6 Ensemble Models Jobs

You will be part of Maruti Suzuki's Analytics Centre of Excellence (ACE) CoE team as a Data Scientist. Your responsibilities will include designing and implementing workflows of Linear and Logistic Regression, Ensemble Models (Random Forest, Boosting) using R/Python. You should have demonstrable competency in Probability and Statistics, with the ability to use ideas of Data Distributions, Hypothesis Testing, and other Statistical Tests. Experience in handling outliers, denoising data, and managing the impact of pandemic-like situations will be crucial. Additionally, you will be expected to perform Exploratory Data Analysis (EDA) of raw data, conduct feature engineering where applicable, and showcase competency in Data Visualization using the Python/R Data Science Stack. Leveraging cloud platforms for training and deploying large-scale solutions, as well as training and evaluating ML models using various machine learning and deep learning algorithms, will be part of your role. You will also need to retrain and maintain model accuracy in deployment and package & deploy large-scale models on on-premise systems using multiple approaches including docker. Taking complete ownership of the assigned project, working in Agile environments, and being well-versed with project tracking tools like JIRA or equivalent will be expected. Your competencies should include knowledge of cloud platforms (AWS, Azure, and GCP), exposure to NoSQL databases (MongoDB, Cassandra, Cosmos DB, HBase), and forecasting experience in products like SAP, Oracle, Power BI, Qlik, etc. Proficiency in Excel (Power Pivot, Power Query, Macros, Charts), experience with large datasets and distributed computing (Hive/Hadoop/Spark), and transfer learning using state-of-the-art models in different spaces such as vision, NLP, and speech will be beneficial. Integration with external services and Cloud API, as well as working with data annotation approaches and tools for text, images, and videos, will also be part of your responsibilities. The ideal candidate should have a minimum of 2 years and a maximum of 8 years of work experience, along with a Bachelor of Technology (B.Tech) or equivalent educational qualification.,

You should have the ability to design and implement workflows of Linear and Logistic Regression, Ensemble Models (Random Forest, Boosting) using R/Python. Demonstrating competency in Probability and Statistics, you should be capable of utilizing ideas of Data Distributions, Hypothesis Testing, and other Statistical Tests. Your experience should include dealing with outliers, denoising data, and handling the impact of pandemic like situations. Performing Exploratory Data Analysis (EDA) of raw data and feature engineering wherever applicable is crucial. You should possess demonstrable competency in Data Visualization using the Python/R Data Science Stack. Leveraging cloud platforms for training and deploying large-scale solutions is essential. Being able to train and evaluate ML models using various machine learning and deep learning algorithms is a must. You should also be skilled in retraining and maintaining model accuracy in deployment. Knowledge of cloud platforms such as AWS, Azure, and GCP is required. Exposure to NoSQL databases (MongoDB, Cassandra, Cosmos DB, HBase) is preferred. An understanding of forecasting experience in products like SAP, Oracle, Power BI, and Qlik is beneficial. Proficiency in Excel (Power Pivot, Power Query, Macros, Charts) is expected. Having experience with large datasets and distributed computing (Hive/Hadoop/Spark) is advantageous. Knowledge of transfer learning using state-of-the-art models in different spaces like vision, NLP, and speech is a plus. Integration with external services and Cloud API is also a part of the role. Working with data annotation approaches and tools for text, images, and videos is desirable. You should be able to package and deploy large-scale models on on-premise systems using multiple approaches, including Docker. Taking complete ownership of the assigned project is necessary. Experience of working in Agile environments and being well-versed with JIRA or equivalent project tracking tools is expected.,

You should have a Bachelor's Degree in a technical or quantitative field from an accredited college or university. A Master's or PhD in Computer Science, Statistics, Mathematics, Engineering, Bioinformatics, Physics, Operations Research, or related fields is preferred. You must have at least 10 years of relevant experience in Machine Learning and Statistics. A strong mathematical background is required, with the ability to understand algorithms and methods both mathematically and intuitively. Your primary responsibilities will include translating business objectives into analytic approaches, identifying data sources to support analysis, and analyzing structured and unstructured data using advanced statistical methods, deep learning, and Generative AI. You will need to perform exploratory data analyses, generate and test working hypotheses, prepare and analyze historical data, and identify patterns. Proficiency in Python and SQL is essential, along with experience in working with open-source packages and commercial/enterprise applications. You should be comfortable with machine learning and statistical methods such as regression, classification, clustering, ensemble and tree-based models, and time-series analysis. Prior experience or understanding in ML Ops in any cloud platform is required. You should have a strong background in Generative AI, particularly with tools like ChatGPT and CoPilot, and hands-on experience in using APIs to integrate with CoPilot and fabric. Exposure to the Microsoft Tech Stack ecosystem is necessary, along with familiarity with Azure Document Intelligence and Azure Machine Learning for model training and deployment. Additionally, you should be familiar with at least one of the following: Azure AI Language, Azure AI Vision. As part of your role, you will need to communicate results and educate others through reports and presentations. Familiarity with DevOps, code version control, and software development coding best practices is essential. Candidates must hold at least two of the following certifications from Azure: DP-203, MB260, DP-900, AI-102, AI-900.,

We are currently seeking a highly-skilled Data Science Senior Manager with a strong background in data analytics and management. The ideal candidate will have a proven track record of leveraging data-driven insights to drive business improvement and optimize overall business performance. You should have a minimum of 10-14 years of relevant experience in the field of Data Science. As a Data Science Senior Manager, your key responsibilities will include managing and leading a team of data scientists to achieve organizational goals, driving the collection, cleaning, and preprocessing of complex datasets, building predictive models and machine-learning algorithms, proposing solutions and strategies to business challenges, collaborating with engineering and product development teams, overseeing the development and implementation of ML algorithms and models, utilizing predictive modeling to increase and optimize customer experiences, revenue generation, campaign optimization, and other business outcomes, identifying valuable data sources and automating collection processes, undertaking data collection, preprocessing, and analysis, and communicating complex data or algorithms into insights that everyone can understand. You should have proficiency in SQL, Python, Pyspark, experience in data pre-processing, deep knowledge of Supervised ML, EDA, Unsupervised ML, strong understanding of Forecasting Algorithms, Ensemble Models, Causal approaches, excellent understanding of machine learning algorithms, processes, tools, and platforms, proven experience as a Data Science Manager or similar role, strong problem-solving and analytical skills, good communication skills with the ability to explain complex concepts to non-technical stakeholders, and strong leadership and project management skills. Qualifications should include a Bachelor's Degree in Computer Science, Statistics, Applied Math, or a related field with a Master's Degree preferred, and a minimum of 10-14 years of experience in data science or a related field. This is an excellent opportunity for individuals looking to apply their leadership and technical skills in a dynamic and fast-paced environment. We are an equal opportunity employer and value diversity and inclusion at our company. We encourage applications from all backgrounds. If you are passionate about data science and are eager to make a significant impact within a leading organization, apply today. Join us and be a part of our exciting journey.,

As a Healthcare Technology Organization dedicated to simplifying, accelerating, and optimizing care delivery for healthcare enterprises, AVIZVA has been a strategic enabler in the industry since 2011. With a proven track record of over 13 years, we have designed and delivered more than 150 customized products for prominent Medical Health Plans, Dental and Vision Plan Providers, PBMs, Medicare Plan Providers, TPAs, and other healthcare entities. In your role as an Associate Manager - Applied Machine Learning at AVIZVA, you will be at the forefront of architecting, designing, and developing advanced GenAI products and services. Your responsibilities will include leveraging your technical expertise in machine learning to lead a team effectively and contribute to the development of Large Language Model (LLM) based products. By combining GenAI and traditional ML approaches, you will play a crucial role in meeting key product requirements. Collaboration is key in this role, as you will work closely with cross-functional teams, including product managers and business leaders, to deliver scalable machine-learning solutions that align with business objectives. **Job Responsibilities:** - Lead the team by setting clear goals, priorities, and performance expectations that align with business objectives. - Architect and oversee the lifecycle of LLM based GenAI projects, ensuring timely delivery in line with business needs. - Take ownership of technical and operational challenges, providing solutions to keep projects on track. - Collaborate with infrastructure and engineering teams to seamlessly deploy and integrate models into production environments. - Foster a culture of continuous improvement through agile practices and regular retrospectives. - Stay updated on emerging machine learning technologies and prototype new algorithms to tackle complex challenges. - Motivate the team to deliver high-quality results on time while maintaining a collaborative work environment. **Skills & Qualifications:** - Bachelor's or Master's degree in Computer Science or a related analytical field. - Minimum of 1 year of experience in Gen AI, Agentic AI, and Large Language Models. - Hands-on experience in building RAG pipelines and utilizing NLP, NLG, Text Analytics, and Transformer-based models. - 10+ years of experience as an Applied Machine Learning Engineer or Data Scientist, with expertise in Python. - Strong knowledge of system design, architecture, design principles, and Core Python. - Proficiency in ensemble models, classification, clustering algorithms, and Object-Oriented Programming. - Experience with ORM tools, RESTful services, debugging, testing frameworks, and web development. - Familiarity with Agile methodology, excellent communication, and problem-solving skills. Join AVIZVA to be a part of a dynamic team that is dedicated to transforming healthcare delivery through innovative technology solutions.,

AVIZVA is a Healthcare Technology Organization dedicated to simplifying, accelerating, and optimizing the way healthcare enterprises deliver care. Since its establishment in 2011, AVIZVA has been a key strategic enabler for healthcare enterprises, enhancing their overall care delivery through tailored products and services. With over 13 years of expertise, AVIZVA has successfully engineered more than 150 products for leading Medical Health Plans, Dental and Vision Plan Providers, PBMs, Medicare Plan Providers, TPAs, and other healthcare entities. As an Associate Manager - Applied Machine Learning at AVIZVA, you will play a crucial role in architecting, designing, and developing advanced GenAI products and services. This position requires a strong technical background in machine learning coupled with leadership skills to drive the team towards success. Your responsibilities will include contributing to the development of Large Language Model (LLM) based products, integrating GenAI and traditional machine learning approaches to meet key product requirements. Collaboration with cross-functional teams, such as product managers and business leaders, will be essential to deliver scalable machine-learning solutions that align with business needs. Your role will involve setting clear goals and priorities for the team, overseeing the lifecycle of GenAI projects, addressing technical and operational challenges, and ensuring seamless deployment of models into production environments. Embracing a culture of continuous improvement, you will lead the team in delivering high-quality results while maintaining a collaborative work environment. To excel in this role, you should hold a Bachelor's or Master's degree in Computer Science or a related analytical field. A minimum of one year of experience in Gen AI, Agentic AI, and Large Language Models (LLMs) is required, along with hands-on experience in building RAG (Retrieval Augmented Generation) pipelines. Proficiency in NLP, NLG, Text Analytics, and working with Transformer-based models like BERT is essential. Additionally, you should have over 10 years of experience as an Applied Machine Learning Engineer or Data Scientist, with expertise in Python, system design, and architecture. Your technical skills should encompass a strong command of Core Python, advanced Python libraries like PyTorch and FAST API, as well as experience with classification and clustering algorithms, ensemble models, and object-oriented programming. Familiarity with ORM tools, debugging, testing frameworks, front-end fundamentals, and Agile methodology will be beneficial for the role. Excellent communication and problem-solving skills are also key attributes for success in this position.,