55 Classification Jobs - Page 3

Data Scientist: 4 -7 years of Relevant Data Science Experience, with demonstrated proficiency and hands-on experience navigating data science complexities. Good communication skills, both verbal and written. Exhibit a fervour for crafting modular, scalable, and bug-free Python code. Comfortable in SQL with additional proficiency in office tools like Excel & PowerPoint. Experience in production engineering best practices (e.g. Git versioning, Docker). Excitement to collaborate with diverse stakeholders across the organisation. In-depth understanding of various data science approaches, machine learning algorithms, and statistical methods. Hunger to learn new technologies and embrace the change. Proficiency in foundational concepts and algorithms in machine learning, encompassing regression and classification techniques, and a keen awareness of their assumptions, strengths, and limitations. Must-Have Skills: Regression/Classification/Optimization/ Python Proficiency in these key skills is crucial to thriving in this role.

Design, develop, and implement ABBYY Flexicapture workflows to automate document capture, classification, data extraction, and validation processes. Exp with the configuration and administration of Flexicapture machines, including processing servers.

Requirement : Bachelor's Degree in Computer Science, Operations Research, Statistics, or related field. Knowledge of R, or Python Knowledge of building regression and classification models Familiarity with any or all of, Regularization methods: Lasso, Ridge Ensemble methods: Random Forest, Boosting Time Series analysis: Auto-regression, moving average, etc. Graphs modeling Support Vector Machines Decision trees Key Skills : Have a Data Science acumen Able to explore the data and understand the problem Be able to implement a solution Test your implementation Document your work Clean codes that can be reused Aware of general developments in the Data Science area Preferred : Master's or higher degrees. Industry experience in the field of Data Science. Participation in competitions like Kaggle, Netflix Data Challenge. Open source contributions in areas of Data Science (Machine Learning, Deep Learning, Statistical Learning). Worked on Scala and/or Spark. Understanding of generative AI concepts, such as transformers, diffusion models, and LLMs Work on a Mac system.

School : WITTY Campus : Witty International School, Borivali Country : India Qualification : Bachelor in Library Science OverView : Witty International School Responsibility : A School Library Assistant is responsible for the day-to-day operations of a school library, assisting students and staff with finding materials, checking books in and out, maintaining the library collection, and supporting a positive learning environment by promoting reading and research skills, all under the guidance of a librarian. SkillsDescription : A School Library Assistant is responsible for the day-to-day operations of a school library, assisting students and staff with finding materials, checking books in and out, maintaining the library collection, and supporting a positive learning environment by promoting reading and research skills, all under the guidance of a librarian. Disclaimer : Our company is an equal opportunity employer committed to creating a diverse and inclusive workplace. We encourage applications from individuals of all backgrounds and experiences.

Dear candidate, We found your profile suitable for our current opening, please go through the below JD for better understanding of the role, Job Description : Role : Senior Lead Datasceintist Exp : 18 - 25years Mode of work : Hybrid Model Work Location : Hyderabad/Bangalore/Noida/Pune/Kolkata Role Overview: We are looking for an experienced Senior Lead Data Scientist / ML Engineer with a strong blend of pre-sales expertise, team leadership , and technical proficiency across classical machine learning, deep learning, and generative AI . You will engage in high-level client discussions, drive technical sales strategies, and lead a team to design and implement cutting-edge ML solutions. This is a strategic role requiring both thought leadership and hands-on technical contributions. Roles & Responsibilities Key Responsibilities Pre-Sales & Client Engagement Collaborate with the sales and business development teams to identify client needs and formulate AI/ML solutions. Present technical concepts, project proposals, and proof-of-concepts (POCs) to prospects and clients. Translate complex client requirements into actionable project scopes, estimates,and technical proposals. Leadership & Team Management Provide direction, mentorship, and performance feedback to a team of data scientists and ML engineers. Establish best practices in solution design, code reviews, model validation, and production deployment. Drive the strategic roadmap for AI initiatives, ensuring alignment with organizational goals and market trends. Classical Machine Learning & Statistical Modeling Apply classical machine learning techniques (e.g., regression, clustering, decision trees, ensemble methods) to solve diverse business problems. Design and optimize data pipelines, feature engineering processes, and model selection strategies. Ensure robust model evaluation, tuning, and performance monitoring in production environments. Deep Learning & Generative AI Develop and maintain deep learning models using frameworks such as TensorFlow or PyTorch for tasks like computer vision, NLP, or recommendation systems. Explore and build solutions leveraging generative AI (GANs, VAEs, or transformer-based architectures) for innovative product features and services. Champion research and experimentation with state-of-the-art AI models, staying ahead of industry advances. Project Delivery & MLOps Lead end-to-end ML project lifecycles, from data exploration and model development to deployment and post-launch maintenance. Implement MLOps best practices (CI/CD, containerization, model versioning) on cloud or on-premise infrastructures. Collaborate with DevOps and engineering teams to integrate ML solutions seamlessly into existing systems. Stakeholder Management & Communication Serve as a key technical advisor to executive leadership, product managers, and client teams. Communicate complex AI/ML findings in clear, actionable terms to both technical and non-technical audiences. Advocate data-driven decision-making and foster a culture of innovation within the organization. Required Qualifications Education & Experience Masters or PhD in Computer Science, Data Science, Engineering, or a related field is preferred. 12+ years of relevant industry experience in data science or ML engineering, with 5+ years in a leadership or management capacity. Technical Expertise Pre-Sales : Demonstrated experience in client-facing roles, solutioning, and proposal development. Classical ML : Skilled in traditional algorithms (regression, classification,clustering, etc.) and statistical methods. Deep Learning : Hands-on expertise with frameworks (e.g., TensorFlow,PyTorch) for CNNs, RNNs, transformer architectures, etc. Generative AI : Practical exposure to GANs, VAEs, or large language models, with a track record of building generative models. MLOps : Familiarity with CI/CD pipelines, Docker/Kubernetes, and cloud platforms (AWS, Azure, GCP). Leadership & Communication Proven ability to mentor and lead data science/ML engineering teams to meet project goals. Exceptional communication skills for presenting to clients, stakeholders, and executive leadership. Experience in agile methodologies and project management, balancing multiple projects simultaneously. Please check below link for organisation details, https://www.tavant.com/ If interested , please drop your resume to dasari.gowri@tavant.com Regards Dasari Krishna Gowri Associate Manager - HR www.tavant.com