying machine learning models in real-world environments. Hands-on experience in Automated Valuation Models (AVM) , LangChain , and LLM-powered applications . Proficiency with Python-based data science tools like Pandas , NumPy , Scikit-learn , XGBoost , and LightGBM . Skilled in feature engineering , data intelligence extraction , and handling structured, semi-structured, and unstructured data . Experience integrating models into APIs and production environments.

description 5+ years with Azure (ML pipeline components), Azure Databricks, Azure DevOps. Proven experience of design and deployment of end-to-end ML pipelines. Experience with building infrastructure for classic DS models and/or LLM/SLMs. 2+ years with orchestration (e.g., Kubeflow, Airflow, Azure Data Factory) and CI/CD for ML. Experience deploying containerized ML solutions (e.g. Docker/Kubernetes). Knowledge of model and data versioning (e.g. MLflow, DVC). Knowledge of MLSecOps (security in the context of MLOps) Experience with Infrastructure as a Code (e.g., Terraform, CloudFormation). Essential functions List of identified areas for improvements for existing PepsiCo project Recommendation on: MLOps practice MLSecOps Sample templates and pipelines Recommendation on the infrastructure for: Classic DS models LLM solution, primarily focused on fine tuning SLM by domain Recommendation on Data Strategy: JIT access to data for the period of training with security guardrails (access, data masking, etc.) Qualifications Azure Databricks, Azure DevOps. ML Ops ML SecOps Classic DS Model Would be a plus Knowledge of MLOps for LLM/SLM Experience in ML system/architecture design (load balancing, caching, failover). Knowledge in building scalable, resilient ML architectures. Cross-team collaboration experience (data science, engineering, DevOps). Experience with monitoring/logging for production models (e.g. Prometheus, Grafana, ELK stack).

1. Project description Migration of User Knowledge Objects from Splunk to Clickhouse / Grafana / Bosun: PRE Observability team is undertaking a large-scale observability transformation initiative aimed at migrating from Splunk to a more cost-effective and scalable open-source observability stack based on Clickhouse and Grafana. As part of this effort, we are seeking POD-based teams to support the migration of user knowledge objects such as dashboards, reports, alerts, macros and lookups. 2. Client description 3. Key Responsibilities: Lead the design, development, and deployment of AI-based automation tools for data artifact migration. Develop machine learning models to intelligently map, transform, and validate data across different big data platforms. Build robust data pipelines to handle high-volume, high-velocity data migration. Collaborate with data engineers and architects to integrate AI-driven solutions into existing data workflows. Implement NLP and pattern recognition algorithms to automate schema conversion and data validation. Design custom algorithms for automated data quality checks and anomaly detection. Mentor junior engineers and contribute to technical leadership within the AI engineering team. Stay updated with the latest advancements in AI, big data technologies, and automation frameworks. Create comprehensive technical documentation and best practice guidelines for AI-based data migration. 4. Details on tech stack Splunk ClickHouse Grafana Data Migration Automation

Job Summary: - Data Scientist with good hands-on experience of 3+ years in developing state of the art and scalable Machine Learning models and their operationalization, leveraging off-the-shelf workbench production. Job Responsibilities: - 1. Hands on experience in Python data-science and math packages such as NumPy, Pandas, Sklearn, Seaborn, PyCaret, Matplotlib 2. Proficiency in Python and common Machine Learning frameworks (TensorFlow, NLTK, Stanford NLP, PyTorch, Ling Pipe, Caffe, Keras, SparkML and OpenAI etc.) 3. Experience of working in large teams and using collaboration tools like GIT, Jira and Confluence 4. Good understanding of any of the cloud platform AWS, Azure or GCP 5. Understanding of Commercial Pharma landscape and Patient Data / Analytics would be a huge plus 6. Should have an attitude of willingness to learn, accepting the challenging environment and confidence in delivering the results within timelines. Should be inclined towards self motivation and self-driven to find solutions for problems. 7. Should be able to mentor and guide mid to large sized teams under him/her Job Requirements: - 1. Strong experience on Spark with Scala/Python/Java 2. Strong proficiency in building/training/evaluating state of the art machine learning models and its deployment 3. Proficiency in Statistical and Probabilistic methods such as SVM, Decision-Trees, Bagging and Boosting Techniques, Clustering 4. Proficiency in Core NLP techniques like Text Classification, Named Entity Recognition (NER), Topic Modeling, Sentiment Analysis, etc. Understanding of Generative AI / Large Language Models / Transformers would be a plus Qualification: - - B-Tech or BE in Computer Science / Computer Applications from Tier 1-2 college with 3+ years of proven experience in the field of Advanced Analytics or Machine Learning OR - Master's degree in Machine Learning / Statistics / Econometrics, or related discipline from Tier 1-2 college with 3+ years of experience Must have Skills: - Real-world experience in implementing machine learning/statistical/econometric models/advanced algorithms Breadth of machine learning domain knowledge Experience in application of machine learning algorithms (classification, regression, deep learning, NLP, etc.) Experience with a ML/data-centric programming language (such as Python, Scala, or R) and ML libraries (pandas, numpy, scikit-learn, etc.) Experience with Apache Hadoop / Spark (or equivalent cloud-computing/map-reduce framework) Skills that give you an edge: - Strong analytical skills to solve and model complex business requirements are a plus. With life sciences or pharma background. We will provide (Employee Value Proposition) Offer an inclusive environment that encourages diverse perspectives and ideas Deliver challenging and unique opportunities to contribute to the success of a transforming organization Opportunity to work on technical challenges that may impact across geographies Vast opportunities for self-development: online Axtria Institute, knowledge sharing opportunities globally, learning opportunities through external certifications Sponsored Tech Talks & Hackathons Possibility to relocate to any Axtria office for short and long-term project

Design, develop, and deploy AI/ML models; build scalable, low-latency ML infrastructure; run experiments; optimize algorithms; collaborate with data scientists, engineers, and architects; integrate models into production to drive business value. Required Candidate profile 5–10 yrs in AI/ML, strong in model development, optimization, and deployment. Skilled in Azure, ML pipelines, data science tools, and collaboration with cross-functional teams.

Job Description AI/ML Engineer We are seeking a sharp, innovative, and passionate AI/ML Engineer to join our R&D team. You will be responsible for designing and deploying intelligent algorithms that enhance the predictive capabilities of our remote diagnostics platform used in railway signaling and other critical infrastructure. Responsibilities: Build and deploy machine learning and deep learning models for predictive maintenance and anomaly detection. Analyze time-series sensor data to develop accurate failure prediction models. Work with massive datasets – cleaning, preprocessing, feature engineering, and model tuning. Develop and expose ML models as REST APIs for integration into cloud-based systems. Collaborate with domain experts, data engineers, and full stack developers to create robust, production-grade solutions. Perform continuous evaluation and improvement of deployed models (MLOps). Stay updated with the latest AI research and evaluate them for real-world application. Required Skills & Qualifications: 2–5 years of experience in AI/ML project development and deployment. Proficiency in Python , Scikit-learn , Pandas , NumPy . Hands-on experience with TensorFlow or PyTorch . Solid understanding of ML algorithms , classification , regression , clustering , NLP , or computer vision . Experience with model deployment , APIs , and Docker . Knowledge of cloud platforms (AWS/GCP/Azure) is a plus. Strong problem-solving skills and understanding of statistical concepts. Nice to Have: Experience with time-series forecasting and anomaly detection. Prior exposure to predictive maintenance in industrial environments. Familiarity with IoT data and sensor networks.

Role Summary: The Senior Data Scientist is a technical leadership role with direct accountability for the delivery of multiple projects within FMCG including the management of the analytics quality on these projects. The Senior Data Scientist collaborates closely with other Data Scientists and consultants on projects (across the FMCG client portfolio) to transform client questions and issues into analytical solutions. Key responsibilities: Accountable for the analytics quality and delivery of key FMCG projects. Transforming client questions and issues into analytical solutions, through partnering with Consultants to scope solutions and ensure projects are successfully delivering value to clients. Task management including overseeing and delegating technical tasks amongst data scientists. Team management: leading a small team of technical analysts (~1-3 direct reports). Key activities: * Accountable for the analytics quality and delivery of key FMCG projects: Delivery and build of analytical solutions, transforming transaction- or customer-level data sets into client ready strategic insights e.g. data exploration, cleansing, manipulation, extracting insights, and clear presentation via spreadsheets, PowerPoint presentations and self-service analytical visualization tools. Task management including overseeing and delegating technical tasks amongst analysts within project team, including reviewing code, analysis and outputs. Design and be accountable for solution design, analytical methodology / technique and quality assurance for analytical projects. Providing estimates of work effort, timeframes, costings and resourcing for analytical tasks. * Partnering with consultants to ensure projects are successfully delivered and providing value to clients: Convert data into meaningful, actionable recommendations for Quantium's clients. Transforming client questions and issues into analytical solutions, through project scoping and solution design. * Team management: leading a small team of Data Scientists: Directly manage all direct reports, managing on-boarding, driving their performance, supporting their development & progression and managing the formal performance review process. Provide technical guidance for direct reports and other analysts within the project team as needed / on a day-to-day basis. Support team initiatives, such as interviewing candidates, facilitating team training or knowledge sharing, or organizing events. Be a role model of Quantium's DNA and support a culture of collaboration, innovation, high-performance and fun. Experience and education required: 1. Approximately 5+ years experience in a highly technical analytics environment, carrying out data analytics or data science work. Strong coding experience in SQL. Experience in working with large datasets to solving commercial business problems (customer-level and/or sales transaction-level datasets preferred). Advanced knowledge of technical analytics discipline, including data preparation, feature engineering and foundational analytics concepts, model development and model training. 2. Well-developed commercial acumen to understand business needs and be able suggest the commercial impacts of different analytics solutions or approaches. Experience transforming client questions and issues into analytical solutions, through project scoping and solution design. Experience in FMCG/CPG or Retail industry (preferred). Experience working in consulting environment (preferred). 3. Experience in supervising the work of others as a senior team member, project manager or team leader. 4. Experience with successfully managing either internal and external stakeholders, delivering against projects, tasks and activities in a dynamic deadline driven environments. 5. Experience and interest in people management, mentoring and development. 6.Tertiary qualifications in engineering, mathematics, actuarial studies, statistics, physics, or a related discipline. Key business capabilities required: 1. Resource Planning - Coordination of resources effectively to achieve committed client outcomes at a high level of quality. 2. Client Project Planning - Effective capture, planning and management of the series of inter-related activities involved in delivering the agreed client scope of work, including managing dependencies, making decisions on variances to the original plan and aligning stakeholders. 3. Client Project Delivery- Effective management that integrates people, systems, structures and practices across Quantium and a client organization to ensure high quality project delivery. 4. Business and Product Requirements - Ability to effectively translate business and client needs or problems into an a sustainable technical or product solution. 5. Method Evaluation - Assess the appropriateness of the solution to the original problem and the application of the method. 6. Method Selection - Choose the appropriate type of analytics or modelling to best solve the problem, given all inputs and prescribed outputs. 7. Method Design - Design the most appropriate structure for the method that best solves the problem, given inputs and prescribed outputs. 8. Insight Generation: Convert information into meaningful, actionable recommendations for Quantium's clients and partners. Key People and leadership capabilities required: 1. Self-aware - you leverage diversity across people, tasks, client interactions and projects, taking responsibility for self and other. 2. Agile and innovative - you possess strong lateral thinking skills and actively develop these in others. 3. Achieve and perform - you have exceptional execution skills and are achievement focused. 4. Brand advocate - you anticipate and consider brand and cultural impact in decision making. 5. Purposeful and aligned - you can set clear, tangible objectives which deliver against our strategy. 6. Achievement oriented - you effectively facilitate challenging performance related conversations in a timely and appropriate manner. 7. Coach - you demonstrate the ability to coach and develop others while facilitating learning, growth and engagement.

About the team: In this role, you will be part of the GDM Analytics team, with responsibility to support all efforts to enhance our team's sales data analytics capabilities. You will be required to coordinate our efforts and actions with the nine market units. Keeping constant client and broker focus with particular emphasis on our growth initiatives and sales campaigns will be important. Minimum qualifications: Bachelor's , Master's or PHD in Statistics, Mathematics, Data Science, Computer Science or a related quantitative field. At least 5 years of work experience with analysis applications (e.g., extracting insights, performing statistical analysis, or solving business problems), and coding (e.g., Python, R, SQL). Commercial Insurance experience would be a plus. Job Requirements: Work with stakeholders throughout the GDM organization to identify opportunities for leveraging data to drive business solutions. Mine and analyze data from Sales Analytics databases to drive efficiency improvements and meet growth objectives. Assess the effectiveness and accuracy of new data sources and data gathering techniques. Develop custom data models and algorithms to apply to data sets. Develop and automate reports, iteratively build dashboards to provide insights at scale, solving for business priorities. Develop processes and tools to monitor and analyze model performance and data accuracy. Collaborate with cross-functional teams to understand business requirements and identify opportunities for applying GenAI technologies Stay up to date with the latest advancements in GenAI technologies and recommend innovative solutions to enhance data science processes. Deliver effective presentations of findings and recommendations to multiple levels of stakeholders, creating visual displays of quantitative information. Manage stakeholders, solicit ideas, prioritize, and manage expectations. About you: Strong problem-solving skills with an emphasis on solution development. Experience with analysis applications (e.g., extracting insights, performing exploratory data analysis, or solving business problems), and coding (e.g., Python, R, SQL) to manipulate data and draw insights from large datasets. Proficiency in machine learning libraries and frameworks such as TensorFlow, PySpark, scikit-learn. Experience with data preprocessing, feature engineering, and data wrangling techniques. Solid understanding of probability concepts, statistical analysis, hypothesis testing, and experimental design. Experience with Large Language and other Machine Learning models to analyze structured and unstructured data (e.g., for Natural Language Processing). Knowledge of a variety of machine learning techniques (clustering, ensembles, artificial neural networks, etc.) and their real-world advantages/drawbacks. Excellent written and verbal communication skills for coordinating across teams. A drive to learn and master new technologies and techniques. Keywords: Reference Code: 134304

Role & responsibilities : Hands-on experience in relevant field (within essential requirement of post basic qualification experience) in: Proven track record in Database Performance Tuning, Database Security, Promoting Process Improvement, Problem Solving, Presenting Technical Information, Quality Focus, Database Management, Data Maintenance, Operating Systems, Attention to Detail, Information Security Policies Proven enterprise database administration experience in Oracle/Microsoft SQL Server Proficient in design and development of relational (& optionally hierarchical) databases, including ability to design for performance, scalability, availability, flexibility & extensibility, meeting security requirements. Strong knowledge of database engineering activities, including installation and configuration of RDBMS software. Work Experience as Database Administrator (DBA) Oracle Database 19C/ RAC configuration/ Oracle Golden Gate configuration. Experience with any Application Performance Monitoring Tools such as Dynatrace / AppDynamics BASIC QUALIFICATION (AS ON 31.03.2025): B.Tech / B.E. in Computer Science/ Computer Science & Engineering/ Information Technology/ Electronics/ Electronics & Communications Engineering or Equivalent Degree in above specified disciplines with minimum 60% score. Or MCA or equivalent Or M.Tech / M.Sc. in Computer Science/ Computer Science & Engineering/ Information Technology/ Electronics/ Electronics & Communications Engineering or Equivalent Degree in above specified disciplines. (From a University/ Institution/ Board recognised by Govt. Of India/ approved by Govt. Regulatory Bodies) OTHER QUALIFICATION (AS ON 31.03.2025) Preferred Certifications: (valid as on 31.03.2025) Oracle Certified Associate (OCA) Database Administrator Oracle Certified Professional (OCP) SQL Queries and PL/SQL WORK EXPERIENCE : Minimum 6 years post qualification experience in IT Industry.

B.Tech/ Master's in Data Science /Computer Science/ Statistics /Applied Mathematics or Equivalent Degree in above specified disciplines with minimum 50% score. (From a University/ Institution/ Board recognised by Govt. Of India/ approved by Govt. Regulatory Bodies) OTHER QUALIFICATION (ASON 31.03.2025) Preferred Certifications: (Valid as on 31.03.2025) Experience with cloud platforms (e.g., AWS, Azure, Google Cloud) and big data technologies. WORK EXPERIENCE(POST-BASIC QUALIFICATION) (AS ON 31.03.2025) Minimum 6 years post qualification experience in IT Industry. Role & responsibilities Hands-on experience in relevant field (within essential requirement of post basic qualification experience) in: post qualification experience in IT/Data Science in BFSI sector out of which min. 1 year experience as a Data Scientist Programming Statistics and probability Data wrangling and database management Machine learning and deep learning Data visualization Cloud computing

What You Need Masters in Computer Science, Computer Engineering or other relevant fields (PhD Preferred) 8+ years of experience in Data Science (healthcare experience will be a plus) Strong hands-on experience in Python - building enterprise applications along with optimization techniques. Strong experience with deep learning techniques to build NLP/Computer vision models as well as state of art GenAI pipelines - knowledge of implementing agentic workflows is a plus. Has demonstrable experience deploying deep learning models in production at scale with interactive improvements- would require hands-on expertise with at least 1 deep learning frameworks like Pytorch or Tensorflow. Has keen interest in research and stays updated with key advancements in the area of AI and ML in the industry. Deep understanding of classical ML techniques - Random Forests, SVM, Boosting, Bagging - and building training and evaluation pipelines. Demonstrate experience with global and local model explainability using LIME, SHAP and associated techniques. Hands on experience with at least one ML platform among Databricks, Azure ML, Sagemaker s Experience in developing and deploying production ready models Knowledge of implementing an MLOps framework. Possess a customer-focused attitude through conversations and documentation Here s What We Offer Generous Leave Benefits: Enjoy generous leave benefits of up to 40 days. Parental Leave: Experience one of the industrys best parental leave policies to spend time with your new addition. Sabbatical Leave Policy: Want to focus on skill development, pursue an academic career, or just take a break Weve got you covered. Health Insurance: We offer health benefits and insurance to you and your family for medically related expenses related to illness, disease, or injury. Pet-Friendly Office*: Spend more time with your treasured friends, even when youre away from home. Bring your furry friends with you to the office and let your colleagues become their friends, too. *Noida office only Creche Facility for children*: Say goodbye to worries and hello to a convenient and reliable creche facility that puts your childs well-being first. *India offices

Description We are seeking an experienced Data Scientist with a strong focus on Machine Learning to join our team in India. The ideal candidate will have 5-15 years of experience in applying machine learning techniques to real-world problems, with a deep understanding of data analysis and statistical modeling. Responsibilities Designing and implementing machine learning models to solve complex business problems. Conducting data analysis to identify trends and patterns in large datasets. Collaborating with cross-functional teams to define data requirements and deliver insights. Presenting findings and recommendations to stakeholders in a clear and concise manner. Continuously improving existing machine learning algorithms and processes. Skills and Qualifications Proficiency in programming languages such as Python, R, or Java. Experience with machine learning frameworks such as TensorFlow, Keras, or PyTorch. Strong understanding of statistical analysis and data mining techniques. Familiarity with big data technologies like Hadoop, Spark, or similar. Experience with data visualization tools such as Tableau, Power BI, or Matplotlib. Ability to work with large datasets and perform data cleaning and preprocessing. Strong problem-solving skills and attention to detail. Excellent communication skills to convey complex concepts to non-technical stakeholders.

Looking for a highly skilled Senior Machine Learning Engineering Lead to oversee and drive machine learning initiatives focusing on time series analysis, process curve analysis, tabular data, and feature engineering. In this role, you will lead a team of engineers and data scientists, ensuring the effective delivery of machine learning solutions to customers. You will also be responsible for designing efficient workflows, building robust CI/CD pipelines, and handling client interactions to deliver high-quality solutions on time.Roles & Responsibilities: Machine Learning and Data Engineering: Time Series Analysis : Develop and implement advanced machine learning models for analyzing time-series data (e.g., forecasting, anomaly detection). Process Curve Analysis : Apply machine learning techniques to analyze process curves, optimize processes, and predict system behavior based on historical data. Tabular Data : Manage and work with structured/tabular datasets to build models that deliver actionable insights. Feature Engineering : Design and implement innovative feature engineering techniques to enhance model performance, ensuring that features align with business goals. Model Development and Optimization : Develop, test, and optimize machine learning models and algorithms for various business use cases. Leadership and Team Management: Team Mentorship : Lead a team of machine learning engineers and data scientists, providing guidance and mentorship to junior team members. Collaboration : Work closely with data scientists, software engineers, product managers, and other stakeholders to design, implement, and deliver end-to-end solutions. Customer Handling : Serve as the primary point of contact for customers, gathering requirements, addressing technical challenges, and ensuring the timely delivery of high-quality solutions. Client Deliverables : Ensure all project milestones are met, and machine learning models and solutions are aligned with customer expectations. Pipeline and Workflow Design: CI/CD Pipeline : Design and maintain robust CI/CD pipelines for machine learning model training, validation, and deployment, ensuring efficient and automated workflows. Model Deployment and Monitoring : Oversee the deployment of machine learning models into production, ensuring they meet performance, reliability, and scalability requirements. Automated Workflows : Build automated workflows for data pipelines, model training, evaluation, and reporting, ensuring seamless integration with business processes. Quality Assurance and Optimization: Performance Monitoring : Monitor model performance post-deployment, identifying and addressing any issues related to accuracy, speed, or scalability. Process Improvement : Continuously evaluate and improve model development practices, machine learning pipelines, and workflows to drive efficiency and reduce time-to-market. Documentation : Ensure that all models, pipelines, and processes are well-documented and easily reproducible for future iterations or modifications. Required skills:Technical Skills: Programming Languages : Proficiency in Python, R, or other relevant languages (e.g., Java, Scala). Machine Learning Frameworks : Expertise in ML libraries like scikit-learn, TensorFlow, Keras, XGBoost, PyTorch, etc. Time Series Analysis : Experience with time-series forecasting models (ARIMA, LSTM, Prophet, etc.) and anomaly detection. Data Engineering : Expertise in working with large-scale datasets and tools like Pandas, NumPy, SQL, and data wrangling techniques. Feature Engineering : Strong skills in creating meaningful features to improve model accuracy and performance. CI/CD Tools : Experience with CI/CD tools like Jenkins, GitLab, CircleCI, or similar platforms for automating deployment workflows. Cloud Platforms : Experience with cloud computing services like AWS, GCP, or Azure for model deployment and scalability. Version Control : Proficient in using Git for version control and collaboration. Soft Skills: Strong leadership and team management skills, with a focus on mentoring and development of team members. Excellent communication skills for handling customer interactions, explaining technical concepts to non-technical stakeholders, and delivering presentations. Problem-solving mindset with the ability to analyze complex data and identify actionable insights. Highly organized, detail-oriented, and able to manage multiple projects simultaneously. Experience: 8+ years of experience in machine learning engineering with a focus on time-series analysis, process curve analysis, tabular data, and feature engineering. At least 3-5 years of leadership experience managing teams and handling customer-facing responsibilities. Strong experience in designing and deploying ML models in production environments. Proven track record of successfully managing client relationships and delivering high-quality solutions on time. Experienced in working in cross-functional, international setups Entrepreneurial, business-driven mindset. Preferred Expertise: Experience in deploying models at scale using containerization technologies like Docker and Kubernetes. Knowledge of MLOps principles and practices. Background in domain-specific areas (e.g., manufacturing, finance, healthcare) related to time-series and process data. Qualifications B.E./ M.E./M. Tech in Computer Science Engineering, Ph. D is plus

About Us: At Novus Loyalty, we are committed to building cutting-edge AI-driven solutions that enhance business performance and user experience. We are currently seeking a skilled and passionate AI Engineer to join our team, with a strong emphasis on Azure AI technologies. Key Responsibilities: Design, develop, and deploy AI models using Azure AI services. Work on various AI domains, including Generative AI, Agentic AI, and other advanced ML models. Collaborate with cross-functional teams to integrate AI solutions into production environments. Conduct data analysis and preprocessing to support model development. Monitor and optimize AI model performance and accuracy. Stay up-to-date with emerging AI technologies, tools, and best practices. Required Qualifications: Minimum 3 years of hands-on experience in AI/ML model development. Proven experience with Azure AI services (e.g., Azure Machine Learning, Cognitive Services, Azure OpenAI). Strong programming skills in Python or other relevant languages. Solid understanding of machine learning frameworks (e.g., TensorFlow, PyTorch, Scikit-learn). Experience with large language models (LLMs), NLP, or generative AI applications is a plus. Familiarity with MLOps practices and cloud-based model deployment. Excellent problem-solving and communication skills.

Oracle Cloud Infrastructure (OCI) is at the forefront of cloud innovation, blending the agility of a startup with the reliability of a leading enterprise software provider Our AI Science team pioneers state-of-the-art machine learning solutions that empower customers and solve complex real-world problems at scale. provider. As a Senior Applied Scientist, you will develop and deploy state-of-the-art computer vision solutions leveraging generative AI technologies such as Large multimodal models and computer vision technologies such as image classification, object detection, vision grounding etc. This individual contributor(IC) role will build best-in-class computer vision solutions at scale. Perfect for a hands-on data science architecture design and is eager to drive innovation and excellence in AI and computer vision area. You will partner with the Product and Engineering managers to influence strategic decisions, drive experimentation and communicate results to higher managements. You will build best-in-class LLM/LMM/computer vision solutions for the Oracle business domain at scale. You will also partner with Product Management, Data Labelling and Engineering teams to get to develop build best-in-class computer vision solutions at scale. The ideal candidate has extensive experience with computer vision techniques, deep learning techniques, model serving, and a demonstrated ability to think strategicallyabout business, product, and technical challenges to contribute to the development of current and future vision services Key Responsibilities Development of advanced AI models and algorithms, focusing on large language model, large multimodal, computer vision and foundation models. Design, implement and test the critical module/features of AI service that are correct, highly available, scalable, and cost-effective. Champion best practices for testing, benchmarking, and model validation to ensure reliability and performance. Analysis of ML models, and optimizing models for accuracy and latency. Large-scale training & production deployment with ML models. Own data analysis, feature engineering, technique selection & implementation, debugging, and maintenance of production model. Experience implementing machine learning algorithms or research papers from scratch to production. Work with large, complex data sets. Proactively identify the technical issues/bugs and provide innovative solutions. File patent and publication as by product of solving complex business problems Partner closely with product managers, engineering leads, and annotation/data teams to define requirements, data quality assurance and acceptance of data/annotation as required. Leverage Oracle Cloud technology. Preferred Qualifications Ph.D. (preferred) or Master's in Computer Science, Machine Learning, Computer Vision, or related field. PhD in computer vision or 2+ years of Experience designing, implementing and deploying computer vision models in production environments Expertise in GenAI, LLMs, LMMs, object detection, facial recognition, and image classification. Strong foundation in deep learning architectures such as CNNs, transformers, diffusion models, and multimodal models. Expert in at least one high level language such as Python/Java/C++ Practical experience in ML algorithm design, model training and production deployment using microservices architecture Practical experience working in a cloud environment: Oracle Cloud (OCI), AWS, GCP, Azure or similar technology. Experience or willingness to learn and work in Agile and iterative development processes. Strong drive to learn and master new technologies and techniques. Deep understanding of data structures, algo Career Level - IC3

Job Requirements Education: Bachelors degree (Statistics, Business Analytics, Data Science, Math, Economics, etc.) Masters degree preferred (MBA/MS/M.Tech in Computer Science or related field) Experience: 5–7 years in a Data Science/Advanced Analytics role Behavioral Skills: Delivery Excellence Business Orientation Social Intelligence Innovation and Agility Knowledge & Technical Skills: Functional analytics experience (Supply Chain, Marketing, Customer Analytics, etc.) Statistical modeling using tools such as R, Python, KNIME Knowledge of statistics and experimental design (A/B testing, hypothesis testing, causal inference) Experience building and evaluating machine learning models MLOps tools and practices (MLflow, DVC, Docker, etc.) Strong Python programming (Pandas, Scikit-learn, PyTorch/TensorFlow, etc.) Experience with big data technologies (AWS, Azure, GCP, Hadoop, Spark) Familiarity with relational (MySQL, SQL Server) and non-relational (MongoDB, DynamoDB) databases BI and reporting tools (Power BI, Tableau, Alteryx) Proficiency with Microsoft Office applications (especially Excel) Roles & Responsibilities Analytics & Strategy: Analyze large-scale structured and unstructured data to develop insights and machine learning models across various business domains Apply statistical and machine learning techniques to generate value from operational, financial, and customer data Recommend best-fit algorithms and models with clear justifications for business use Leverage cloud platforms for modeling and big data analysis; utilize data visualization tools to communicate results Operational Excellence: Follow industry-standard coding practices and development lifecycles Formulate hypotheses, develop analytics frameworks, and bring structure to complex problems Collaborate with Data Engineering to maintain core data infrastructure and automate analytical processes Stakeholder Engagement: Work cross-functionally with business stakeholders, engineers, and visualization experts to deliver impactful projects Communicate complex models and results to non-technical stakeholders in a clear and compelling way

Requirements: Must have experience as a Data Scientist or transitioned from Data Engineer Proficient in AWS Expertise in ML Model Design & Development Strong Feature Engineering experience Good to Have: NLP, GraphQL / Graph ML, Generative AI Education: B.Tech / M.Tech in Computer Science, IT, or ECE Location: Delhi NCR,Bangalore,Chennai,Pune,Kolkata,Ahmedabad,Mumbai,Hyderabad