205 Random Forest Jobs - Page 8

Team: - Strategy & Consulting Practice: - Marketing Analytics - Conversational AI Job location: - Hyderabad Should have hands on experience with at least one Machine learning algorithm, Logistic Regression, Random Forest, K-Means Clustering. Fallout Analytics, NLP, Journey Analytics, Audio Personification, Customer analytics Concepts of Intent, Entity, Fallback Management and Context Management AI bot using Dialogflow / Rasa / EX / ES. Webhooks and Ngrok, programming language like Python, SQL - Advanced Level. Omni Channel Integration Regression Testing Node.js Understanding of CI/CD pipelines Advanced Level. Experience with proposing solution architectures.

GM Analytics Solutions is looking for a driven, dedicated and experienced Data Scientist Essential Responsibilities: As a Data Scientist, you will solve complex challenges and identify new opportunities using a combination of Data analytical expertise, business acumen, strategic thinking, and project & relationship management skills. He/she will work with the Product Owner, VP of IT capture business requirements, The Data Scientist will partner with the development team (on-site and off-shore) to execute the projects. Must have strong knowledge about statistical techniques like segmentation, predictive modeling, statistical modeling clustering, linear regression, logistic regression, SVM, Random Forest, Gradient Boosting, Optimization and time series forecasting to derive meaningful insights from data and to build high level solutions that predict and optimize business outcomes based on client's success criterion. Requirement: Minimum with 3 years hands-on in machine learning algorithms Should be familiar with Supervised and Unsupervised algorithms and should have worked on Anomaly detection. Excellent understanding of machine learning techniques and algorithms and should be proficient in some or all of the following techniques: Linear & Logistic Regression, Decision Trees, Random Forests, K-Nearest Neighbors, Markov Chain, Monte Carlo, Gibbs Sampling, Evolutionary Algorithms, Support Vector Machines, Neural Networks, k-NN, Naive Bayes, SVM, Decision Forests etc Expert knowledge of advanced data mining and statistical modeling techniques, including Predictive modeling (e.g., binomial and multinomial regression, ANOVA); Classification techniques, Clustering, Principal Component Analysis, factor analysis; Decision Tree techniques (e.g., CART, CHAID) Should have some experience working with time series data Comfortable working with the Engineering Team to design, code, train, test, deploy and iterate on enterprise-scale machine learning systems Expert in Data processing, wrangling and visualization Experience with automated feature engineering and dealing with large datasets Should have experience in deploying machine learning model Very Good analytical thinking with problem-solving abilities Should have experience in deploying machine learning model Good knowledge on writing complex SQL queries for selecting data from database. Comfortable working with Python, Jupyter Notebook and ability to work with machine learning frameworks. Deliver results within committed scope, timeline, and budget Role & Responsibility: Works to design and develop analytical/ data mining/ machine learning/deep learning models as part of data science solutions Perform quantitative and qualitative analysis like (raw) data analysis, statistical modelling, data deep-dives etc. to acquire insights from data Data pulling or creating from different sources Responsible for analyzing data from multiple data sources (DBs, flat files, etc.), and building predictive models using Python Work to design and build an end-to-end prototype data science solution to a business problem in any specific sector/ function, more specific to healthcare domain. Develop actionable insights to drive outcome. Translate insights into an analysis report and communicates the insights back to the requestor.. Different models and their performances in Real time and Batch developed using Python (Pandas)/MLib/PySpark and opting the better solution depending on the cases Validate the models - statistically as well as from business perspective in discussions with business stakeholders Work to support and guide model deployment and model lifecycle management Map insights to action items (working with stakeholders) in order to improve business metrics Facilitate monitoring of actions to drive outcome: Monitor actions (targeted business outcomes achieved)- by providing guidance and feedback to the operations team Project governance: Ensure compliance to governance model. Seek and manage customer feedback in order to ensure strong customer satisfaction on projects Competency Requirements: Must possess the following knowledge, skills, and abilities to perform this job successfully: Familiar with standard concepts, practices, and procedures within the field. Creativity and latitude required. Ability to work in a fast-paced, result-driven, and complex healthcare setting. Ability to meet strict deadlines. Excellent analytical, problem-solving, organization and time management skills. Takes a sense of ownership Capable of embracing unexpected change in direction or priority. Excellent communication skills. Strong self-sufficiency and initiative working on database projects. This position may be modified to reasonably accommodate an incumbent with a disability. This job requires the ability to work with others in a team environment, the ability to accept direction from superiors and the ability to follow Company policies and procedures. Regular, predictable and dependable attendance is essential to the satisfactory performance of this job. GM Analytics is an equal opportunity employer and considers qualified applicants for employment without regard to race, color, creed, religion, national origin, sex, sexual orientation, gender identity and expression, age, disability, veteran status, or any other protected factor.to join our Gurgaon based team of IT professionals. The position is responsible for projects heavy in back-end database work including creating and maintaining interfaces between multiple sources and the database.

About The Role 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.

About The Role 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.

About The Role 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.

About The Role 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.

About The Role 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.

Role Overview: As a Data Scientist within IBM's Chief Analytics Office, you will support AI-driven projects across the enterprise. You will apply your technical skills in AI, machine learning, and data analytics to assist in implementing data-driven solutions that align with business goals. This role involves working with team members to translate data insights into actionable recommendations. Key Responsibilities: Technical Execution and Leadership: Develop and deploy AI models and data analytics solutions. Support the implementation and optimization of AI-driven strategies per business stakeholder requirements. Help refine data-driven methodologies for transformation projects. Data Science and AI: Design and implement machine learning solutions and statistical models, from problem formulation through deployment, to analyze complex datasets and generate actionable insights. Learn and utilize cloud platforms to ensure the scalability of AI solutions. Leverage reusable assets and apply IBM standards for data science and development. Project Support: Lead and contribute to various stages of AI and data science projects, from data exploration to model development. Monitor project timelines and help resolve technical challenges. Design and implement measurement frameworks to benchmark AI solutions, quantifying business impact through KPIs. Collaboration: Ensure alignment to stakeholders’ strategic direction and tactical needs. Work with data engineers, software developers, and other team members to integrate AI solutions into existing systems. Contribute technical expertise to cross-functional teams. Required education Bachelor's Degree Preferred education Master's Degree Required technical and professional expertise Education: Bachelor’s or Master’s in Computer Science, Data Science, Statistics, or a related field is required; an advanced degree strongly preferred Experience: 5+ yearsof experience in data science, AI, or analytics with a focus on implementing data-driven solutions Experience with data cleaning, data analysis, A/B testing, and data visualization Experience with AI technologies through coursework or projects Technical Skills: Proficiency in SQL and Python for performing data analysis and developing machine learning models Knowledge of common machine learning algorithms and frameworkslinear regression, decision trees, random forests, gradient boosting (e.g., XGBoost, LightGBM), neural networks, and deep learning frameworks such as TensorFlow and PyTorch Experience with cloud-based platforms and data processing frameworks Understanding of large language models (LLMs) Familiarity with IBM’s watsonx product suite Familiarity with object-oriented programming Analytical Skills: Strong problem-solving abilities and eagerness to learn Ability to work with datasets and derive insights Other Requirements: Good communication skills, with the ability to explain technical concepts clearly Enthusiasm for learning and applying new technologies Strong project management skills, with the ability to balance multiple initiatives, prioritize tasks effectively, and meet deadlines in a fast-paced environment Successful completion of Coding Assessment Preferred technical and professional experience Advanced degree strongly preferred

Exp - 6- 10 Years Level - Senior Consultant Skill - ML OPS with Gen AI Location - Bengaluru Event on 9th May in Bangalore location Hybrid Mode (2 days WFO in a week) Education - B.Tech/B.E/MS/MBA ML OPs Engineer Required: 6-10 years of Consulting, Data, and Analytics experience Experience in descriptive & predictive analytics, both theoretical and practical knowledge in basic ML algorithms like linear and non-linear regression, linear and non-linear classification, dimensional reduction, anomaly detection, statistical concepts and techniques like theoretical distributions, parametric and non-parametric inference 6+ years of experience implementing & executing data science projects throughout the entire lifecycle: Developing/designing and implementing solutions E2E in production. Strong knowledge of Python or R Programming experience with Node.js, SQL, Java, JavaScript OR PERL Experience in cloud-based data platforms on AWS, GCP and Azure Understanding of multi-tier application architectures Ability to develop, test and maintain programming environments and architectural standards Foundational understanding of application development lifecycle and using tools like ANT, Maven, Gradle and Version control (SVN OR GIT OR BitBucket) Experience with working in an agile development lifecycle and continuous integration processes using tools such as Jenkins Experience in doing deployments for Java, .NET , Angular , Node.js , PHP, Python applications using Jenkins/Bamboo Experience on code quality assessment tools and integration with CI tool Strong logical structuring and problem-solving skills Strong verbal, written and presentation skills Preferred Additional Experience in using Spark either with Scala or Python Experience with different database types like RDS and NoSQL Experience in cloud deployments Knowledge of working in a Linux environment Strong understanding and experience configuring, managing and supporting applications using tools such as OpsWorks, Datadog and CloudWatch on AWS Experience in Docker /Swarm / Kubernetes Experience or exposure to Test Driven Development Experience (Junit / TestNG) Experience on Behavior Driven Development Experience (Cucumber / Selenium) Expertise in any commercial data visualization tool such as Tableau, Qlik, Power BI Experience with real time data movement solutions that use security and encryption protocols while data is in transit

Skills Required: Python, R, Statistics, Machine Learning, Deep Learning, Cluster Regression, Generative AI (GenAI) Responsibilities: Assist with the development, testing, and deployment of AI/ML models, including Generative AI (GenAI) solutions. Brainstorm and implement solutions by referencing research papers, scholarly articles, and industry best practices. Perform data mining using state-of-the-art methods to extract insights and enable predictive analytics. Process, cleanse, and verify the integrity of datasets , ensuring their usability for accurate analysis and model training. Conduct error analysis for demand, wind, and solar forecast models to identify and implement enhancements. Carry out manual computations for demand, wind, and solar forecasts, complementing automated systems when necessary. Perform in-depth analysis to uncover insights and solve complex problems within the renewable energy domain. Understand and optimise forecasting models using R and Python programming. Design and implement new scripts in R and Python to automate tasks and improve operational efficiency. Develop Generative AI applications , including scenario generation, predictive modelling, and domain-specific innovations. Collaborate with cross-functional teams to integrate GenAI solutions into forecasting workflows. Update project status for self-assigned tasks daily, ensuring clear communication and project alignment.

Practical in applying geometric concepts, with strong Python & SQL skills. Creative problem-solver, innovator, able to build agent-driven solutions. Senior dev with TDD, AWS knowledge preferred over Ph.D.

Role Overview: As a Data Scientist within IBM's Chief Analytics Office, you will support AI-driven projects across the enterprise. You will apply your technical skills in AI, machine learning, and data analytics to assist in implementing data-driven solutions that align with business goals. This role involves working with team members to translate data insights into actionable recommendations. Key Responsibilities: Technical Execution and Leadership: Develop and deploy AI models and data analytics solutions. Support the implementation and optimization of AI-driven strategies per business stakeholder requirements. Help refine data-driven methodologies for transformation projects. Data Science and AI: Design and implement machine learning solutions and statistical models, from problem formulation through deployment, to analyze complex datasets and generate actionable insights. Learn and utilize cloud platforms to ensure the scalability of AI solutions. Leverage reusable assets and apply IBM standards for data science and development. Project Support: Lead and contribute to various stages of AI and data science projects, from data exploration to model development. Monitor project timelines and help resolve technical challenges. Design and implement measurement frameworks to benchmark AI solutions, quantifying business impact through KPIs. Collaboration: Ensure alignment to stakeholders’ strategic direction and tactical needs. Work with data engineers, software developers, and other team members to integrate AI solutions into existing systems. Contribute technical expertise to cross-functional teams. Required education Bachelor's Degree Preferred education Master's Degree Required technical and professional expertise Experience: 5+ yearsof experience in data science, AI, or analytics with a focus on implementing data-driven solutions Experience with data cleaning, data analysis, A/B testing, and data visualization Experience with AI technologies through coursework or projects Technical Skills: Proficiency in SQL and Python for performing data analysis and developing machine learning models Knowledge of common machine learning algorithms and frameworkslinear regression, decision trees, random forests, gradient boosting (e.g., XGBoost, LightGBM), neural networks, and deep learning frameworks such as TensorFlow and PyTorch Experience with cloud-based platforms and data processing frameworks Understanding of large language models (LLMs) Familiarity with IBM’s watsonx product suite Familiarity with object-oriented programming Analytical Skills: Strong problem-solving abilities and eagerness to learn Ability to work with datasets and derive insights Other : Good communication skills, with the ability to explain technical concepts clearly. Enthusiasm for learning and applying new technologies Strong project management skills, with the ability to balance multiple initiatives, prioritize tasks effectively, and meet deadlines in a fast-paced environment Successful completion of Coding Assessment Preferred technical and professional experience . Education: Bachelor’s or Master’s in Computer Science, Data Science, Statistics, or a related field is required; an advanced degree strongly preferred Advanced degree strongly preferred

Optum is a global organization that delivers care, aided by technology to help millions of people live healthier lives. Come make an impact on the communities we serve as you help us advance health optimization on a global scale. Join us to start Caring. Connecting. Growing together. Primary Responsibilities: Drive client value by: Creating innovative solutions driven by exploratory data analysis from diverse datasets Responsible for developing/delivering end-to-end Machine Learning projects/solutions that have a high degree of value, ambiguity, scale and complexity Ability to coach/guide follow data scientists and accountable for delivering advanced analytics products Using an analytical approach to design, develop, and implement data enrichments, predictive models, and advanced algorithms that lead to expanded value extraction from data Leading efforts for applied use of machine learning to drive process optimization and transformation Applying knowledge of data modeling, statistics, machine learning, programming, simulation, and advanced mathematics to recognize patterns, identify opportunities, pose business questions, and make valuable discoveries leading to more actionable insights Working with analytics and statistical software and products, such as SQL, R, Python, Hadoop and others to perform analysis and interpret data Creating artifacts like STM, HLD, LLD for hardening prototypes into production (prototype to hardening) Communicate the performance of the machine learning algorithms across an interdisciplinary team Create impact at scale by: Developing and managing a comprehensive catalog of scalable data services that expand the value of analytical offerings Designing and promoting best practices related to data enrichment, advanced modeling, and algorithm creation in support of analytically driven insight Collaborating with business intelligence architects and domain analysts to maximize the effectiveness of business intelligence tools, dashboards, and other dynamic reporting capabilities Leading efforts to build sophisticated data enrichment processes that server as the single source of truth to expanded insights on base data Ensuring complex analytics adhere to statistical best practices Comply with the terms and conditions of the employment contract, company policies and procedures, and any and all directives (such as, but not limited to, transfer and/or re-assignment to different work locations, change in teams and/or work shifts, policies in regard to flexibility of work benefits and/or work environment, alternative work arrangements, and other decisions that may arise due to the changing business environment). The Company may adopt, vary or rescind these policies and directives in its absolute discretion and without any limitation (implied or otherwise) on its ability to do so Required Qualifications: Bachelors degree (preferably in information technology, engineering, math, computer science, analytics, engineering or other related field) 8+ years of combined experience in data science, data enrichment, and advanced modeling 8+ years of experience creating models/solutions using Python, Spark-SQL, Scala or other similar coding language 8+ years of experience manipulating large data sets through statistical software (ex. R, SAS) or other methods 5+ years of experience managing complex data projects and programs 5+ years of experience creating healthcare analytics Hands on experience in Microsoft Azure, Databricks, Mlflow and model deployment frameworks Hands-on experience in implementing and training machine learning algorithms and statistical analyses, including for example non-parametric tests, linear mixed models, modern supervised and unsupervised machine learning algorithms such as SVM, random forest, PCA, t-SNE, clustering, deep learning, and LLMs Highly proficient with hands-on experience in Python coding, Spark SQL and any other programming language along with corresponding language packages Proven excellent communication and presentation skills Ability to develop and deploy data pipelines, machine learning models, or applications on cloud platforms (Azure, Databricks, AzureML)

Job description: Enable data driven decision making across the Tesco business globally by developing analytics solutions using a combination of math, tech and business knowledge. In this job, I am accountable for: Following our Business Code of Conduct and always acting with integrity and due diligence and have these specific risk responsibilities: - Understands business needs and in depth understanding of Tesco processes - Builds on Tesco processes and knowledge by applying CI tools and techniques. - Responsible for completing tasks and transactions within agreed KPI's - Solves problems by analyzing solution alternatives Engaging with business & functional partners to understand business priorities, ask relevant questions and scope same into a analytical solution document calling out how application of data science will improve decision making In depth understanding of techniques to prepare the analytical data set leveraging multiple complex data set sources - Building Statistical models and ML algorithms with practitioner level competency -Writing structured, modularized & codified algorithms using Continuous Improvement principles (development of knowledge assets and reusable modules on GitHub, Wiki, etc) with expert competency - Building easy visualization layer on top of the algorithms in order to empower end-users to take decisions - this could be on a visualization platform (Tableau / Python) or through a recommendation set through PPTs Working with the line manager to ensure application / consumption and proactively identifying opportunities to help the larger Tesco business with areas of improvement. Experience relevant for this job: - Applied Math: Applied Statistics, Design of Experiments, - 2 - 4 years experience in data science application in Retail or Regression, Decision Trees, Forecasting, Optimization CPG Preferred algorithms, Clustering, NLP - Functional experience: Marketing, Supply Chain, Customer, - Tech: SQL, Hadoop, Spark, Python, Tableau, MS Excel, MS Merchandising, Operations, Finance or Digital PowerPoint, GitHub - Business: Basic understanding of Retail domain - Soft Skills: Analytical Thinking & Problem solving, Storyboarding, Articulate communication

Primary Responsibilities: Drive client value by: Creating innovative solutions driven by exploratory data analysis from diverse datasets Responsible for developing/delivering end-to-end Machine Learning projects/solutions that have a high degree of value, ambiguity, scale and complexity Ability to coach/guide follow data scientists and accountable for delivering advanced analytics products Using an analytical approach to design, develop, and implement data enrichments, predictive models, and advanced algorithms that lead to expanded value extraction from data Leading efforts for applied use of machine learning to drive process optimization and transformation Applying knowledge of data modeling, statistics, machine learning, programming, simulation, and advanced mathematics to recognize patterns, identify opportunities, pose business questions, and make valuable discoveries leading to more actionable insights Working with analytics and statistical software and products, such as SQL, R, Python, Hadoop and others to perform analysis and interpret data Creating artifacts like STM, HLD, LLD for hardening prototypes into production (prototype to hardening) Communicate the performance of the machine learning algorithms across an interdisciplinary team Create impact at scale by: Developing and managing a comprehensive catalog of scalable data services that expand the value of analytical offerings Designing and promoting best practices related to data enrichment, advanced modeling, and algorithm creation in support of analytically driven insight Collaborating with business intelligence architects and domain analysts to maximize the effectiveness of business intelligence tools, dashboards, and other dynamic reporting capabilities Leading efforts to build sophisticated data enrichment processes that server as the single source of truth to expanded insights on base data Ensuring complex analytics adhere to statistical best practices Comply with the terms and conditions of the employment contract, company policies and procedures, and any and all directives (such as, but not limited to, transfer and/or re-assignment to different work locations, change in teams and/or work shifts, policies in regard to flexibility of work benefits and/or work environment, alternative work arrangements, and other decisions that may arise due to the changing business environment). The Company may adopt, vary or rescind these policies and directives in its absolute discretion and without any limitation (implied or otherwise) on its ability to do so Required Qualifications: Bachelors degree (preferably in information technology, engineering, math, computer science, analytics, engineering or other related field) 8+ years of combined experience in data science, data enrichment, and advanced modeling 8+ years of experience creating models/solutions using Python, Spark-SQL, Scala or other similar coding language 8+ years of experience manipulating large data sets through statistical software (ex. R, SAS) or other methods 5+ years of experience managing complex data projects and programs 5+ years of experience creating healthcare analytics Hands on experience in Microsoft Azure, Databricks, Mlflow and model deployment frameworks Hands-on experience in implementing and training machine learning algorithms and statistical analyses, including for example non-parametric tests, linear mixed models, modern supervised and unsupervised machine learning algorithms such as SVM, random forest, PCA, t-SNE, clustering, deep learning, and LLMs Highly proficient with hands-on experience in Python coding, Spark SQL and any other programming language along with corresponding language packages Proven excellent communication and presentation skills Ability to develop and deploy data pipelines, machine learning models, or applications on cloud platforms (Azure, Databricks, AzureML)

Bachelors/Master’s degree in Computer Science, Data Science, AI/ML, or related field. Strong programming experience in Python (NumPy, Pandas, Scikit-learn, PyTorch/TensorFlow). Solid experience in machine learning, NLP, and deep learning frameworks . Hands-on expertise in LLMs (OpenAI, Hugging Face Transformers, LangChain, RAG frameworks) . Knowledge of vector databases (Pinecone, Weaviate, FAISS, Milvus) for semantic search and retrieval-augmented generation. Experience with cloud AI services (AWS SageMaker, GCP Vertex AI, Azure ML). Strong skills in SQL and data visualization tools (Power BI, Tableau, or similar). Familiarity with MLOps and model lifecycle management . Excellent analytical, problem-solving, and stakeholder communication skills. Good to Have (Preferred): Experience with multi-modal LLMs (text + image, text + speech). Understanding of Reinforcement Learning from Human Feedback (RLHF) . Contributions to open-source NLP/LLM projects. Prior experience in financial services, healthcare, or e-commerce domain is a plus.

Role: Gather relevant information to define the business problem Creative thinker capable of linking AI methodologies to identified business challenges Develop AI/ML applications leveraging the latest industry and academic advancements Ability to work cross-functionally, and across borders drawing on a broader team of colleagues to effectively execute the AI agenda All About You: Demonstrated passion for AI competing in sponsored challenges such as Kaggle Previous experience with or exposure to: Deep Learning algorithm techniques, open source tools and technologies, statistical tools, and programming environments such as Python, R, and SQL Big Data platforms such as Hadoop, Hive, Spark, GPU Clusters for deep learning Classical Machine Learning Algorithms like Logistic Regression, Decision trees, Clustering (K-means, Hierarchical and Self-organizing Maps), TSNE, PCA, Bayesian models, Time Series ARIMA/ARMA, Recommender Systems - Collaborative Filtering, FPMC, FISM, Fossil Deep Learning algorithm techniques like Random Forest, GBM, KNN, SVM, Bayesian, Text Mining techniques, Multilayer Perceptron, Neural Networks Feedforward, CNN, LSTMs GRUs is a plus. Optimization techniques Activity regularization (L1 and L2), Adam, Adagrad, Adadelta concepts; Cost Functions in Neural Nets Contrastive Loss, Hinge Loss, Binary Cross entropy, Categorical Cross entropy; developed applications in KRR, NLP, Speech and Image processing Deep Learning frameworks for Production Systems like Tensorflow, Keras (for RPD and neural net architecture evaluation), PyTorch and Xgboost, Caffe, and Theono is a plus Concentration in Computer Science.

Welcome to the relentless pursuit of better. Inviting applications for the role of Data Scientist The position is based out of India and the focus of the role is to have enterprise level experience in Predictive and NLP Model build, validation, implementation, monitoring, etc. and do analysis on data, be able to understand, translate and integrate the analysis. We are seeking a highly skilled and experienced Generative AI Specialist for developing and implementing cutting-edge generative models to solve complex problems using LLM technology. Need to collaborate with cross-functional teams, conduct research, and deliver innovative solutions in the field of generative artificial intelligence. Responsibilities Participating and collaborating with operation teams in the organization to understand the business requirements and to deliver scalable solutions. Conduct thorough research on state-of-the-art generative AI techniques, stay up to date with the latest advancements, and apply them to enhance the capabilities of LLM models. Ability to create models using Classification and Regression techniques and perform Hypothesis Testing and Feature selection. Strong analytical and problem-solving skills, and ability to set goals and meet deadlines in fast paced working environment. Analyze user behavior, conversion data, customer journeys to generate hypothesis and build optimization plans and provide insights for feature improvements. Perform deep dive analyses on key business trends from different perspectives and package the insights into easily consumable presentations and documents. Lead efforts to train and fine-tune language models, ensuring they meet high standards of performance, efficiency, and safety. Work on strategies to scale language models, optimizing for efficiency and reducing resource consumption. Deploy model in cloud- Azure, AWS, GCP. Qualifications we seek in you. Minimum qualifications Education in Statistics, Mathematics, Computer Science, or another quantitative field. Preferred qualifications Experience using computer languages (Python, SQL, etc.) to manipulate data and draw insights from large data sets. Experience in deploying LLM models in production. Experience in using industry standard AI/ML libraries i.e., Sklearn, Keras, Tensorflow, AutoML etc. Solid understanding of generative AI concepts, frameworks, and techniques, with hands-on experience in developing and deploying generative models. Proficiency in working with Large Language Models (LLMs), such as GPT-3, GPT-4, or similar models like Llama 2, Falcon LLM. Strong programming skills in languages such as Python and experience with deep learning libraries/frameworks (e.g., TensorFlow, PyTorch). Strong communication and collaboration skills, with the ability to work effectively in a multidisciplinary team environment. Familiarity with natural language processing (NLP) and understanding of various NLP tasks is a plus. Prior experience in handling LLM use cases or working with large-scale language models is highly desirable. Ensure data quality and integrity through best practices and compliance to framework, architecture, and coding standards. Genpact is an Equal Opportunity Employer and considers applicants for all positions without regard to race, color, religion or belief, sex, age, national origin, citizenship status, marital status, military/veteran status, genetic information, sexual orientation, gender identity, physical or mental disability or any other characteristic protected by applicable laws. Genpact is committed to creating a dynamic work environment that values diversity and inclusion, respect and integrity, customer focus, and innovation. For more information, visit www.genpact.com. Follow us on Twitter, Facebook, LinkedIn, and YouTube. Furthermore, please do note that Genpact does not charge fees to process job applications and applicants are not required to pay to participate in our hiring process in any other way. Examples of such scams include purchasing a 'starter kit,' paying to apply, or purchasing equipment or training.

Location - All Genpact Locations Responsibilities Professional experience with different regression and classification methods in implementation and deployment of project on AWS GCP and Azure cloud platform. Follow the standard practice and guidelines while using Python, SQL. Experience with Langchain framework for GenAI. Develop and fine-tuning Generative AI models such as GPT for various applications. Using Generative AI to work on tasks like text generation, sentiment analysis, chatbots and language translation using RAG and agent-based models. Adjust language models that have already been trained for generative AI applications. Experience in tokenization and embeddings and must have used GPT, LLaMA, Huggingface, Mistral, AWS BedRock for deploying the models. Analyze data and Generating insights using generative AI techniques for predictive modelling and data generation. Building chatbot using different scalable data source for generating charts and statement. Having experience building front end application using Streamlit/Gradio/Flask/Fast for Generative AI input and output display. Responsible for weekly release of upgrades and new features to enhance current algorithm. Evaluating the performance of generative AI models and implementing improvements based on feedback. Ensuring ethical and responsible use of AI by addressing bias, privacy concerns and fairness in AI models. Must Demonstrate understanding of evaluation metrics specific to GenAI task such as inception score, frechet inception distance, perpetual path length. Collaborating with cross-functional teams, including data scientist, engineers, and domain experts to integrate Generative AI into product or services. Able to design Machine learning, Deep learning and Generative AI architecture and its successful execution in the project. Must have basic understanding on Word and Excel. Proficiency in programming language like Python, SQL, frameworks such as Langchain for AI model development. Experience on Rest API, Flask API, Fast API. Qualifications we seek in you!Minimum Qualifications / Skills Any Graduate BE/B- Tech, BCA, MCA, BSc/MSc Behavioral / team skills Personal drive and positive work ethic to deliver results within tight deadlines and in demanding situations Flexibility to adapt to a variety of engagement types, working hours and work environments and locations Excellent written, oral communication and presentation skills Bring a data-driven approach to decision making intellectually curious, always eager to learn new skills and share the knowledge with others Proactive planner and can work independently to manage own responsibilities Genpact is an Equal Opportunity Employer and considers applicants for all positions without regard to race, color, religion or belief, sex, age, national origin, citizenship status, marital status, military/veteran status, genetic information, sexual orientation, gender identity, physical or mental disability or any other characteristic protected by applicable laws. Genpact is committed to creating a dynamic work environment that values diversity and inclusion, respect and integrity, customer focus, and innovation. Get to know us at genpact.com and on LinkedIn, X, YouTube, and Facebook.Furthermore, please do note that Genpact does not charge fees to process job applications and applicants are not required to pay to participate in our hiring process in any other way. Examples of such scams include purchasing a 'starter kit,' paying to apply, or purchasing equipment or training.

Bachelor's /Master's /PhD degree in a quantitative field (CS, Machine learning, Mathematics, Economics, Statistics, Data Science) Preferred Institution: NIT, ISI, Any - School of Economics Responsibilities: Serve as expert in Data Science, build framework to develop Production level DS/AI models. Apply AI research and ML models to accelerate business innovation and solve impactful business problems for our clients. Partner with business and technical stakeholders to translate challenging business problems into state-of-the-art data science solutions. Present results, insights, and recommendations to senior management with an emphasis on the business impact. Build engaging rapport with client leadership through relevant conversations and genuine business recommendations that impact the growth and profitability of the organization. Required Skills: Expertise in ML - Regression, Classification, Clustering, Time Series Modeling, Graph Network, Recommender System, Bayesian modeling, Deep learning, Computer Vision, NLP/NLU, Reinforcement learning, Federated Learning, Meta Learning. Proficient in some or all of the following techniques: Linear & Logistic Regression, Decision Trees, Random Forests, K-Nearest Neighbors, Support Vector Machines ANOVA, Principal Component Analysis, Gradient Boosted Trees, ANN, CNN, RNN, Transformers. Expertise in programming languages SQL, Python/ R, Spark. Expertise in ML frameworks and libraries (TensorFlow, Keras, PyTorch). Experience with cloud computing services Azure. Expert in Statistical Modelling & Algorithms E.g. Hypothesis testing, Sample size estimation, A/B testing. Knowledge in Mathematical programming - Linear Programming, Mixed Integer Programming etc , Stochastic Modelling - Markov chains, Monte Carlo, Stochastic Simulation, Queuing Models. Experience with Optimization Solvers (Gurobi, Cplex) and Algebraic programming Languages(PulP). Knowledge in GPU code optimization, Spark MLlib Optimization. Familiarity to deploy and monitor ML models in production, delivering data products to end-users. Experience with ML CI/CD pipelines.

Bachelor's /Master's /PhD degree in a quantitative field (CS, Machine learning, Mathematics, Economics, Statistics, Data Science) Preferred Institution: NIT, ISI, Any - Scool of Economics Responsibilities: Serve as expert in Data Science, build framework to develop Production level DS/AI models. Apply AI research and ML models to accelerate business innovation and solve impactful business problems for our clients. Partner with business and technical stakeholders to translate challenging business problems into state-of-the-art data science solutions. Present results, insights, and recommendations to senior management with an emphasis on the business impact. Build engaging rapport with client leadership through relevant conversations and genuine business recommendations that impact the growth and profitability of the organization. Required Skills: Expertise in ML - Regression, Classification, Clustering, Time Series Modeling, Graph Network, Recommender System, Bayesian modeling, Deep learning, Computer Vision, NLP/NLU, Reinforcement learning, Federated Learning, Meta Learning. Proficient in some or all of the following techniques: Linear & Logistic Regression, Decision Trees, Random Forests, K-Nearest Neighbors, Support Vector Machines ANOVA, Principal Component Analysis, Gradient Boosted Trees, ANN, CNN, RNN, Transformers. Expertise in programming languages SQL, Python/ R, Spark. Expertise in ML frameworks and libraries (TensorFlow, Keras, PyTorch). Experience with cloud computing services Azure. Expert in Statistical Modelling & Algorithms E.g. Hypothesis testing, Sample size estimation, A/B testing. Knowledge in Mathematical programming - Linear Programming, Mixed Integer Programming etc , Stochastic Modelling - Markov chains, Monte Carlo, Stochastic Simulation, Queuing Models. Experience with Optimization Solvers (Gurobi, Cplex) and Algebraic programming Languages(PulP). Knowledge in GPU code optimization, Spark MLlib Optimization. Familiarity to deploy and monitor ML models in production, delivering data products to end-users. Experience with ML CI/CD pipelines.

Bachelor's /Master's /PhD degree in a quantitative field (CS, Machine learning, Mathematics, Economics, Statistics, Data Science) Preferred Institution: NIT, ISI, Any - School of Economics Required Skills: Expertise in ML - Regression, Classification, Clustering, Time Series Modeling, Graph Network, Recommender System, Bayesian modeling, Deep learning, Computer Vision, NLP/NLU, Reinforcement learning, Federated Learning, Meta Learning. Proficient in some or all of the following techniques: Linear & Logistic Regression, Decision Trees, Random Forests, K-Nearest Neighbors, Support Vector Machines ANOVA, Principal Component Analysis, Gradient Boosted Trees, ANN, CNN, RNN, Transformers. Expertise in programming languages SQL, Python/ R, Spark. Expertise in ML frameworks and libraries (TensorFlow, Keras, PyTorch). Knowledge in cloud computing services Azure. Expert in Statistical Modelling & Algorithms E.g. Hypothesis testing, Sample size estimation, A/B testing. Knowledge in Mathematical programming - Linear Programming, Mixed Integer Programming etc , Stochastic Modelling - Markov chains, Monte Carlo, Stochastic Simulation, Queuing Models. Familiarity to deploy and monitor ML models in production, delivering data products to end-users.

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 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.

We are looking for a Senior Data Scientist who is passionate about solving complex business problems using data. The ideal candidate will have strong hands-on experience in Python , SQL , and advanced machine learning algorithms , along with domain expertise in forecasting , pricing optimization , or inventory planning . You will work closely with cross-functional teams including product, engineering, and business stakeholders to drive data-driven strategies. Key Responsibilities: Design, build, and deploy predictive and optimization models for use cases such as demand forecasting , dynamic pricing , or inventory optimization . Translate business problems into analytical frameworks and provide actionable insights. Build and maintain scalable data pipelines and model workflows using Python and SQL. Collaborate with data engineers to ensure model integration into production systems. Present findings and recommendations to leadership using data visualizations and storytelling. Stay current with the latest techniques in machine learning , statistics , and operations research . Lead and mentor junior data scientists and analysts when required. Required Skills and Experience: 5+ years of experience in a Data Science or Analytics role with a strong business impact. Strong programming skills in Python (pandas, scikit-learn, statsmodels, etc.). Proficiency in SQL for data extraction, transformation, and manipulation. Deep understanding of machine learning algorithms (regression, classification, clustering, time series forecasting). Experience with one or more of the following domains: Demand Forecasting Price Optimization Inventory Optimization / Supply Chain Analytics Strong problem-solving and quantitative skills. Experience working with large datasets and distributed computing tools (e.g., Spark, Hadoop) is a plus. Familiarity with data visualization tools (e.g., Tableau, Power BI, matplotlib, seaborn). Preferred Qualifications: Masters or PhD in Computer Science, Statistics, Mathematics, Economics, Operations Research, or a related field. Experience in retail, e-commerce, manufacturing, or logistics is a strong plus. Exposure to optimization libraries (e.g., PuLP, OR-Tools, Gurobi) is a bonus. Experience deploying models using MLOps tools or platforms is a plus.