39 Decision Tree Jobs

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

Role & responsibilities Develop and implement a comprehensive analytics strategy to support the organization's business objectives. Lead cross-functional projects using advanced data modeling and analysis techniques to discover insights that will guide strategic decisions and uncover optimization opportunities. Build, develop and maintain data models, reporting systems, data automation systems, dashboards and performance metrics support that support key business decisions on Microsoft Power BI and Snowflake. Driving key business impacting processes like demand forecast generation and SNOP processes. Generating sales recommendation for trade sales team. Optimizing business process like network, inventory, etc., with data modeling and predicting / prescribing algorithms. Oversee the design and delivery of reports and insights that analyze business functions and key operations and performance metrics. Manage and optimize processes for data intake, validation, mining and engineering as well as modeling, visualization and communication deliverables. Anticipate future demands of initiatives related to people, technology, budget and business within your department and design/implement solutions to meet these needs. Apply advanced analytics techniques to improve commercial routines and processes. Organize and drive successful completion of data insight initiatives through effective management of analyst and data employees and effective collaboration with stakeholders. Communicate results and business impacts of insight initiatives to stakeholders within and outside of the company. Ability to look, analyse, critically think, and communicate insights to support data-driven decisions. Preferred candidate profile With 10+ years of experience in a position monitoring, managing, manipulating and drawing insights from data, and someone with at least 3 years of experience leading a team Experience with data visualization tools: Power BI, Tableau, Raw, chart.js, etc. Experience in understanding and managing the data flow across multiple systems to datawarehouse. Working knowledge of data mining principles: predictive analytics, mapping, collecting data from multiple data systems on premises and cloud-based data sources. Understanding of and experience using analytical concepts and statistical techniques: hypothesis development, designing tests/experiments, analyzing data, drawing conclusions, and developing actionable recommendations for business units.

Job Title - + + Management Level: Location:Kochi, Coimbatore, Trivandrum Must have skills:Big Data, Python or R Good to have skills:Scala, SQL Job Summary A Data Scientist is expected to be hands-on to deliver end to end vis a vis projects undertaken in the Analytics space. They must have a proven ability to drive business results with their data-based insights. They must be comfortable working with a wide range of stakeholders and functional teams. The right candidate will have a passion for discovering solutions hidden in large data sets and working with stakeholders to improve business outcomes. Roles and Responsibilities Identify valuable data sources and collection processes Supervise preprocessing of structured and unstructured data Analyze large amounts of information to discover trends and patterns for insurance industry. Build predictive models and machine-learning algorithms Combine models through ensemble modeling Present information using data visualization techniques Collaborate with engineering and product development teams Hands-on knowledge of implementing various AI algorithms and best-fit scenarios Has worked on Generative AI based implementations Professional and Technical Skills 3.5-5 years experience in Analytics systems/program delivery; at least 2 Big Data or Advanced Analytics project implementation experience Experience using statistical computer languages (R, Python, SQL, Pyspark, etc.) to manipulate data and draw insights from large data sets; familiarity with Scala, Java or C++ 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 Hands on experience in Azure/AWS analytics platform (3+ years) Experience using variations of Databricks or similar analytical applications in AWS/Azure Experience using business intelligence tools (e.g. Tableau) and data frameworks (e.g. Hadoop) Strong mathematical skills (e.g. statistics, algebra) Excellent communication and presentation skills Deploying data pipelines in production based on Continuous Delivery practices. Additional Information Multi Industry domain experience Expert in Python, Scala, SQL Knowledge of Tableau/Power BI or similar self-service visualization tools Interpersonal and Team skills should be top notch Nice to have leadership experience in the past Qualification Experience:3.5 -5 years of experience is required Educational Qualification:Graduation (Accurate educational details should capture)

Title : Senior Manager -Data Science, Machine Learning and GenAI Technical Leader Job Area: Information Technology Group, Information Technology Group > IT Management General Summary: Experience in engaging with business and technical stakeholders, understanding complex problem statements, and proposing value-driven Data Science & ML solutionsFunctional & technical leadership in developing data science roadmap and guiding the team with end-to-end delivery (design, development, maintenance, and optimization) of advanced analytical solutions with focus on process standardization and best practicesProactive in reaching out to wide variety of stakeholders for increasing the awareness of Data Science, ML and GenAI capabilities and identifying business value driven opportunitiesAnalyze the market and industry trends in the technology and proactively look for opportunities in bringing the best solutions 'Strong analytical skills with the ability to gather information from several sources and identify fundamental patterns/trends in dataConduct research, design statistical studies and develop solutionsDevelop Story Telling dashboards on analytics to assist business in decision makingImplement deep learning models for structured and unstructured data setsPerform Time Series Analysis and Forecast (ARIMA, Exponential Smoothing, VAR etc.)Implementation experience with identifying, prototyping, developing and delivering GenAI solutions using Industry standard RAG models and frameworksAbility to develop capabilities in Text Analytics ranging from Basic to Advanced (Topic Modelling, NLP)Experience with AWS suite of Data Science and ML toolsDevelops predictive models using Machine Learning algorithms (SVM, Random Forest, Neural Network, Decision Tree, Logistic Regression, K-mean Clustering, Catboost etc.) 'Experience with other cloud platforms (GCP and Azure)Understanding of Data Platforms and Data EngineeringExposure to ChatBot solutions and Automation technologies Minimum Qualifications: 7+ years of IT-related work experience with a Bachelor's degree. OR 9+ years of IT-related work experience without a Bachelors degree. 4+ years in a leadership role in projects/programs.

hands on SQL/ SAS programming experience & handling complex/large data Must have experience inTableau/Power BI Experience in campaign performance measurement, customer targeting framework Proven ability to design and lead strategic projects Required Candidate profile Must - SAS , SQL, Python Good in Statistical model , Predictive model, Logistic regression, Linear regression BFSI Mandatory - Credit risk, Credit Card, Retail Banking

Roles & Responsibilities: Ensure that high quality bio statistical and psychopharmacology support is provided by the Analytics team Ensure that staff implement innovative, rigorous bio statistical methods to meet study objectives Lead RWE (Real World Evidence) large scale analytics (LSA) studies. Run statistical programs in R, R shiny, deploy study packages and generate reliable RWE results in TFLs with minimal supervision. Provide statistical support for design, implementation, running, analysis and dissemination of results for clinical trials Design and analyze clinical research projects Create and execute Statistical Analysis Plans Strong Knowledge in RWE(Real World Evidence) with Bio statistics Background Experience in creating cohort analysis or Meta analysis or Survival analysis or Bayesian Versus Frequentest Approaches to Clinical Trials Experience in implementing generalized mixture models, Bayesian mixer models, Fixed-effects and Random-effects models Knowledge on Statistical Process Control, Stochastic Optimization Knowledgeable in R or Python programming Skills and shiny web app development Knowledge on Cloud platform like AWS Exposure to Healthcare data formats like HL7, OMOP, ODHSI Exposure to RWE, RWA, RWD Experience with data sources like registries, EMR Good communications Skills

Role And Responsibilities : - Work with stakeholders throughout the organization to identify opportunities for leveraging company data to drive business solutions. - Mine and analyze data from company databases to drive optimization and improvement of business strategies. - Assess the effectiveness and accuracy of data sources and data gathering techniques. - Develop custom data models and algorithms to apply to data sets. - Use predictive modelling to increase and optimize business outcomes. - Work individually or with extended teams to operationalize models & algorithms into structured software, programs or operational processes - Coordinate with different functional teams to implement models and monitor outcomes. - Develop processes and tools to monitor and analyze model performance and data accuracy. - Provide recommendations to business users based upon data/ model outcomes, and implement recommendations including changes in operational processes, technology or data management - Primary area of focus: PSCM/ VMI business; secondary area of focus: ICS KPI s - Business improvements pre & post (either operational program, algorithm, model or resultant software). Improvements measured in time and/or dollar savings - Satisfaction score of business users (of either operational program, algorithm, model or resultant software). Qualifications And Education Requirements - Graduate BSc/BTech in applied sciences with year 2 statistics courses. - Relevant Internship (at least 2 months) OR Relevant Certifications of Preferred Skills. Preferred Skills - Strong problem-solving skills with an emphasis on business development. - Experience the following coding languages : - R or python (Data Cleaning, Statistical and Modelling packages) , SQL, VBA and DAX (PowerBI) - Knowledge of 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 technique Compliance Requirements : - GET has a Business Ethics Policy which provides guidance to all employees in their day-to-day roles as well as helping you and the business comply with the law at all times. The incumbent must read, understand and comply with, at all times, the policy along with all other corresponding policies, procedures and directives. QHSE Responsibilities - Demonstrate a personal commitment to Quality, Health, Safety and the Environment. - Apply GET, and where appropriate Client Company s, Quality, Health, Safety & Environment Policies and Safety Management Systems. - Promote a culture of continuous improvement, and lead by example to ensure company goals are achieved and exceeded. Skills - Analytical skills - Negotiation - Convincing skills Key Competencies - Never give up attitude - Flexible - Eye to detail Experience: Minimum 8 Years Of Experience.

Job Information Job Opening ID ZR_1640_JOB Date Opened 13/12/2022 Industry Technology Job Type Work Experience 8-12 years Job Title Sr Technical Lead City Hyderabad Province Telangana Country India Postal Code 500001 Number of Positions 4 Roles & Responsibilities: Ensure that high quality bio statistical and psychopharmacology support is provided by the Analytics team Ensure that staff implement innovative, rigorous bio statistical methods to meet study objectives Lead RWE (Real World Evidence) large scale analytics (LSA) studies. Run statistical programs in R, R shiny, deploy study packages and generate reliable RWE results in TFLs with minimal supervision. Provide statistical support for design, implementation, running, analysis and dissemination of results for clinical trials Design and analyze clinical research projects Create and execute Statistical Analysis Plans Strong Knowledge in RWE(Real World Evidence) with Bio statistics Background Experience in creating cohort analysis or Meta analysis or Survival analysis or Bayesian Versus Frequentest Approaches to Clinical Trials Experience in implementing generalized mixture models, Bayesian mixer models, Fixed-effects and Random-effects models Knowledge on Statistical Process Control, Stochastic Optimization Knowledgeable in R or Python programming Skills and shiny web app development Knowledge on Cloud platform like AWS Exposure to Healthcare data formats like HL7, OMOP, ODHSI Exposure to RWE, RWA, RWD Experience with data sources like registries, EMR Good communications Skills check(event) ; career-website-detail-template-2 => apply(record.id,meta)" mousedown="lyte-button => check(event)" final-style="background-color:#2B39C2;border-color:#2B39C2;color:white;" final-class="lyte-button lyteBackgroundColorBtn lyteSuccess" lyte-rendered=""> I'm interested

Data Scientist (6-8 Years Experience) Company Overview Accenture is a global professional services company with leading capabilities in digital, cloud, and security. Combining unmatched experience and specialized skills across more than 40 industries, we offer Strategy and Consulting, Interactive, Technology, and Operations services"”all powered by the world's largest network of Advanced Technology and Intelligent Operations centers. Our 700,000+ people deliver on the promise of technology and human ingenuity every day, serving clients in more than 120 countries. We embrace the power of change to create value and shared success for our clients, people, shareholders, partners, and communities. At Accenture, we offer a dynamic and challenging environment for analytical and creative minds. We value a diverse workforce committed to achieving client goals and delivering results. Were built on a foundation of exceptional talent and are on the lookout for driven, energetic professionals to enhance our team. Key Responsibilities Data Handling Data Collection:Participate in calls with stakeholders (internal and external, based in the US) to gather data from various sources (email, Dropbox, Egnyte, databases). Data Audit:Lead assessment of data quality, identify gaps, and create summaries as per database requirements. Data Scrubbing:Assist with creating data cleansing rules and incorporate data clarifications provided by data source owners. Data Profiling:Assist with creating multi-dimensional data views, data analysis reports, and extracts. Data Classification Spend Classification:Analyze procurement spend using several techniques to comprehensively classify into a custom taxonomy in Accenture's spend analytics tool. Enhancements:Diligently incorporate feedback and make recommendations for process improvement. Report Generation:Create specific and opportunity spend-assessment reports/templates. Periodic Refreshes:Lead discussions with US-based stakeholders for data gathering, data quality checks, control total validation, and spend classification. Advanced Analytics and AI/ML Develop custom data models and algorithms to apply to data sets. Use machine learning tools and statistical techniques to produce solutions to problems. Implement clustering and auto classification using predictive and supervised learning techniques. Design and implement complex data models from scratch. Develop and optimize ETL processes to ensure efficient data handling and processing. Create intuitive and effective front-end interfaces from scratch. Apply AI/ML techniques to optimize supply chain management, including demand forecasting, inventory optimization, and supplier performance analysis. Utilize advanced machine learning algorithms and statistics:regression, simulation, scenario analysis, modeling, clustering, decision trees, neural networks, etc. Develop and implement AI/ML models for predictive analytics and automated decision-making in supply chain operations. Industry Research Secondary Research:Conduct market research to create company and industry primers using online secondary data or information sources. Technical Requirements Python:Hands-on experience with threading limitations and multi-process architecture. MySQL:Ability to integrate multiple data sources using MySQL. Strong coding knowledge and experience with several languages (e.g., R, SQL, JavaScript, Java, CSS, C++). Familiarity with statistical and data mining techniques (e.g., GLM/Regression, Random Forest, Boosting, Trees, text mining, social network analysis). Experience with advanced machine learning algorithms and statistics:regression, simulation, scenario analysis, modeling, clustering, decision trees, neural networks, etc. Collaboration and Communication Coordinate with different functional teams to implement models and monitor outcomes. Develop processes and tools to monitor and analyze model performance and data accuracy. Excellent spoken and written English communication skills, with the ability to participate in global team calls. Other Important Details Work Location:Gurugram, India Expected Start Dates:July 2024 Qualifications Who Should Apply? Work Experience:6-8 years of relevant experience in data modeling, ETL automation, AI/ML, and front-end design. Academic Qualifications:Bachelor’s or Master’s degree in Engineering, Mathematics, Computer Science, or a related field. Job Requirements: - Extensive experience in handling and classifying spend data using AI/ML Techniques. - Strong leadership and team management skills. - Proficiency in MS Excel and MS PowerPoint. - High attention to detail, accuracy, and innovative problem-solving skills. - Preferred experience in supply chain management, with a focus on applying AI/ML techniques to optimize operations.

Data Analytics Engineer / Data Scientist Location- Mysuru (Preferred) or Remote (India) Full-Time | 3+ Years Experience ABOUT HOPTEKAI: At Hoptek, a Kearney Company, were building AI-powered SaaS products that help trucking companies operate smarter from pricing freight and planning networks to allocating assets and reducing waste. We’re looking for a Data Analytics Engineer / Data Scientist who’s excited to solve hard operations problems, build AI models that get embedded into our products, and help our customers get smarter through data. If you love building applied ML solutions and developing new ideas at the intersection of logistics and optimization, this role is for you. POSITION OVERVIEW: Build machine learning and optimization models to support pricing, routing, and network planning Partner with product and engineering teams to embed AI algorithms into customer-facing software Analyze freight networks and develop insights that drive operational efficiency Use PostgreSQL and Apache Superset to develop internal and customer-facing analytics as needed Prototype innovative solutions to unstructured problems using Python, OR techniques, and statistical methods Understand how customers interact with the platform and develop analytics to support adoption and value delivery What We’re Looking For: 3+ years of experience in data science, analytics engineering, or operations research Proficiency in Python, SQL, and relevant data/ML libraries (e.g., pandas, scikit-learn, XGBoost) Strong grasp of optimization techniques, network models, or decision science Familiarity with data visualization tools — especially Apache Superset Ability to work with real-world, messy logistics data and extract actionable intelligence Curiosity and creativity in approaching open-ended product and analytics challenges Bonus Points For: Experience in transportation, logistics, or freight planning Hands-on experience with graph analytics or geospatial data Experience productionizing ML/OR models within SaaS applications Exposure to pricing algorithms, dynamic optimization, or network simulations Why HOPTEKAI: Applied AI, Real Impact: Your work powers critical product decisions — from what to bid, to where to send the next truck Innovation-Driven: You’ll get to explore new techniques and shape the future of optimization in freight Close Loop from Data to Product: Help us transform ideas into algorithms, and algorithms into product features Mysuru Preferred: Collaborate on-site with our core team — or work remotely within India We’re Hiring Fast: Join a high-impact team at a critical growth moment

Core Characteristics Achievement-oriented Enjoys taking on challenges, even if they might fail. Innovative – Prefers working in unconventional ways or on tasks that require creativity with multivariable inputs and uncertainties. Resource maximizing – Identifies and leverages team resource strengths, while maintaining awareness and pushing for needed growth opportunities. Autonomous/ independent – Enjoys working with little direction. Dynamically detail oriented – Has the awareness of the need and ability to go deep without getting lost, while staying grounded with the bigger picture. Critical thinker – Applies logic, reason, and rationale to a given problem and/ or proposed solution. Dependable – More reliable than spontaneous. Flexible – Ability to manage competing priorities in a fluid environment. Prioritizing – Effective with prioritization, goal setting, and time management. Communicator – Excellent in communications, interpersonally, and in writing. Key Responsibilities: Analyze and interpret complex datasets to uncover valuable insights. Develop and implement Machine Learning (ML) models and algorithms. Collaborate with the team to design and execute data experiments. Utilize cloud platforms for data storage, processing, and analysis. Present findings and insights to both technical and non-technical stakeholders Stay updated on industry trends and advancements in data science, with a focus on healthcare informatics. Analyze complex healthcare data sets to identify trends, patterns, and insights. Create and present reports, dashboards, and visualizations to communicate findings to stakeholders. Isolate healthcare trend drivers and financial impacts associated with client medical claims, pharmacy claims, and other types of healthcare data. Perform varying types of analysis including medical carrier network valuations, discount analysis, and benchmarking. Conduct complex analyses adhering to best practice standards by selecting appropriate data sources, developing assumptions, recognizing considerations, and establishing recommendations. Identify opportunities for process improvement and efficiency through data analysis. Resolve unreasonable results, suboptimal solutions, and data anomalies based on experience and professional judgment. Act as a technical expert and advise on strategic data mining techniques used to identify new relationships or patterns in data. Build predictive models to accurately analyze potential outcomes that are likely costs / savings for a given initiative or event(s). Translate, document, and present approaches, processes, and results of complex modeling and statistical analysis into layperson terms for diverse, internal and external audiences. Qualifications: Degree in computer science, Statistics, Data Science, or a related field. Strong working knowledge of data manipulation and analysis libraries (e.g. Pandas, NumPy, scikit-learn) Familiarity with machine learning (ML) concepts and algorithms. Analyze and interpret complex healthcare datasets to extract valuable insights. Experience with data visualization tools (e.g. Matplotlib, Seaborn, tableau, PowerBI) Basic understanding of databases systems and SQL Experience with cloud platforms (e.g., AWS, Azure or Google Cloud) in a healthcare and biomedical data (ex., clinical and life-sciences) context. Experience with AI/ML frameworks (e.g., TensorFlow, PyTorch) and familiarity with generative AI tools for innovative data-driven solutions. Excellent problem-solving and analytical skills. Eagerness to learn and adapt to new technologies and methodologies. Must possess strong analytical skills with the ability to collect, organize, analyze, and disseminate information with attention to detail and accuracy. Ability to generate information quickly and manage multiple projects at once. Strong analytical skills with the ability to collect, organize, analyze, conceptualize, problem solve, and disseminate information confidently and collaboratively with attention to detail, accuracy, timeliness. Experience in building and deploying highly scalable systems, algorithms, and tools on platforms to support machine learning and deep learning solutions Experience with Azure/AWS tools and technology

Job Description: We are seeking an experienced Data Scientist with expertise in advanced machine learning techniques to join our dynamic team. The ideal candidate will have hands-on experience developing and deploying models using ensemble methods and other cutting-edge ML algorithms, mostly in the US banking domain. Key Responsibilities: Develop and help deploy advanced machine learning models, including ensemble techniques, for customer lifecycle use cases (e.g., prescreen, acquisition, account management, collections, and fraud). Collaborate with cross-functional teams to define, develop, and improve predictive models that drive business decisions. Work with large datasets, utilizing tools like Python and SQL , to extract, clean, and transform data for modeling purposes. Ensure model robustness, interpretability, and scalability within banking environments. Strong problem-solving skills with the ability to handle complex datasets and turn them into actionable insights.

Data Scientist with experience in projects related to Churn- Machine learning-random Forest-XGBoost-Logistics Regression. candidate must be an immediate Joiner or 30 Days NP

Project Role : Data Engineer Project Role Description : Design, develop and maintain data solutions for data generation, collection, and processing. Create data pipelines, ensure data quality, and implement ETL (extract, transform and load) processes to migrate and deploy data across systems. Must have skills : Python (Programming Language) Good to have skills : Oracle Procedural Language Extensions to SQL (PLSQL)Minimum 3 year(s) of experience is required Educational Qualification : 15 years full time education Summary :As a Data Engineer, you will design, develop, and maintain data solutions for data generation, collection, and processing. Create data pipelines, ensure data quality, and implement ETL processes to migrate and deploy data across systems. Be involved in the end-to-end data management process. Roles & Responsibilities:- Expected to perform independently and become an SME.- Required active participation/contribution in team discussions.- Contribute in providing solutions to work-related problems.- Develop and maintain data pipelines.- Ensure data quality throughout the data management process. Professional & Technical Skills: - Must To Have Skills: Proficiency in Python (Programming Language).- Strong understanding of statistical analysis and machine learning algorithms.- Experience with data visualization tools such as Tableau or Power BI.- Hands-on implementing various machine learning algorithms such as linear regression, logistic regression, decision trees, and clustering algorithms.- Solid grasp of data munging techniques, including data cleaning, transformation, and normalization to ensure data quality and integrity. Additional Information:- The candidate should have a minimum of 3 years of experience in Python (Programming Language).- This position is based at our Gurugram office.- A 15 years full-time education is required. Qualification 15 years full time education