172 Decision Tree Jobs - Page 5

Associate Process Manager Role and responsibilities: Understand business problem and requirements by building domain knowledge and translate to data science problem. Conceptualize and design cutting edge data science solution to solve the data science problem, apply design-thinking concepts. Identify the right algorithms, tech stack, sample outputs required to efficiently adder the end need. Prototype and experiment the solution to successfully demonstrate the value. Independently or with support from team, execute the conceptualized solution as per plan by following project management guidelines. Present the results to internal and client stakeholder in an easy to understand manner with great story telling, story boarding, insights and visualization. Help build overall data science capability for eClerx through support in pilots, pre sales pitches, product development, and practice development initiatives. Technical and Functional Skills: Bachelors degree in Computer Science with 4 to 6 years of work experience. Must have experience in Advance Analytics, Data Science, regression, forecasting, analytics, SQL, R, Python, decision tree, random forest, SAS, clustering classification. Ability to engage clients to understand business requirements and convert the same into technical/modelling problems for solution development. Demonstrate strong interpersonal skills and a comfort interacting with clients from the C-suite to marketing managers to technical specialists. Demonstrated knowledge of analytical/statistical techniques and their applications; a working knowledge of/experience in R and Python is a plus. Demonstrated excellent communications skills, both written and spoken, as well as being able to explain complex technical concepts in plain English. Ability to present results of statistical models in business language. Domain understanding of at least one preferably two verticals amongst Retail, Cable, Technology (not mandate). Knowledge of data visualization tools (Tableau, QlikView, etc.) is a plus. Demonstrate strong analytical and storytelling skills and the ability to find relevant stories from piles of reports. Ability to manage specific tasks to completion with minimal direction. Ideal candidate has been in a consulting role previously. Hands-on expertise on the applied statistical techniques including multi-variate regression, logistic regression, market-mix models, clustering, classification, survival, churn models, speech analytics, image analytics, etc. Ability to collaborate with onsite colleagues in the US & UK. Expert in handling large data, cleansing & preparation for modelling. Very high attention to detail and quality.

Associate Process Manager Role and responsibilities: Understand business problem and requirements by building domain knowledge and translate to data science problem. Conceptualize and design cutting edge data science solution to solve the data science problem, apply design-thinking concepts. Identify the right algorithms, tech stack, sample outputs required to efficiently adder the end need. Prototype and experiment the solution to successfully demonstrate the value. Independently or with support from team, execute the conceptualized solution as per plan by following project management guidelines. Present the results to internal and client stakeholder in an easy to understand manner with great story telling, story boarding, insights and visualization. Help build overall data science capability for eClerx through support in pilots, pre sales pitches, product development, and practice development initiatives. Technical and Functional Skills: Bachelors degree in Computer Science with 4 to 6 years of work experience. Must have experience in Advance Analytics, Data Science, regression, forecasting, analytics, SQL, R, Python, decision tree, random forest, SAS, clustering classification. Ability to engage clients to understand business requirements and convert the same into technical/modelling problems for solution development. Demonstrate strong interpersonal skills and a comfort interacting with clients from the C-suite to marketing managers to technical specialists. Demonstrated knowledge of analytical/statistical techniques and their applications; a working knowledge of/experience in R and Python is a plus. Demonstrated excellent communications skills, both written and spoken, as well as being able to explain complex technical concepts in plain English. Ability to present results of statistical models in business language. Domain understanding of at least one preferably two verticals amongst Retail, Cable, Technology (not mandate). Knowledge of data visualization tools (Tableau, QlikView, etc.) is a plus. Demonstrate strong analytical and storytelling skills and the ability to find relevant stories from piles of reports. Ability to manage specific tasks to completion with minimal direction. Ideal candidate has been in a consulting role previously. Hands-on expertise on the applied statistical techniques including multi-variate regression, logistic regression, market-mix models, clustering, classification, survival, churn models, speech analytics, image analytics, etc. Ability to collaborate with onsite colleagues in the US & UK. Expert in handling large data, cleansing & preparation for modelling. Very high attention to detail and quality.

Associate Process Manager Role and responsibilities: Understand business problem and requirements by building domain knowledge and translate to data science problem. Conceptualize and design cutting edge data science solution to solve the data science problem, apply design-thinking concepts. Identify the right algorithms, tech stack, sample outputs required to efficiently adder the end need. Prototype and experiment the solution to successfully demonstrate the value. Independently or with support from team, execute the conceptualized solution as per plan by following project management guidelines. Present the results to internal and client stakeholder in an easy to understand manner with great story telling, story boarding, insights and visualization. Help build overall data science capability for eClerx through support in pilots, pre sales pitches, product development, and practice development initiatives. Technical and Functional Skills: Bachelors degree in Computer Science with 4 to 6 years of work experience. Must have experience in Advance Analytics, Data Science, regression, forecasting, analytics, SQL, R, Python, decision tree, random forest, SAS, clustering classification. Ability to engage clients to understand business requirements and convert the same into technical/modelling problems for solution development. Demonstrate strong interpersonal skills and a comfort interacting with clients from the C-suite to marketing managers to technical specialists. Demonstrated knowledge of analytical/statistical techniques and their applications; a working knowledge of/experience in R and Python is a plus. Demonstrated excellent communications skills, both written and spoken, as well as being able to explain complex technical concepts in plain English. Ability to present results of statistical models in business language. Domain understanding of at least one preferably two verticals amongst Retail, Cable, Technology (not mandate). Knowledge of data visualization tools (Tableau, QlikView, etc.) is a plus. Demonstrate strong analytical and storytelling skills and the ability to find relevant stories from piles of reports. Ability to manage specific tasks to completion with minimal direction. Ideal candidate has been in a consulting role previously. Hands-on expertise on the applied statistical techniques including multi-variate regression, logistic regression, market-mix models, clustering, classification, survival, churn models, speech analytics, image analytics, etc. Ability to collaborate with onsite colleagues in the US & UK. Expert in handling large data, cleansing & preparation for modelling. Very high attention to detail and quality.

Associate Process Manager Role and responsibilities: Understand business problem and requirements by building domain knowledge and translate to data science problem. Conceptualize and design cutting edge data science solution to solve the data science problem, apply design-thinking concepts. Identify the right algorithms, tech stack, sample outputs required to efficiently adder the end need. Prototype and experiment the solution to successfully demonstrate the value. Independently or with support from team, execute the conceptualized solution as per plan by following project management guidelines. Present the results to internal and client stakeholder in an easy to understand manner with great story telling, story boarding, insights and visualization. Help build overall data science capability for eClerx through support in pilots, pre sales pitches, product development, and practice development initiatives. Technical and Functional Skills: Bachelors degree in Computer Science with 4 to 6 years of work experience. Must have experience in Advance Analytics, Data Science, regression, forecasting, analytics, SQL, R, Python, decision tree, random forest, SAS, clustering classification. Ability to engage clients to understand business requirements and convert the same into technical/modelling problems for solution development. Demonstrate strong interpersonal skills and a comfort interacting with clients from the C-suite to marketing managers to technical specialists. Demonstrated knowledge of analytical/statistical techniques and their applications; a working knowledge of/experience in R and Python is a plus. Demonstrated excellent communications skills, both written and spoken, as well as being able to explain complex technical concepts in plain English. Ability to present results of statistical models in business language. Domain understanding of at least one preferably two verticals amongst Retail, Cable, Technology (not mandate). Knowledge of data visualization tools (Tableau, QlikView, etc.) is a plus. Demonstrate strong analytical and storytelling skills and the ability to find relevant stories from piles of reports. Ability to manage specific tasks to completion with minimal direction. Ideal candidate has been in a consulting role previously. Hands-on expertise on the applied statistical techniques including multi-variate regression, logistic regression, market-mix models, clustering, classification, survival, churn models, speech analytics, image analytics, etc. Ability to collaborate with onsite colleagues in the US & UK. Expert in handling large data, cleansing & preparation for modelling. Very high attention to detail and quality.

The ideal candidate must possess in-depth functional knowledge of the process area and apply it to operational scenarios to provide effective solutions. The role enables to identify discrepancies and propose optimal solutions by using a logical, systematic, and sequential methodology. It is vital to be open-minded towards inputs and views from team members and to effectively lead, control, and motivate groups towards company objects. Additionally, candidate must be self-directed, proactive, and seize every opportunity to meet internal and external customer needs and achieve customer satisfaction by effectively auditing processes, implementing best practices and process improvements, and utilizing the frameworks and tools available. Goals and thoughts must be clearly and concisely articulated and conveyed, verbally and in writing, to clients, colleagues, subordinates, and supervisors. Associate Process Manager Role and responsibilities: Understand business problem and requirements by building domain knowledge and translate to data science problem. Conceptualize and design cutting edge data science solution to solve the data science problem, apply design-thinking concepts. Identify the right algorithms, tech stack, sample outputs required to efficiently adder the end need. Prototype and experiment the solution to successfully demonstrate the value. Independently or with support from team, execute the conceptualized solution as per plan by following project management guidelines. Present the results to internal and client stakeholder in an easy to understand manner with great story telling, story boarding, insights and visualization. Help build overall data science capability for eClerx through support in pilots, pre sales pitches, product development, and practice development initiatives. Technical and Functional Skills: Bachelors degree in Computer Science with 4 to 6 years of work experience. Must have experience in Advance Analytics, Data Science, regression, forecasting, analytics, SQL, R, Python, decision tree, random forest, SAS, clustering classification. Ability to engage clients to understand business requirements and convert the same into technical/modelling problems for solution development. Demonstrate strong interpersonal skills and a comfort interacting with clients from the C-suite to marketing managers to technical specialists. Demonstrated knowledge of analytical/statistical techniques and their applications; a working knowledge of/experience in R and Python is a plus. Demonstrated excellent communications skills, both written and spoken, as well as being able to explain complex technical concepts in plain English. Ability to present results of statistical models in business language. Domain understanding of at least one preferably two verticals amongst Retail, Cable, Technology (not mandate). Knowledge of data visualization tools (Tableau, QlikView, etc.) is a plus. Demonstrate strong analytical and storytelling skills and the ability to find relevant stories from piles of reports. Ability to manage specific tasks to completion with minimal direction. Ideal candidate has been in a consulting role previously. Hands-on expertise on the applied statistical techniques including multi-variate regression, logistic regression, market-mix models, clustering, classification, survival, churn models, speech analytics, image analytics, etc. Ability to collaborate with onsite colleagues in the US & UK. Expert in handling large data, cleansing & preparation for modelling. Very high attention to detail and quality.

At EY, you will have the opportunity to shape a career that reflects your uniqueness, supported by a global network, inclusive environment, and cutting-edge technology to help you reach your full potential. Your individual voice and perspective are vital in contributing to EY's continuous improvement. By joining us, you will not only create an exceptional journey for yourself but also play a part in building a better working world for everyone. EY GDS's Tax Innovation, Solutions, and Technology (IST) group, along with the Tax Tech Transformation (TTT) team, is dedicated to developing, implementing, and integrating innovative technology solutions that cater better to our clients and engagement teams. As a member of EY's core Tax practice, you will gain in-depth tax technical knowledge and excel in database management, data analytics, and programming skills. The ever-evolving regulatory landscape demands tax departments to handle a vast amount of data more efficiently. Gathering, organizing, and analyzing data to meet complex regulations often involves data from various systems and departments within an organization. Managing this diverse and extensive data can be a significant challenge for companies. As part of EY's GDS IST and TTT teams, you will collaborate closely with partners, clients, and tax experts to develop and integrate technology solutions that enhance value, streamline processes, and equip clients with cutting-edge tools to support their tax needs. Your role will involve applying machine learning techniques to derive actionable insights, coding in Python and R, managing the end-to-end model development process, and designing systems to process large datasets for machine learning applications. You will also work on statistical methods, simulation models, and engage with stakeholders to understand business requirements and present solutions effectively. To excel in this position, you should have at least 2 years of overall experience, with hands-on expertise in Machine Learning and Artificial Intelligence tools like neural networks, deep learning, and regression. Proficiency in programming languages such as R and Python, along with experience in end-to-end ML projects, is essential. A Master's degree in Statistics/Mathematics or a Bachelor's/Master's degree in Science/Engineering/MCA is required for this role. Additionally, exposure to cloud platforms like Azure or AWS and strong communication skills are desirable qualities. EY offers a dynamic and global work environment where you can collaborate with diverse teams on exciting projects, develop new skills, and contribute to building a better working world. Join us at EY and be part of a forward-thinking team that values commercial acumen, technical expertise, and a passion for continuous learning in a fast-paced setting. You will have the opportunity to work with leading businesses across various industries and contribute to EY's mission of creating a better working world through trust, innovation, and inclusive practices.,

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.,

As a member of the R&A COE team at EY, you will be part of a dynamic group working on various Data Science and Machine Learning projects. Your role will involve utilizing your experience in data science projects and demonstrating advanced programming skills in SAS, R, or Python. You will be expected to independently understand and address data science problems using techniques such as linear regression, logistic regression, random forest, support vector machines, ANOVA/ANCOVA, time series modeling, segmentation, decision tree, clustering, recommendation engines, and forecasting. In this position, you will collaborate with a diverse team to contribute to Decision Sciences implementation projects. Your responsibilities will include developing analytical strategies for businesses, communicating with onsite coordinators, and presenting model results to clients. Timely completion of assigned tasks and regular status reporting will be essential components of your role. To be successful in this role, you should hold a degree in BE/BTech/MCA/MBA/CA with 0-3 years of experience in Information Management/Analytics. Having an understanding of Business Intelligence & Data Visualization concepts and experience with BI/Visualization tools will be advantageous. Additionally, you should possess excellent communication skills, a collaborative mindset, and a familiarity with software development best practices. If you have a background in the Banking/Finance domain, prior experience in client-facing roles, and strong written and verbal communication skills, it will be considered as additional assets. By joining EY, you will be part of a global organization dedicated to building a better working world through innovation, collaboration, and a commitment to creating value for clients, society, and the planet.,

To develop and maintain machine learning models aligned with business priorities, work with diverse technology stacks for model deployment and integration with business teams, and extract, transform, and derive key insights from data in order to improve business and customer experience - Proficiency in predictive modelling, feature engineering, Hypothesis testing and Machine Learning techniques (Decision Trees, GBM, XG-Boost, GLM modelling, Forecasting, Scorecard development, Clustering) - Proficiency in A/B Testing, campaign design and scaling data science models into production level model that can handle complex real-time data - Good hands on experience in Python and SQL - Expertise in AWS cloud Tech-stacks - Proficiency in analytics project management and working with business Stakeholders - Excellent communication skills with ability to explain the problems/solutions with clarity - Exposure to AWS services like SageMaker, Glue, Athena, S3 etc. - Knowledge on Gen AI - AWS certifications are a value add - Prior experience in Banking domain is a must

Work with subject matter experts from airlines to identify opportunities for leveraging data to deliver insights and actionable prediction of customer behavior and operations performance. Assess the effectiveness and accuracy of new data sources, data gathering and forecasting techniques. Develop custom data models and algorithms to apply to data sets and run proof of concept studies. Leverage existing Statistical and Machine Learning tools to enhance in-house algorithms. Collaborate with software engineers to implement and test production quality code for forecasting and data analytics models. Develop processes and tools to monitor and analyze data accuracy and models? performance. Demonstrate software to customers and perform value proving benchmarks. Calibrate software for customer needs and train customer for using and maintaining software. Resolve customer complaints with software and respond to suggestions for improvements and enhancements. Required Qualifications Advanced Degree in Statistics, Operations Research, Computer Science, Mathematics, Machine Learning or related Quantitative disciplines. Proven ability to apply modeling and analytical skills to real-world problems. Knowledge of a variety of machine learning techniques (clustering, decision tree learning, artificial neural networks, etc.) and their real-world advantages/drawbacks. Knowledge of advanced statistical techniques and concepts (regression, properties of distributions, statistical tests and proper usage, etc.) and experience with applications. Solid programming skills with knowledge of R, SQL, Python, PySpark or other data-extraction and analysis tools and programming languages such as Java, JavaScript or C++. Experience with deployment of machine learning and statistical models on a cloud and leveraging services like Amazon SageMaker and Amazon Forecast. Knowledge of airline revenue management algorithms and experience of developing demand forecasting and price optimization models

Job Description: AI Developer Fresher Location: Bangalore Company: MagicBox Cybersec Pvt. Ltd. Employment Type: Full-time | Entry-level Position Overview: We're MagicBox Cybersec, and we're building a powerful Cybersecurity in a Box a fully automated, AI- driven platform to detect threats, prevent intrusions, and ensure compliance. We're on the hunt for fresh minds who think logically, solve problems creatively, and love building smart systems that make the digital world safer. Key Responsibilities: • • • • Build and train AI/ML models for threat detection, anomaly detection, and behavioral analysis. Develop intelligent automation pipelines for cybersecurity operations. Work closely with AI & security experts to integrate models into real-time environments. Apply your skills in Python, ML libraries, and Linux to develop scalable solutions. Qualifications: • • Education o B.E./B.Tech/M.Tech in CS, AI, Data Science, or related fields o 01 year experience. Freshers are welcome! Skills o o o o o o o o o o Strong analytical and logical reasoning skills. Passion for AI/ML and interest in Cybersecurity. Familiarity with Python and frameworks like TensorFlow, PyTorch, or Scikit-learn. Comfortable in Linux environments (CLI, scripting). Project experience in AI/ML (college / online / hackathon / personal). Supervised/Unsupervised learning. Classification algorithms. Decision Trees. Random Forest. Deep Learning Algorithms(ANN, RNN, CNN, LSTMP, LLMs). Additional Qualifications: • • • Basic understanding of cybersecurity workflows (IDS, SIEM, etc.) Exposure to NLP or AI-based automation tools Git, Bash, or scripting experience What We Offer: • • • Work on cutting-edge AI Cybersecurity projects from day one. Mentorship and rapid learning opportunities. Flat structure, startup vibe, innovation-friendly culture. Ready to join us? Apply Now! Send your CV and a short note on your AI interests to: careers@magicboxcysec.com

Data Analyst, Food Supply Chain ABOUT US Target is an iconic brand, a Fortune 50 company and one of Americas leading retailers. At Target, we have a visionto become the best - the best culture and brand, the best place for growth and the company with the best reputation. We offer an inclusive, collaborative and energetic work environment that rewards those who perform. We deliver engaging, innovative and on-trend experiences for our team members and our guests. We invest in our team members' futures by developing leaders and providing a breadth of opportunities for professional development. It takes the best to become the best, and we are committed to building a team that does the right thing for our guests, shareholders, team members and communities. PRIMARY FUNCTION Data Analyst, Food Supply Chain to join our team. As a part of the F&B Data Analytics team, our analysts work closely with business owners as well as technology and data product teams staffed with product owners and engineers. They support all F&B strategic initiatives with data, reporting, visualization, insights, analysis, analytics and automation. F&B teams rely on this team of analysts to bring data to support decision making. ABOUT THE JOB As a Data Analyst you will support all business areas within Food Supply Chain of Target with critical data analysis that helps field and leadership to make profitable decisions. Become a data expert or business analyst and utilize tools like decision trees, clustering, regression, time series, structural equation modeling, linear programming, SQL and OLAP. Use your skills, experience and talents to be a part of groundbreaking thinking and visionary goals. Interface with the Target business representatives and leaders to validate business requirements/requests for reporting solutions. Determine best methods in order to gather data and present information. Build reporting solutions to meet business needs. Communicate with project/team manager to share knowledge and findings. Document design and requirements for reporting solutions. Core responsibilities of this job are described within this job description. Job duties may change at any time due to business need. ABOUT YOU: 4-year degree or equivalent experience 1+ year as a Data Analyst with strong academic performance in a quantitative field; or strong equivalent experience Intermediate SQL experience writing complex queries Solid problem solving, analytical skills, data curiosity, data mining, Data creation and consolidation Support conclusions with a clear, understandable story that leverages descriptive statistics, basic inferential statistics, and data visualizations Willingness to ask questions about business objectives and the measurement needs for a project workstream, and be able to measure objectives & key results Excellent communication skills with the ability to speak to both business and technical teams, and translate ideas between them Knowledge of AB Testing methods, time series, regression models including statistical analysis Experience in analytics tools such asSQL, Excel, Hadoop, Hive, Spark, Python, R, Domo and/or equivalent technologies Useful Links- Life at Target- https://india.target.com/ Benefits- https://india.target.com/life-at-target/workplace/benefits Culture- https://india.target.com/life-at-target/belonging

Hands on Experience:- NLP/LLM Hugging Face, YOLO, CNNs, Stable Diffusion ML algorithms (regression, decision trees, clustering) Model training/fine-tuning using real-world datasets FastAPI,Flask,Django Docker, Kubernetes Cloud experience

Educational Bachelor of Engineering Service Line Data & Analytics Unit Responsibilities Preferred Proficiency with statistical analysis tools (e.g., SAS, SPSS, R & Python) Hands on experience in Statistical Techniques & Deep Learning such as Decision Tree, Segmentation, Logistic and Multiple Regression, and others Experience of Forecasting, Campaign Management andCustomer Segmentation is desirable Strong Excel, Access and PowerPoint skills Familiarity with database query tools (SQL) Basic understanding of data warehouse architecture Understanding of various Analytical Tools, Platform & Frameworks. Technical and Professional : Data science . machine learning Good to have PySpark/Databricks Preferred Skills: Technology-Data Science-Machine Learning

The ideal candidate must possess knowledge relevant to the functional area, and act as a subject matter expert in providing advice in the area of expertise, and also focus on continuous improvement for maximum efficiency. It is vital to focus on the high standard of delivery excellence, provide top-notch service quality and develop successful long-term business partnerships with internal/external customers by identifying and fulfilling customer needs. The candidate should be able to break down complex problems into logical and manageable parts in a systematic way, and generate and compare multiple options, and set priorities to resolve problems. The ideal candidate must be proactive, and go beyond expectations to achieve job results and create new opportunities. The role must positively influence the team, motivate high performance, promote a friendly climate, give constructive feedback, provide development opportunities, and manage career aspirations of direct reports. Communication skills are key here, to explain organizational objectives, assignments, and the big picture to the team, and to articulate team vision and clear objectives. Senior Process Manager Role and responsibilities: Understand business problem and requirements by building domain knowledge and translate to data science problem. Conceptualize and design cutting edge data science solution to solve the data science problem, apply design-thinking concepts. Identify the right algorithms, tech stack, sample outputs required to efficiently adder the end need. Prototype and experiment the solution to successfully demonstrate the value. Independently or with support from team, execute the conceptualized solution as per plan by following project management guidelines. Present the results to internal and client stakeholder in an easy to understand manner with great story telling, story boarding, insights and visualization. Help build overall data science capability for eClerx through support in pilots, pre sales pitches, product development, and practice development initiatives. Technical and Functional Skills: Bachelors degree in Computer Science with 7 to 10 years of work experience. Must have experience in Advance Analytics, Data Science, regression, forecasting, analytics, SQL, R, Python, decision tree, random forest, SAS, clustering classification. Ability to engage clients to understand business requirements and convert the same into technical/modelling problems for solution development. Demonstrate strong interpersonal skills and a comfort interacting with clients from the C-suite to marketing managers to technical specialists. Demonstrated knowledge of analytical/statistical techniques and their applications; a working knowledge of/experience in R and Python is a plus. Demonstrated excellent communications skills, both written and spoken, as well as being able to explain complex technical concepts in plain English. Ability to present results of statistical models in business language. Domain understanding of at least one preferably two verticals amongst Retail, Cable, Technology (not mandate). Knowledge of data visualization tools (Tableau, QlikView, etc.) is a plus. Demonstrate strong analytical and storytelling skills and the ability to find relevant stories from piles of reports. Ability to manage specific tasks to completion with minimal direction. Ideal candidate has been in a consulting role previously. Hands-on expertise on the applied statistical techniques including multi-variate regression, logistic regression, market-mix models, clustering, classification, survival, churn models, speech analytics, image analytics, etc. Ability to collaborate with onsite colleagues in the US & UK. Expert in handling large data, cleansing & preparation for modelling. Very high attention to detail and quality.

The ideal candidate must possess knowledge relevant to the functional area, and act as a subject matter expert in providing advice in the area of expertise, and also focus on continuous improvement for maximum efficiency. It is vital to focus on the high standard of delivery excellence, provide top-notch service quality and develop successful long-term business partnerships with internal/external customers by identifying and fulfilling customer needs. The candidate should be able to break down complex problems into logical and manageable parts in a systematic way, and generate and compare multiple options, and set priorities to resolve problems. The ideal candidate must be proactive, and go beyond expectations to achieve job results and create new opportunities. The role must positively influence the team, motivate high performance, promote a friendly climate, give constructive feedback, provide development opportunities, and manage career aspirations of direct reports. Communication skills are key here, to explain organizational objectives, assignments, and the big picture to the team, and to articulate team vision and clear objectives. Senior Process Manager Role and responsibilities: Understand business problem and requirements by building domain knowledge and translate to data science problem. Conceptualize and design cutting edge data science solution to solve the data science problem, apply design-thinking concepts. Identify the right algorithms, tech stack, sample outputs required to efficiently adder the end need. Prototype and experiment the solution to successfully demonstrate the value. Independently or with support from team, execute the conceptualized solution as per plan by following project management guidelines. Present the results to internal and client stakeholder in an easy to understand manner with great story telling, story boarding, insights and visualization. Help build overall data science capability for eClerx through support in pilots, pre sales pitches, product development, and practice development initiatives. Technical and Functional Skills: Bachelors degree in Computer Science with 7 to 10 years of work experience. Must have experience in Advance Analytics, Data Science, regression, forecasting, analytics, SQL, R, Python, decision tree, random forest, SAS, clustering classification. Ability to engage clients to understand business requirements and convert the same into technical/modelling problems for solution development. Demonstrate strong interpersonal skills and a comfort interacting with clients from the C-suite to marketing managers to technical specialists. Demonstrated knowledge of analytical/statistical techniques and their applications; a working knowledge of/experience in R and Python is a plus. Demonstrated excellent communications skills, both written and spoken, as well as being able to explain complex technical concepts in plain English. Ability to present results of statistical models in business language. Domain understanding of at least one preferably two verticals amongst Retail, Cable, Technology (not mandate). Knowledge of data visualization tools (Tableau, QlikView, etc.) is a plus. Demonstrate strong analytical and storytelling skills and the ability to find relevant stories from piles of reports. Ability to manage specific tasks to completion with minimal direction. Ideal candidate has been in a consulting role previously. Hands-on expertise on the applied statistical techniques including multi-variate regression, logistic regression, market-mix models, clustering, classification, survival, churn models, speech analytics, image analytics, etc. Ability to collaborate with onsite colleagues in the US & UK. Expert in handling large data, cleansing & preparation for modelling. Very high attention to detail and quality.

The ideal candidate must possess in-depth functional knowledge of the process area and apply it to operational scenarios to provide effective solutions. The role enables to identify discrepancies and propose optimal solutions by using a logical, systematic, and sequential methodology. It is vital to be open-minded towards inputs and views from team members and to effectively lead, control, and motivate groups towards company objects. Additionally, candidate must be self-directed, proactive, and seize every opportunity to meet internal and external customer needs and achieve customer satisfaction by effectively auditing processes, implementing best practices and process improvements, and utilizing the frameworks and tools available. Goals and thoughts must be clearly and concisely articulated and conveyed, verbally and in writing, to clients, colleagues, subordinates, and supervisors. Associate Process Manager Role and responsibilities: Understand business problem and requirements by building domain knowledge and translate to data science problem. Conceptualize and design cutting edge data science solution to solve the data science problem, apply design-thinking concepts. Identify the right algorithms, tech stack, sample outputs required to efficiently adder the end need. Prototype and experiment the solution to successfully demonstrate the value. Independently or with support from team, execute the conceptualized solution as per plan by following project management guidelines. Present the results to internal and client stakeholder in an easy to understand manner with great story telling, story boarding, insights and visualization. Help build overall data science capability for eClerx through support in pilots, pre sales pitches, product development, and practice development initiatives. Technical and Functional Skills: Bachelors degree in Computer Science with 4 to 6 years of work experience. Must have experience in Advance Analytics, Data Science, regression, forecasting, analytics, SQL, R, Python, decision tree, random forest, SAS, clustering classification. Ability to engage clients to understand business requirements and convert the same into technical/modelling problems for solution development. Demonstrate strong interpersonal skills and a comfort interacting with clients from the C-suite to marketing managers to technical specialists. Demonstrated knowledge of analytical/statistical techniques and their applications; a working knowledge of/experience in R and Python is a plus. Demonstrated excellent communications skills, both written and spoken, as well as being able to explain complex technical concepts in plain English. Ability to present results of statistical models in business language. Domain understanding of at least one preferably two verticals amongst Retail, Cable, Technology (not mandate). Knowledge of data visualization tools (Tableau, QlikView, etc.) is a plus. Demonstrate strong analytical and storytelling skills and the ability to find relevant stories from piles of reports. Ability to manage specific tasks to completion with minimal direction. Ideal candidate has been in a consulting role previously. Hands-on expertise on the applied statistical techniques including multi-variate regression, logistic regression, market-mix models, clustering, classification, survival, churn models, speech analytics, image analytics, etc. Ability to collaborate with onsite colleagues in the US & UK. Expert in handling large data, cleansing & preparation for modelling. Very high attention to detail and quality.

The candidate must possess in-depth functional knowledge of the process area and apply it to operational scenarios to provide effective solutions. He/she must be able to identify discrepancies and propose optimal solutions by using a logical, systematic, and sequential methodology. It is vital to be open-minded towards inputs and views from team members and to effectively lead, control, and motivate groups towards company objects. Additionally, he/she must be self-directed, proactive, and seize every opportunity to meet internal and external customer needs and achieve customer satisfaction by effectively auditing processes, implementing best practices and process improvements, and utilizing the frameworks and tools available. Goals and thoughts must be clearly and concisely articulated and conveyed, verbally and in writing, to clients, colleagues, subordinates and supervisors. Process Manager Role and responsibilities: Understand business problem and requirements by building domain knowledge and translate to data science problem. Conceptualize and design cutting edge data science solution to solve the data science problem, apply design-thinking concepts. Identify the right algorithms, tech stack, sample outputs required to efficiently adder the end need. Prototype and experiment the solution to successfully demonstrate the value. Independently or with support from team, execute the conceptualized solution as per plan by following project management guidelines. Present the results to internal and client stakeholder in an easy to understand manner with great story telling, story boarding, insights and visualization. Help build overall data science capability for eClerx through support in pilots, pre sales pitches, product development, and practice development initiatives. Technical and Functional Skills: Bachelors degree in Computer Science with 5+ years of work experience. Must have experience in Advance Analytics, Data Science, regression, forecasting, analytics, SQL, R, Python, decision tree, random forest, SAS, clustering classification. Ability to engage clients to understand business requirements and convert the same into technical/modelling problems for solution development. Demonstrate strong interpersonal skills and a comfort interacting with clients from the C-suite to marketing managers to technical specialists. Demonstrated knowledge of analytical/statistical techniques and their applications; a working knowledge of/experience in R and Python is a plus. Demonstrated excellent communications skills, both written and spoken, as well as being able to explain complex technical concepts in plain English. Ability to present results of statistical models in business language. Domain understanding of at least one preferably two verticals amongst Retail, Cable, Technology (not mandate). Knowledge of data visualization tools (Tableau, QlikView, etc.) is a plus. Demonstrate strong analytical and storytelling skills and the ability to find relevant stories from piles of reports. Ability to manage specific tasks to completion with minimal direction. Ideal candidate has been in a consulting role previously. Hands-on expertise on the applied statistical techniques including multi-variate regression, logistic regression, market-mix models, clustering, classification, survival, churn models, speech analytics, image analytics, etc. Ability to collaborate with onsite colleagues in the US & UK. Expert in handling large data, cleansing & preparation for modelling. Very high attention to detail and quality.

The candidate must possess in-depth functional knowledge of the process area and apply it to operational scenarios to provide effective solutions. He/she must be able to identify discrepancies and propose optimal solutions by using a logical, systematic, and sequential methodology. It is vital to be open-minded towards inputs and views from team members and to effectively lead, control, and motivate groups towards company objects. Additionally, he/she must be self-directed, proactive, and seize every opportunity to meet internal and external customer needs and achieve customer satisfaction by effectively auditing processes, implementing best practices and process improvements, and utilizing the frameworks and tools available. Goals and thoughts must be clearly and concisely articulated and conveyed, verbally and in writing, to clients, colleagues, subordinates, and supervisors. Process Manager Role and responsibilities: Collaborate with clients to understand their business objectives and provide analytic solutions that positively address their needs. Conduct discovery sessions, workshops and whiteboard sessions to identify, understand and define customer needs, objectives, roadmaps and/or business requirements to design solutions that can best address existing or prospective clients. Conducting stakeholder interviews and workshops to gather and prioritize business requirements. Analysing and documenting current business processes and systems. Identifying opportunities for process improvement, cost reduction, and efficiency gains. Translating business requirements into functional specifications for technical teams. Identify the right algorithms, tech stack, sample outputs required to efficiently adder the end need. Collaborating with stakeholders to validate requirements and ensure alignment with business goals. Supporting the implementation and testing of solutions to ensure they meet business needs. Technical and Functional skills: 5 years of experience as a customer facing business analyst with minimum graduation in any field. Analytical ExpertiseProficient in analysing business processes, systems, and requirements to identify areas for improvement and optimization. Communication Skills: Ability to effectively communicate with stakeholders from various backgrounds to gather requirements, facilitate meetings, and present findings. Problem-Solving Skills: Capable of identifying problems, proposing solutions, and implementing strategies to address business challenges. DocumentationSkilled in documenting business requirements, user stories, process flows, and other artefact to ensure clear communication and understanding among stakeholders. Data AnalysisComfortable with data analysis techniques and tools to derive insights and make data-driven recommendations. Domain KnowledgePossesses a deep understanding of the Hi-tech industry or Supply chain / logistics domain, enabling them to provide valuable insights and recommendations. Project ManagementFamiliarity with project management methodologies and practices to effectively manage project timelines, resources, and deliverables. Must have experience in Advance Analytics, Data Science, regression, forecasting, analytics, SQL, R, Python, decision tree, random forest, SAS, clustering classification. Hands-on expertise on the applied statistical techniques including multi-variate regression, logistic regression, market-mix models, clustering, classification, survival, churn models, speech analytics, image analytics, etc. Knowledge of data visualization tools like Power BI, Tableau, QlikSense etc. Demonstrate strong analytical and storytelling skills and the ability to find relevant stories from piles of reports. Very high attention to detail and quality.

Immediate Openings on Data Scientist _India Experience : 5 + Skill:- Data Scientist Location : India Notice Period :- Immediate . Employment Type: Contract . Job Description: Strong problem-solving skills with an emphasis on product development. Experience using statistical computer languages (R, Python, SLQ, etc.) to manipulate data and draw insights from large data sets. Experience working with and creating data architectures. Knowledge of a variety of machine learning techniques (clustering, decision tree learning, artificial neural networks, etc.) and their real-world advantages/drawbacks. Knowledge of advanced statistical techniques and concepts (regression, properties of distributions, statistical tests and proper usage, etc.) and experience with applications. Excellent written and verbal communication skills for coordinating across teams. A drive to learn and master new technologies and techniques. Were looking for someone with 5-7 years of experience manipulating data sets and building statistical models, has a Masters in Statistics, Mathematics, Computer Science or another quantitative field, and is familiar with the following software/tools: Coding knowledge and experience with several languages: C, C++, Java, JavaScript, etc. Knowledge and experience in statistical and data mining techniques: GLM/Regression, Random Forest, Boosting, Trees, text mining, social network analysis, etc. Experience querying databases and using statistical computer languages: R, Python, SLQ, etc. Experience using web services: Redshift, S3, Spark, etc. Experience creating and using advanced machine learning algorithms and statistics: regression, simulation, scenario analysis, modeling, clustering, decision trees, neural networks, etc. Experience analyzing data from 3rd party providers: Google Analytics, Crimson Hexagon, Facebook Insights, etc. Experience visualizing/presenting data for stakeholders using different tools. Working knowledge of message queuing (Kafka or Google Pub/Sub), stream processing, and highly scalable data stores.

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 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

Evaluate model development data quality, methodology Perform proper documentation Conduct in-depth analysis of large data sets and support the review and maintenance process of relevant models and model validation documentation. Required Candidate profile 2+ years experience in model development or model validation experience in the retail section of a U. S. financial services/banking hands-on and proven experience utilizing Python, Spark , SAS, SQL,

Skill required: Insight Engine - Analytics Insights Designation: Analytics and Modeling Analyst Qualifications: Any Graduation Years of Experience: 3 to 5 years About Accenture Combining unmatched experience and specialized skills across more than 40 industries, we offer Strategy and Consulting, Technology and Operations services, and Accenture Song all powered by the worlds largest network of Advanced Technology and Intelligent Operations centers. Our 699,000 people deliver on the promise of technology and human ingenuity every day, serving clients in more than 120 countries. Visit us at www.accenture.com What would you do We are seeking a Machine Learning Data Scientist with 2 to 3 years of hands-on experience to join our growing Insights and Analytics team. The ideal candidate will be proficient in building ML models using supervised and unsupervised learning techniques, comfortable working with Python-based ML libraries, and experienced in data preparation workflows. Familiarity with Microsofts AI/ML ecosystem is a strong advantage. What are we looking for Preferred (Strong Advantage):Hands-on experience with Azure Machine Learning Studio and Automated ML.Familiarity with Azure Cognitive Services for vision, language, and decision tasks.Experience working with Microsoft Fabric and Synapse ML integration. Qualifications:Bachelor s or Masters degree in Computer Science, Data Science, Engineering, or related field.23 years of experience in applied machine learning and data science projects.Solid understanding of model training, validation, and deployment workflows.Experience working with version control (e.g., Git) and collaborative development environments.Nice to Have:Familiarity with tools that help automate and manage the process of building, testing, and deploying machine learning models (MLOps and CI/CD pipelines).Basic understanding of cloud-based architecture and APIs. Roles and Responsibilities: Develop and implement machine learning models using supervised and unsupervised techniques.Apply appropriate machine learning algorithms for prediction tasks (e.g., linear regression, decision trees, neural networks) and data segmentation (e.g., k-means clustering, hierarchical clustering) based on project needs.Perform data preprocessing, feature engineering, and model evaluation.Use Python libraries such as scikit-learn, TensorFlow, and others to build and test models.Analyse and manipulate structured datasets using notebooks (e.g., Jupyter).Collaborate with data engineers, analysts, and product teams to translate business problems into ML solutions.Document model performance, data flows, and process pipelines. Qualification Any Graduation

In the IBM Chief Information Office,you wi be part of a dynamic team driving the future of AI and data science in arge-scae enterprise transformations. We offer a coaborative environment where your technica expertise wi be vaued, and your professiona deveopment wi be supported. Join us to work on chaenging projects, everage the atest technoogies, and make a tangibe impact on eading organisations. As a Data Scientist within IBM's Chief Information Office, you wi support AI-driven projects across the enterprise. You wi appy your technica skis in AI, machine earning, and data anaytics to assist in impementing data-driven soutions that aign with business goas. This roe invoves working with team members to transate data insights into actionabe recommendations. Key Responsibiities: Technica Execution and Leadership: Deveop and depoy AI modes and data anaytics soutions. Support the impementation and optimisation of AI-driven strategies per business stakehoder requirements. Hep refine data-driven methodoogies for transformation projects. Data Science and AI: Design and impement machine earning soutions and statistica modes, from probem formuation through depoyment, to anayse compex datasets and generate actionabe insights. Learn and utiise coud patforms to ensure the scaabiity of AI soutions. Leverage reusabe assets and appy IBM standards for data science and deveopment. Project Support: Lead and contribute to various stages of AI and data science projects, from data exporation to mode deveopment. Monitor project timeines and hep resove technica chaenges. Design and impement measurement frameworks to benchmark AI soutions, quantifying business impact through KPIs. Coaboration: Ensure aignment to stakehoders strategic direction and tactica needs. Work with data engineers, software deveopers, and other team members to integrate AI soutions into existing systems. Contribute technica expertise to cross-functiona teams. Required education Bacheor's Degree Preferred education Master's Degree Required technica and professiona expertise Bacheors or Masters in Computer Science, Data Science, Statistics, or a reated fied is required; an advanced degree is strongy preferred Experience: 5+ yearsof experience in data science, AI, or anaytics with a focus on impementing data-driven soutions Experience with data ceaning, data anaysis, A/B testing, and data visuaization Experience with AI technoogies through coursework or projects Technica Skis: Proficiency in SQL and Python for performing data anaysis and deveoping machine earning modes Knowedge of common machine earning agorithms and frameworksinear regression, decision trees, random forests, gradient boosting (e.g., XGBoost, LightGBM), neura networks, and deep earning frameworks such as TensorFow and PyTorch Experience with coud-based patforms and data processing frameworks Understanding of arge anguage modes (LLMs) Famiiarity with IBMs watsonx product suite Famiiarity with object-oriented programming Anaytica Skis: Strong probem-soving abiities and eagerness to earn

Industry: General Insurance Role Lead Data Scientist Years of Experience 8+ years Purpose of Role In this role, The Candidate should be highly analytical with a knack for analysis, math, and statistics. Critical thinking and problem-solving skills are essential for interpreting data. To help our company analyze trends to make better decisions. Build propensity models, customer segmentations, uplift models, campaign response models, risk, and fraud detection models. Also, Integrate the models with the business processes and consuming systems via ML Ops processes. The ideal candidate is adept at using large data sets to find opportunities for product and process optimization and using models to evaluate the effectiveness of different courses of action. Key Accountabilities Responsibilities will include but will not be restricted to: Create models as required by the business with a high degree of precision and recall. Model accuracy and stability are key accountabilities. Understand business priorities and align data science deliverables to ensure the business receives the intelligence and modeling inputs to drive decisions. Work with stakeholders throughout the organization to identify opportunities for using company data to drive business solutions. Undertake preprocessing of structured and unstructured data and analyze large amounts of information to discover trends and patterns. Assess the effectiveness and accuracy of new data sources and data gathering techniques. Coordinate with different functional teams to implement models and monitor outcomes. Recruit, train, develop and supervise Junior level employees. Develop processes and tools to monitor and analyze model performance and data accuracy. Technical Requirements (what) Proven experience of 8+ years as a Data Scientist. Post Graduate degree in Computer Science, Statistics, Engineering, Physics, Mathematics, Econometrics or MBA with a ML/DS focus. Knowledge of SQL and R or Python; familiarity with Scala & SPARK is an asset. Candidates with experience of working on AWS stack will be preferred, however this is not a compulsory requirement. Knowledge and experience in machine learning, optimization, statistical and data mining techniques- regression, simulation, clustering, decision trees, classification algos (bagging/boosting), neural networks. Desired Personal Qualities or Behavior Strong Analytical critical thinking skills and business acumen Strong commitment to professional development. Process Oriented and excellent time management skills. Ability to adapt to new situations and issues and to solve problems. Good organizational, communication, presentational and people skills - with the capability to communicate concisely and effectively equally well with fellow employees, non-technical colleagues and with members and/or customers alike. Only apply if you are matching with above Criteria Work From Office First and last Saturday will be working 60 and 90 Days Notice periods Please don't apply. Interested candidates can share their resumes at - shubhanshi.agarwal@mounttalent.com 7302239534