10 Classification Techniques Jobs

Role Overview: As a data enthusiast, your role will involve leveraging your collaboration skills to extract valuable insights from complex datasets, enabling you to ask the right questions and provide accurate answers. You will be responsible for analyzing raw data, designing scalable prediction algorithms, collaborating with the engineering team, and generating actionable insights for business improvements. Key Responsibilities: - Analyze raw data by assessing quality, cleansing, and structuring for downstream processing - Design accurate and scalable prediction algorithms - Collaborate with the engineering team to bring analytical prototypes to production - Generate actionable insights for business improvements Qualifications: - Bachelor's degree or equivalent experience in a quantitative field (Statistics, Mathematics, Computer Science, Engineering, etc.) - 3.5 - 10 years of experience in quantitative analytics or data modeling - Deep understanding of predictive modeling, machine-learning, clustering and classification techniques, and algorithms - Fluency in a programming language (Python, C, C++, Java, SQL) - Familiarity with Big Data frameworks and visualization tools (Cassandra, Hadoop, Spark, Tableau),

At Dark Matter Technologies, you are part of a cutting-edge revolution in loan origination. The company's commitment to advanced AI and origination technology solutions is reshaping the industry landscape, paving the way for seamless, efficient, and automated experiences. As a Senior Data Scientist at Dark Matter Technologies, you will play a pivotal role in applying data science and machine learning techniques to tackle complex business challenges and foster innovation. With a minimum of 10 years of experience in the field, your expertise will be pivotal in designing, developing, and implementing sophisticated models for regression, predictions, ranking, and trend analysis. Your responsibilities will include selecting features, building, and optimizing classifiers using machine learning techniques, conducting hypothesis testing, and developing predictive models. Collaborating with cross-functional teams, including data engineers, front-end developers, and security specialists, you will integrate AI models into business solutions. Additionally, you will conduct research and experiments to enhance AI models and algorithms, staying updated on the latest AI/ML technologies and trends. To excel in this role, you must possess at least 10 years of experience in Predictive Analytics and Data Mining, with hands-on expertise in areas such as Linear Regression, Classification Techniques, Logistic Regression, and Unsupervised Learning techniques like k-means/hierarchical clustering. Proficiency in Optimization methods, working in R/Python, T-SQL, and graph-based models is essential. Hands-on experience with Python, Azure Machine Learning, and other Azure AI tools is highly desirable. Your role will involve developing and deploying machine learning models for various use cases, optimizing models through advanced feature engineering, working with large-scale datasets, and collaborating with stakeholders to design data science solutions that address organizational needs. Strong problem-solving skills, solid understanding of statistical analysis and machine learning algorithms, and excellent communication skills are key attributes for success in this position. Preferred skills include exposure to machine learning libraries like Scikit-learn, TensorFlow, or PyTorch, leveraging Azure Machine Learning for data pipelines, experiments, and deployments, and implementing end-to-end AI solutions using Azure AI services. Certification in Microsoft Azure AI relative to Azure Machine Learning, expert database knowledge in SQL, and proficiency in Azure Data Services are advantageous. Join Dark Matter Technologies to be at the forefront of data science innovation and contribute to reshaping the future of loan origination through advanced AI technologies and solutions.,

The ideal candidate's favorite words are learning, data, scale, and agility. You will leverage your strong collaboration skills and ability to extract valuable insights from highly complex data sets to ask the right questions and find the right answers. Responsibilities - Analyze raw data: assessing quality, cleansing, structuring for downstream processing - Design accurate and scalable prediction algorithms - Collaborate with engineering team to bring analytical prototypes to production - Generate actionable insights for business improvements Qualifications - Bachelor's degree or equivalent experience in a quantitative field (Statistics, Mathematics, Computer Science, Engineering, etc.) - At least 1 - 2 years" of experience in quantitative analytics or data modeling - Deep understanding of predictive modeling, machine-learning, clustering and classification techniques, and algorithms - Fluency in a programming language (Python, C, C++, Java, SQL) - Familiarity with Big Data frameworks and visualization tools (Cassandra, Hadoop, Spark, Tableau),

You will be joining Dark Matter Technologies, a company leading the tech-driven revolution in loan origination with cutting-edge AI and origination technology solutions. As a Senior Data Scientist, your role will involve building machine learning models, using various algorithms for regression, prediction, and deep learning. You will be responsible for identifying data sources, analyzing data, writing machine code in Python (or Azure ML), and creating models. The job location is in Hyderabad and Bhubaneswar. Your responsibilities will include selecting features, building, and optimizing classifiers using machine learning techniques, conducting hypothesis testing, and developing predictive models. You will collaborate with cross-functional teams to integrate AI models into business solutions, conduct research to improve AI models and algorithms, and stay updated with the latest AI/ML technologies and trends. Additionally, you will implement and deploy AI models using cloud AI services while ensuring the quality and scalability of AI solutions. To qualify for this role, you should have at least 10 years of experience in Predictive Analytics and Data Mining, with hands-on experience in various areas such as linear regression, classification techniques, logistic regression, unsupervised learning techniques, feature reduction methods, and optimization methods. You must be proficient in working with R/Python, T-SQL, and graph-based models, with hands-on development experience in Python. Understanding of Azure Machine Learning and other Azure AI tools is essential, along with proficiency in data modeling, design, SQL development, and deploying machine learning models for key use cases. Preferred skills include exposure to machine learning libraries like Scikit-learn, TensorFlow, or PyTorch, leveraging Azure Machine Learning for managing data pipelines, experiments, and deployments, and implementing end-to-end AI solutions using Azure AI services. Certification in Microsoft Azure AI relative to Azure Machine Learning, expert database knowledge in SQL, and proficiency in Azure Data Services are also advantageous. You should possess strong problem-solving skills, the ability to work independently and as part of a team, excellent communication skills to convey complex technical concepts to non-technical stakeholders, and a solid understanding of statistical analysis and machine learning algorithms. Your role will involve working with large-scale datasets, ensuring efficiency and scalability in data processing, collaborating with stakeholders to design data science solutions, and presenting analytical findings and business insights to project managers and senior leadership. Keeping abreast of new statistical and machine learning techniques is crucial to improve predictive performance.,

India is among the top ten priority markets for General Mills, and hosts our Global Shared Services Centre. This is the Global Shared Services arm of General Mills Inc., which supports its operations worldwide. With over 1,300 employees in Mumbai, the center has capabilities in the areas of Supply Chain, Finance, HR, Digital and Technology, Sales Capabilities, Consumer Insights, ITQ (R&D & Quality), and Enterprise Business Services. Learning and capacity-building is a key ingredient of our success. Data Scientist I - Decision Sciences About General Mills We make foodthe world loves: 100 brands. In 100 countries. Across six continents. With iconic brands like Cheerios, Pillsbury, Betty Crocker, Nature Valley, and Hagen-Dazs, we've been serving up food the world loves for 155 years (and counting). Each of our brands has a unique story to tell. How we make our food is as important as the food we make. Our values are baked into our legacy and continue to accelerate us into the future as an innovative force for good. General Mills was founded in 1866 when Cadwallader Washburn boldly bought the largest flour mill west of the Mississippi. That pioneering spirit lives on today through our leadership team who upholds a vision of relentless innovation while being a force for good.For more details check out General Mills India Center is our global capability center in Mumbai that works as an extension of our global organization delivering business value, service excellence and growth, while standing for good for our planet and people. With our team of 1800+ professionals, we deliver superior value across the areas of supply chain, digital & technology, innovation, technology & quality, consumer & market intelligence, sales strategy & intelligence, global shared services, finance shared services and Human Resources Shared Services. For more details check out Job Overview This position is part of the Decision Sciences team for CPW within CMI Mumbai. This is a global team of 90 members supporting business and enabling strategies through data-driven solutions. CPW Team is based out of Switzerland (HQ), UK and Mumbai India location. We are looking for a junior data scientist . who is passionate about the possibilities of leveraging data for informed decision-making and has demonstrated and implemented a few of those. . who not only understands the model but also the data and math behind it. Key Accountabilities 1. Develop innovative approaches to assist business partners in achieving objectives through analysis and modelling. 2. Think creatively to identify and test new sources of information that unlock additional business value. 3. Effectively communicate the why and how of data-driven recommendations to cross-functional teams, employing storytelling techniques. 4. Engineer features by leveraging business acumen to categorize, aggregate, pivot, or encode data for optimal results. 5. Utilize machine learning to develop repeatable, dynamic, and scalable models. 6. Passionately advocate for and educate others on the value and significance of data-driven decision-making and analytical methods. 7. Identify and develop long-term data science processes, frameworks, tools, and standards. 8. Collaborate as a member of the team, actively engaging with and seeking feedback from other Data Scientists. 9. Be able to explore and troubleshoot niche technologies and provide automation solutions . Minimum Qualifications 1. Should have a working knowledge of traditional ML and statistical models. 2. Ability to program in R and/or Python and SQL. 3. 3 years of related experience with a bachelor's degree or 2 years with a master's degree. 4. Experience using clustering, regression, and classification Techniques. Preferred Qualifications/ Skills/ Job Experiences Able to execute against a developed analytics plan. Actively manages stakeholder expectations. Understanding/experience in the CPG industry is desirable. Experience in basic statistical analysis, modelling, clustering, and data mining techniques to identify trends and insights. Experience with Market Mix Modeling or Campaign Effectiveness Analysis will be an added advantage. Strong number sense and ability to identify questionable data, investigate it, and address any issues. Exemplary organizational skills with attention to detail and accuracy. Familiarity with data visualization tools like Power BI. Navigate across the team to get the support needed to execute. Effective communication and a team player.

Job Description: Key Responsibilities: Develop, implement, and maintain advanced analytical models using machine learning algorithms and GenAI applications Utilize various advanced analytics techniques to uncover trends, patterns, and insights from large and complex datasets. Collaborate with cross-functional teams to identify business needs and deliver data-driven solutions. Create visually compelling dashboards and reports to present findings to stakeholders. Continuously evaluate and improve existing analytics methodologies and models to enhance accuracy and performance. Stay abreast of industry trends and advancements in analytics and machine learning to drive innovation within the team. Mentor junior team members and contribute to knowledge sharing within the organization. Basic Qualifications: Bachelors or Masters degree in Data Science, Business Analytics, Mathematics, Statistics, or a related field. 8+ years of experience in advanced analytics, data science, machine learning, Generative AI or a related field. Strong experience with quantitative modeling, predictive analytics, text analytics, and forecasting methodologies Proficiency in SQL (or Google BigQuery), Python, visualization tools like Tableau/PowerBI Familiarity with the Retail/CPG/Tech industry and experience with product, transaction, and customer-level data. Excellent communication skills, both verbal and written, with the ability to convey complex concepts to non-technical stakeholders. Strong analytical and problem-solving skills, with an inquisitive mindset. Desired Skills: Proficient in the following advanced analytics techniques: Descriptive Analytics: Statistical analysis, data visualization. Predictive Analytics: Regression analysis, time series forecasting, classification techniques, market mix modeling Prescriptive Analytics: Optimization, simulation modeling. Text Analytics: Natural Language Processing (NLP), sentiment analysis. Extensive knowledge of machine learning techniques, including: Supervised Learning: Linear regression, logistic regression, decision trees, support vector machines, random forests, gradient boosting machines among others Unsupervised Learning: K-means clustering, hierarchical clustering, principal component analysis (PCA), anomaly detection among others Reinforcement Learning: Q-learning, deep Q-networks, etc. Experience with Generative AI and large language models (LLMs) for text generation, summarization, and conversational agents. Researching, loading and application of the best LLMs (GPT, Gemini, LLAMA, etc.) for various objectives Hyper parameter tuning Prompt Engineering Embedding & Vectorization Fine tuning Proficiency in data visualization tools such as Tableau or Power BI. Strong skills in data management, structuring, and harmonization to support analytical needs. #DentsuGlobalServices Location: DGS India - Bengaluru - Manyata N1 Block Brand: Merkle Time Type: Full time Contract Type: Permanent Show more Show less

Navi is a rapidly growing financial services company in India that offers a range of products including Personal & Home Loans, UPI, Insurance, Mutual Funds, and Gold. The mission of Navi is to provide digital-first financial solutions that are easy to use, accessible, and affordable. Leveraging our in-house AI/ML capabilities, technology, and product expertise, Navi is dedicated to creating exceptional customer experiences. As a Navi_ite, you should embody the following qualities: - Perseverance, Passion, and Commitment: Demonstrate dedication, passion for Navi's mission, and ownership by going above and beyond in your responsibilities. - Obsession with high-quality results: Consistently deliver value to customers and stakeholders by producing high-quality outcomes, ensuring excellence in all work aspects, and achieving high standards through efficient time management. - Resilience and Adaptability: Quickly adapt to new roles, responsibilities, and changing circumstances while demonstrating resilience and agility. The role involves: - Monitoring delinquent accounts to meet Company standards - Evaluating underwriting model stability and recommending policy actions to increase approval rates or reduce risk - Developing and maintaining loss forecasting models and ECL provisioning for accounting purposes - Implementing a portfolio monitoring and early warning alert system for loan book health - Utilizing data for decision-making, ensuring data accuracy, defining metrics for process improvement, and identifying areas for product and process enhancement through customer segmentation and analysis - Working with the engineering and data platform team to ensure data availability and reliability Desired Candidate Profile: - Experience in managing multiple stakeholders - Startup mindset - Team building skills - Proficiency in SQL, any BI platform (Tableau, PowerBI, Qlikview, Looker, Quicksight, etc.) - Understanding of basic statistical concepts and data platforms - Ability to identify relevant data for solving business problems and validating hypotheses - Prior experience in data modeling in R/Python and classification/regression techniques (Good to have) - Prior experience/understanding of lending/insurance/banking domain (Good to have),

The ideal candidate's favourite words are learning, data, scale, and agility. You will leverage your strong collaboration skills and ability to extract valuable insights from highly complex data sets to ask the right questions and find the correct answers. Responsibilities Analyze raw data: assessing quality, cleansing, and structuring for downstream processing. Design accurate and scalable prediction algorithms. Molecular Docking and Simulation. Integrating Biological Data. Computational Biology related works. Qualifications Bachelor's degree or equivalent experience in a quantitative field (Bio-informatics, Biotechnology, Statistics, Computer Science, Engineering, etc.) At least 1 - 2 years of experience in quantitative analytics or data modelling Freshers can also apply.* Deep understanding of predictive modelling, machine learning, clustering and classification techniques, and algorithms Fluency in a programming language (Python, R, C, C++, Java, SQL),

At Allstate, great things happen when our people work together to protect families and their belongings from life's uncertainties. For over 90 years, our innovative drive has kept us a step ahead of our customers" evolving needs. From advocating for safety measures like seat belts and airbags to being a leader in pricing sophistication, telematics, and device and identity protection. This role is responsible for leading the use of data to make decisions. You will develop and execute new machine learning predictive modeling algorithms, code tools using machine learning/predictive modeling for business decisions, integrate new data to improve modeling results, and find solutions to business problems through machine learning/predictive modeling. In addition, you will manage projects of small to medium complexity. We are seeking a Data Scientist to apply machine learning and advanced analytics to solve complex business problems. The ideal candidate will possess technical expertise, business acumen, and a passion for solving high-impact problems. Your responsibilities will include developing machine learning models, integrating new data sources, and delivering solutions that enhance decision-making. You will collaborate with cross-functional teams to translate insights into action, from design to deployment. Key Responsibilities: - Design, build, and validate statistical and machine learning models for key business problems. - Perform data exploration and analysis to uncover insights and improve model performance. - Communicate findings to stakeholders, collaborate with teams to ensure solutions are adopted. - Stay updated on modeling techniques, tools, and technologies, integrating innovative approaches. - Lead data science initiatives from planning to delivery, ensuring measurable business impact. - Provide mentorship to junior team members and lead technical teams as required. Must-Have Skills: - 4 to 8 years of experience in applied data science, delivering business value through machine learning. - Proficiency in Python with experience in libraries like scikit-learn, pandas, NumPy, and TensorFlow or PyTorch. - Strong foundation in statistical analysis, regression modeling, classification techniques, and more. - Hands-on experience with building and deploying machine learning models in cloud environments. - Ability to translate complex business problems into structured data science problems. - Strong communication, stakeholder management, analytical, and problem-solving skills. - Proactive in identifying opportunities for data-driven decision-making. - Experience in Agile or Scrum-based project environments. Preferred Skills: - Experience with Large Language Models (LLMs) and transformer architectures. - Experience with production-grade ML platforms and orchestration tools for scaling models. Primary Skills: Business Case Analyses, Data Analytics, Predictive Analytics, Predictive Modeling, Waterfall Project Management. Shift Time: Shift B (India). Recruiter Info: Annapurna Jha, email: ajhat@allstate.com. About Allstate: The Allstate Corporation is a leading insurance provider in the US, with operations in multiple countries, including India. Allstate India is a strategic business services arm focusing on technology, innovation, and operational excellence. Learn more about Allstate India here.,

As a DevOps Engineer for AI products at Linde, you will play a crucial role in the Artificial Intelligence team within Linde's global corporate division. You will collaborate with a diverse international team consisting of Project Managers, Data Scientists, Data and Software Engineers, and other professionals. Your responsibilities will include designing, implementing, and managing robust CI/CD pipelines to support the deployment of AI and data-driven applications globally. You will be tasked with administering and monitoring cloud-based infrastructure to ensure high availability, security, and cost-efficiency of AI product deployments. Additionally, your role will involve developing and maintaining containerized environments using Docker, orchestrating deployment strategies, and establishing infrastructure monitoring and logging solutions for AI platforms in production. It is essential that all DevOps practices adhere to Linde's security guidelines and industry best practices. To succeed in this role, you should have a Bachelor's degree or equivalent experience in a related field such as Statistics, Mathematics, Computer Science, or Engineering. You must possess a good understanding of modern web applications, cloud platforms (Azure, AWS, GCP), Docker, CI/CD pipelines, and database deployments. Experience with automation tools like Azure DevOps and Github Actions is required, along with strong communication skills in English. Linde is a renowned global industrial gases and engineering company operating in over 100 countries. By joining Linde, you will have the opportunity to work on cutting-edge projects that make the world more productive while contributing to sustainability and environmental protection. If you are looking for a career where your work transcends boundaries and positively impacts the world, Linde offers limitless opportunities for growth and development. If you are inspired to be part of a dynamic team that values innovation and excellence, we encourage you to submit your complete application (motivation letter, CV, certificates) through our online job market. At Linde, we are committed to fostering a diverse and inclusive workplace where individuals of all genders can thrive and succeed. Join us at Linde and unleash your potential to make a meaningful difference in the world.,