107 Random Forest Jobs - Page 4

Position Overview As the newest addition to our existing Data Science team, youll combine your analytical skills and business knowledge to deliver key insights to our Product and Management teams. Youll help drive product development using our vast user data sets to enhance our current products and to help us find inferences and relationships in this data to build new productsMore towards the role required Company Overview BOLD is an established and fast-growing product company that transforms work lives. Since 2005, weve helped more than 10,000,000 folks from all over America(and beyond!) reach higher and do better. A career at BOLD promises great challenges, opportunities, culture and the environment. With our headquarters in Puerto Rico and offices in San Francisco and India, were a global organization on a path to change the career industry. Key Responsibilities Demonstrate ability to work on data science projects involving NLP, large language models, predictive modelling, statistical analysis, vector space modelling, machine learning etc. Leverage our rich data sets of user data to perform research, develop models and create data products with our Development & Product teams Develop novel and scalable data systems in cooperation with our system architects that leverage datasets using machine learning techniques to enhance the user experience Collaborates effectively with cross functional teams to deliver end-to-end products & features. Demonstrates ability to multi-task and re-prioritize responsibilities based on changing requirements. Estimates efforts, identify risks, devises and meets project schedules. Runs review meetings effectively and drive the closure of all open issues on time Mentors/coaches data scientists to facilitate their development and provide technical leadership to them. Rises above detail to see broader issues and implications for whole product/team Required Skills Knowledge and experience using statistical and machine learning algorithms including regression, instance-based learning, decision trees, Bayesian statistics, clustering, neural networks, deep learning, ensemble methods Expert knowledge in Python. Experience in using large language models. Experience in feature selection, building and optimizing classifiers. Experience working with backend technologies such asFlask/Gunicorn etc. Experience on working with open source library such Spacy, NLTK, Gensim etc Experience on working with deep-learning library such as Tensor flow, Pytorch etc. Experience with software stack components including common programming languages, back-end technologies, database modelling, continuous integration, services oriented architecture, software testability etc. Be a keen learner and enthusiastic about developing software

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 : 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

Location:Bangalore/Gurgaon/Hyderabad/Mumbai Must have skills: Must have skills:Data Scientist / Transformation Leader & at least 5 years in Telecom Analytics Good to have skills:GEN AI, Agentic AI, Job Summary : About Global Network Data & AI:- Accenture Strategy & Consulting Global Network - Data & AI practice help our clients grow their business in entirely new ways. Analytics enables our clients to achieve high performance through insights from data - insights that inform better decisions and strengthen customer relationships. From strategy to execution, Accenture works with organizations to develop analytic capabilities - from accessing and reporting on data to predictive modelling - to outperform the competition About Comms & Media practice: Comms & Media (C&M) is one of the Industry Practices within Accentures S&C Global Network team. It focuses in serving clients across specific Industries Communications, Media & Entertainment. Communications Focuses primarily on industries related with telecommunications and information & communication technology (ICT). This team serves most of the worlds leading wireline, wireless, cable and satellite communications and service providers Media & Entertainment Focuses on industries like broadcast, entertainment, print and publishing Globally, Accenture Comms & Media practice works to develop value growth strategies for its clients and infuse AI & GenAI to help deliver top their business imperatives i.e., revenue growth & cost reduction. From multi-year Data & AI transformation projects to shorter more agile engagements, we have a rapidly expanding portfolio of hyper-growth clients and an increasing footprint with next-gen solutions and industry practices. Roles & Responsibilities: A Telco domain experienced and data science consultant is responsible to help the clients with designing & delivering AI solutions. He/she should be strong in Telco domain, AI fundamentals and should have good hands-on experience working with the following: Ability to work with large data sets and present conclusions to key stakeholders; Data management using SQL. Propose solutions to the client based on gap analysis for the existing Telco platforms that can generate long term & sustainable value to the client. Gather business requirements from client stakeholders via interactions like interviews and workshops with all stakeholders Track down and read all previous information on the problem or issue in question. Explore obvious and known avenues thoroughly. Ask a series of probing questions to get to the root of a problem. Ability to understand the as-is process; understand issues with the processes which can be resolved either through Data & AI or process solutions and design detail level to-be state Understand customer needs and identify/translate them to business requirements (business requirement definition), business process flows and functional requirements and be able to inform the best approach to the problem. Adopt a clear and systematic approach to complex issues (i.e. A leads to B leads to C). Analyze relationships between several parts of a problem or situation. Anticipate obstacles and identify a critical path for a project. Independently able to deliver products and services that empower clients to implement effective solutions. Makes specific changes and improvements to processes or own work to achieve more. Work with other team members and make deliberate efforts to keep others up to date. Establish a consistent and collaborative presence with clients and act as the primary point of contact for assigned clients; escalate, track, and solve client issues. Partner with clients to understand end clients business goals, marketing objectives, and competitive constraints. Storytelling Crunch the data & numbers to craft a story to be presented to senior client stakeholders. Professional & Technical Skills: Overall 10+ years of experience in Data Science & at least 5 years in Telecom Analytics Masters (MBA/MSc/MTech) from a Tier 1/Tier 2 and Engineering from Tier 1 school Demonstrated experience in solving real-world data problems through Data & AI Direct onsite experience (i.e., experience of facing client inside client offices in India or abroad) is mandatory. Please note we are looking for client facing roles. Proficiency with data mining, mathematics, and statistical analysis Advanced pattern recognition and predictive modeling experience; knowledge of Advanced analytical fields in text mining, Image recognition, video analytics, IoT etc. Execution level understanding of econometric/statistical modeling packages Traditional techniques like Linear/logistic regression, multivariate statistical analysis, time series techniques, fixed/Random effect modelling. Machine learning techniques like - Random Forest, Gradient Boosting, XG boost, decision trees, clustering etc. Knowledge of Deep learning modeling techniques like RNN, CNN etc. Experience using digital & statistical modeling software (one or more) Python, R, PySpark, SQL, BigQuery, Vertex AI Proficient in Excel, MS word, Power point, and corporate soft skills Knowledge of Dashboard creation platforms Excel, tableau, Power BI etc. Excellent written and oral communication skills with ability to clearly communicate ideas and results to non-technical stakeholders. Strong analytical, problem-solving skills and good communication skills Self-Starter with ability to work independently across multiple projects and set priorities Strong team player Proactive and solution oriented, able to guide junior team members. Execution knowledge of optimization techniques is a good-to-have Exact optimization Linear, Non-linear optimization techniques Evolutionary optimization Both population and search-based algorithms Cloud platform Certification, experience in Computer Vision are good-to-haves Qualification Experience: Overall 10+ years of experience in Data Science & at least 5 years in Telecom Educational Qualification: Masters (MBA/MSc/MTech) from a Tier 1/Tier 2 and Engineering from Tier 1 school

Job Title - S&C Global Network - AI - CMT - Consultant Data Science Management Level: 9-Team Lead/Consultant Location: Hyderabad, HDC2A Must-have skills: CMT Analytics Good to have skills: Ability to leverage design thinking, business process optimization, and stakeholder management skills. Job Summary : This role involves driving strategic initiatives, managing business transformations, and leveraging industry expertise to create value-driven solutions. Roles & Responsibilities: Provide strategic advisory services, conduct market research, and develop data-driven recommendations to enhance business performance. Responsibilities/Authorities A Telco domain experienced and data science consultant is responsible to help the clients with designing & delivering AI solutions. He/she should be strong in Telco domain, AI fundamentals and should have good hands-on experience working with the following: Ability to work with large data sets and present conclusions to key stakeholders; Data management using SQL. Propose solutions to the client based on gap analysis for the existing Telco platforms that can generate long term & sustainable value to the client. Gather business requirements from client stakeholders via interactions like interviews and workshops with all stakeholders Track down and read all previous information on the problem or issue in question. Explore obvious and known avenues thoroughly. Ask a series of probing questions to get to the root of a problem. Ability to understand the as-is process; understand issues with the processes which can be resolved either through Data & AI or process solutions and design detail level to-be state Understand customer needs and identify/translate them to business requirements (business requirement definition), business process flows and functional requirements and be able to inform the best approach to the problem. Adopt a clear and systematic approach to complex issues (i.e. A leads to B leads to C). Analyze relationships between several parts of a problem or situation. Anticipate obstacles and identify a critical path for a project. Independently able to deliver products and services that empower clients to implement effective solutions. Makes specific changes and improvements to processes or own work to achieve more. Work with other team members and make deliberate efforts to keep others up to date. Establish a consistent and collaborative presence with clients and act as the primary point of contact for assigned clients; escalate, track, and solve client issues. Partner with clients to understand end clients business goals, marketing objectives, and competitive constraints. Storytelling Crunch the data & numbers to craft a story to be presented to senior client stakeholders. Should be able to travel or relocate to Japan as per business requirement. Professional & Technical Skills: - Relevant experience in the required domain. - Strong analytical, problem-solving, and communication skills. - Ability to work in a fast-paced, dynamic environment. Demonstrated experience in solving real-world data problems through Data & AI Direct onsite experience (i.e., experience of facing client inside client offices in India or abroad) is mandatory. Please note we are looking for client facing roles. Proficiency with data mining, mathematics, and statistical analysis Advanced pattern recognition and predictive modeling experience; knowledge of Advanced analytical fields in text mining, Image recognition, video analytics, IoT etc. Execution level understanding of econometric/statistical modeling packages Traditional techniques like Linear/logistic regression, multivariate statistical analysis, time series techniques, fixed/Random effect modelling. Machine learning techniques like - Random Forest, Gradient Boosting, XG boost, decision trees, clustering etc. Knowledge of Deep learning modeling techniques like RNN, CNN etc. Experience using digital & statistical modeling software (one or more) Python, R, PySpark, SQL, BigQuery, Vertex AI Proficient in Excel, MS word, Power point, and corporate soft skills Knowledge of Dashboard creation platforms Excel, tableau, Power BI etc. Excellent written and oral communication skills with ability to clearly communicate ideas and results to non-technical stakeholders. Strong analytical, problem-solving skills and good communication skills Self-Starter with ability to work independently across multiple projects and set priorities Strong team player Proactive and solution oriented, able to guide junior team members. Execution knowledge of optimization techniques is a good-to-have Exact optimization Linear, Non-linear optimization techniques Evolutionary optimization Both population and search-based algorithms Cloud platform Certification, experience in Computer Vision are good-to-haves Additional Information: - Opportunity to work on innovative projects. - Career growth and leadership exposure. About Our Company | Accenture Qualification Experience: 8-10Years Educational Qualification: Any Degree

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

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: 2-4 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 Advanced degree strongly preferred

We are seeking a talented and motivated Data Scientist with 1-3 years of experience to join our Data Science team. If you have a strong passion for data science, expertise in machine learning, and experience working with large-scale datasets, we want to hear from you. As a Data Scientist at RevX, you will play a crucial role in developing and implementing machine learning models to drive business impact. You will work closely with teams across data science, engineering, product, and campaign management to build predictive models, optimize algorithms, and deliver actionable insights. Your work will directly influence business strategy, product development, and campaign optimization. Major Responsibilities: Develop and implement machine learning models, particularly neural networks, decision trees, random forests, and XGBoost, to solve complex business problems. Work on deep learning models and other advanced techniques to enhance predictive accuracy and model performance. Analyze and interpret large, complex datasets using Python, SQL, and big data technologies to derive meaningful insights. Collaborate with cross-functional teams to design, build, and deploy end-to-end data science solutions, including data pipelines and model deployment frameworks. Utilize advanced statistical techniques and machine learning methodologies to optimize business strategies and outcomes. Evaluate and improve model performance, calibration, and deployment strategies for real-time applications. Perform clustering, segmentation, and other unsupervised learning techniques to discover patterns in large datasets. Conduct A/B testing and other experimental designs to validate model performance and business strategies. Create and maintain data visualizations and dashboards using tools such as matplotlib, seaborn, Grafana, and Looker to communicate findings. Provide technical expertise in handling big data, data warehousing, and cloud-based platforms like Google Cloud Platform (GCP). Required Experience/Skills: Bachelors or Masters degree in Data Science, Computer Science, Statistics, Mathematics, or a related field. 1-3 years of experience in data science or machine learning roles. Strong proficiency in Python for machine learning, data analysis, and deep learning applications. Experience in developing, deploying, and monitoring machine learning models, particularly neural networks, and other advanced algorithms. Expertise in handling big data technologies, with experience in tools such as BigQuery and cloud platforms (GCP preferred). Advanced SQL skills for data querying and manipulation from large datasets. Experience in data visualization tools like matplotlib, seaborn, Grafana, and Looker. Strong understanding of A/B testing, statistical tests, experimental design, and methodologies. Experience in clustering, segmentation, and other unsupervised learning techniques. Strong problem-solving skills and the ability to work with complex datasets and machine learning pipelines. Excellent communication skills, with the ability to explain complex technical concepts to non-technical stakeholders. Preferred Skills: Experience with deep learning frameworks such as TensorFlow or PyTorch. Familiarity with data warehousing concepts and big data tools. Knowledge of MLOps practices, including model deployment, monitoring, and management. Experience with business intelligence tools and creating data-driven dashboards. Understanding of reinforcement learning, natural language processing (NLP), or other advanced AI techniques. Education: Bachelor of Engineering or similar degree from any reputed University.

Research and Problem-Solving: Identify and frame business problems, conduct exploratory data analysis, and propose innovative data science solutions tailored to business needs. Leadership & Communication: Serve as a technical referent for the research team, driving high-impact, high-visibility initiatives. Effectively communicate complex scientific concepts to senior stakeholders, ensuring insights are actionable for both technical and non-technical audiences. Mentor and develop scientists within the team, fostering growth and technical excellence. Algorithm Development: Design, optimize, and implement advanced machine learning algorithms, including neural networks, ensemble models (XGBoost, random forests), and clustering techniques. End-to-End Project Ownership: Lead the development, deployment, and monitoring of machine learning models and data pipelines for large-scale applications. Model Optimization and Scalability: Focus on optimizing algorithms for performance and scalability, ensuring robust, well-calibrated models suitable for real-time environments. A/B Testing and Validation: Design and execute experiments, including A/B testing, to validate model effectiveness and business impat. Big Data Handling: Leverage tools like BigQuery, advanced SQL, and cloud platforms (e.g., GCP) to process and analyze large datasets. Collaboration and Mentorship: Work closely with engineering, product, and campaign management teams, while mentoring junior data scientists in best practices and advanced techniques. Data Visualization: Create impactful visualizations using tools like matplotlib, seaborn, Looker, and Grafana to communicate insights effectively to stakeholders. Required Experience/Skills 5–8 years of hands-on experience in data science or machine learning roles. 2+ years leading data science projects in AdTech Strong hands-on skills in Advanced Statistics, Machine Learning, and Deep Learning. Demonstrated ability to implement and optimize neural networks and other advanced ML models. Proficiency in Python for developing machine learning models, with a strong grasp of TensorFlow or PyTorch. Expertise handling large datasets using advanced SQL and big data tools like BigQuery In-depth knowledge of MLOps pipelines, from data preprocessing to deployment and monitoring. Strong background in A/B testing, statistical analysis, and experimental design. Proven capability in clustering, segmentation, and unsupervised learning methods. Strong problem-solving and analytical skills with a focus on delivering business value. Education: A Master’s in Data Science, Computer Science, Mathematics, Statistics, or a related field is preferred. A Bachelor's degree with exceptional experience will also be considered.

Career Area: Technology, Digital and Data : Your Work Shapes the World at Caterpillar Inc. When you join Caterpillar, you're joining a global team who cares not just about the work we do - but also about each other. We are the makers, problem solvers, and future world builders who are creating stronger, more sustainable communities. We don't just talk about progress and innovation here - we make it happen, with our customers, where we work and live. Together, we are building a better world, so we can all enjoy living in it. Your Impact Shapes the World at Caterpillar Inc When you join Caterpillar, you're joining a global team who cares not just about the work we do - but also about each other. We are the makers, problem solvers and future world builders who are creating stronger, more sustainable communities. We don't just talk about progress and innovation here - we make it happen, with our customers, where we work and live. Together, we are building a better world, so we can all enjoy living in it. Job Summary Caterpillar is seeking a skilled Senior Data Scientist to join our team to act as a champion for our Digital Finance-Disruptive Technology Team within the Global Finance Services Division . The incumbent will leverage internal data and advanced analytics to solve business problems. The preference for this role is to be based out of Whitefield Office, Bangalore, India What you will do As a Senior Data Scientist, you will work in a team environment with a group of data scientists and software developers to support the development, integration, and enhancement of Caterpillar's analytics, AI, and Generative AI projects and products. Gain an understanding of Caterpillar s business and accounting practices, systems, and procedures. Developing ML/AI/GenAI models and solutions. Performing data gathering, data mining, and data processing on large volumes of data; creating appropriate data models. Demonstrating a breadth of knowledge in the application of ML/AI/GenAI and statistical methods and/or digital methods to solve business problems. Conducting research on data model optimization and algorithms to improve the effectiveness and accuracy of data analyses. Participating on 1-3 primary projects concurrently. Having a strong focus on continual learning in the Analytics field. Reporting and presenting team results. The Data Scientist will develop good networks within the technical community to enable them to collaborate on technical solutions, obtain resources and cooperation needed, and remove roadblocks so that they can ensure the success of their projects. What you will have Typically, a Bachelor's, Master s, or Ph.D. degree, preferably in statistics, economics, mathematics, or a similar field with quantitative coursework. 5+ Years of Professional Experience with the ability to deliver data science products with almost no technical guidance from others. The ability to provide technical guidance to less experience data science team members. Experience with data analysis and statistical methods such as regression, hypothesis testing, ANOVA, statistical process control, etc. Practical applications of machine learning techniques such as clustering, logistic regression, CART, random forests, SVM, or neural networks. Technical and problem-solving skills with evidence of continuous learning in the analytics field. Breadth and depth of knowledge in the application of statistical and/or digital methods to solve business problems. Experience with projects connecting data from various business domains and providing forecasts and insights to run the business profitably. Working knowledge of cloud technologies (AWS, Azure, Google Cloud, etc.). Working knowledge of version control/repositories such as GitHub. Experience operating in an Agile environment. Initiative to research and apply new methods and digital technologies to exceed customer expectations. Must demonstrate strong initiative, interpersonal skills, and the ability to communicate effectively. Must be comfortable working in MS Office, and industry standard statistics, analytics, and data visualization packages. Experience mechanizing manual data collection processes using Snowflake to enhance indicative data to generate quicker and more granular insights. Tables/Process could be leveraged by the Forecasting and Financial Analysis Reporting groups. Experience with writing fast and memory-efficient code as well as with various types of parallel processingthreading, multi-core/forking, multiple session, and cluster computing. Skills desired: Analytical Thinking Extensive knowledge of techniques and tools for effective analysis; ability to determine the root cause of problems and create alternative solutions that resolve these issues. GenAI / AI / Machine Learning Extensive experience and knowledge of the principles, technologies, and algorithms of GenAI, AI, and machine learning; ability to develop, implement, and deliver related systems, products, and services. Statistics Extensive knowledge of statistical tools, processes, and practices to describe results on measurable scales; ability to use statistical tools and processes to assist in making business decisions. Programming Languages Extensive experience in applying Python (NumPy, SciPy, Pandas, etc.) to solve business challenges; ability to use tools, techniques, and platforms to write and modify programming languages. Information Processing Extensive experience in processing large quantities of detailed information with high levels of accuracy. Databases Extensive knowledge in writing, debugging, and implementing complex queries involving multiple tables or databases. Presentation Skills Strong presentation and communication skills. What you will get: Work Life Harmony Earned and medical leave. Flexible work arrangements Relocation assistance Holistic Development Personal and professional development through Caterpillar s employee resource groups across the globe Career developments opportunities with global prospects Health and Wellness Medical coverage -Medical, life and personal accident coverage Employee mental wellness assistance program Financial Wellness Employee investment plan Pay for performance -Annual incentive Bonus plan. Additional Information: Caterpillar is not currently hiring individuals for this position who now or in the future require sponsorship for employment visa status; however, as a global company, Caterpillar offers many job opportunities outside of the U.S. which can be found through our employment website at www.caterpillar.com/careers Posting Dates: January 16, 2025 - January 29, 2025 Caterpillar is an Equal Opportunity Employer (EEO). Not ready to applyJoin our Talent Community .

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.

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: 2-4 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

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 is 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

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

Role & responsibilities Requires 5-8 years of proven experience in banking/payments/other domains Strong experience in developing Machine Learning models, Python & SQL Experience working with pre-trained models, awareness of state-of-art in embeddings and applicability for use cases Detailed oriented with a proactive mindset towards problem-solving Excellent communication and presentation skills with the ability to convey complex information clearly and concisely Demonstrated ability to engage with client stake holders

Optum is a global organization that delivers care, aided by technology to help millions of people live healthier lives. The work you do with our team will directly improve health outcomes by connecting people with the care, pharmacy benefits, data and resources they need to feel their best. Here, you will find a culture guided by diversity and inclusion, talented peers, comprehensive benefits and career development opportunities. Come make an impact on the communities we serve as you help us advance health equity on a global scale. Join us to start Caring. Connecting. Growing together Primary Responsibilities Applying knowledge of statistics, machine learning, programming, data modeling, simulation, and advanced mathematics to recognize patterns, identify opportunities, pose business questions, and make valuable discoveries leading to prototype development and product improvement Data mining using state-of-the-art methods Enhancing data collection procedures to include information that is relevant for building analytic systems Processing, cleansing, and verifying the integrity of data used for analysis Doing ad-hoc analysis and presenting results in a clear manner Working with analytics and statistical software such as SQL, R, Python, Hadoop and others to perform analysis and interpret data Work with stakeholders to identify opportunities for leveraging company data to drive business solutions. Mine and analyze data from company databases to drive optimization and improvement of product development, marketing techniques and business strategies Assess the effectiveness and accuracy of new data sources and data gathering techniques Develop custom data models and algorithms to apply to data sets Use predictive modeling to increase and optimize customer experiences, revenue generation, ad targeting and other business outcomes Develop company A/B testing framework and test model quality Coordinate with different functional teams to implement models and monitor outcomes Develop processes and tools to monitor and analyze model performance and data accuracy 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 regards 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 Graduate degree or equivalent experience 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 Experience querying databases and using statistical computer languagesR, Python, SLQ, etc. Experience using web servicesRedshift, S3, Spark, DigitalOcean, etc. Experience creating and using advanced machine learning algorithms and statisticsregression, simulation, scenario analysis, modeling, clustering, decision trees, neural networks, etc. Experience with distributed data/computing toolsMap/Reduce, Hadoop, Hive, Spark, Gurobi, MySQL, etc. Experience visualizing/presenting data for stakeholders usingPeriscope, Business Objects, D3, ggplot, etc. Solid problem solving skills with an emphasis on product development 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 Proven excellent written and verbal communication skills for coordinating across teams A drive to learn and master new technologies and techniques Coding knowledge and experience with several languagesC, C++, Java, JavaScript, etc. Knowledge and experience in statistical and data mining techniquesGLM/Regression, Random Forest, Boosting, Trees, text mining, social network analysis, k-NN, Naive Bayes, SVM, etc. At UnitedHealth Group, our mission is to help people live healthier lives and make the health system work better for everyone. We believe everyone - of every race, gender, sexuality, age, location and income - deserves the opportunity to live their healthiest life. Today, however, there are still far too many barriers to good health which are disproportionately experienced by people of color, historically marginalized groups and those with lower incomes. We are committed to mitigating our impact on the environment and enabling and delivering equitable care that addresses health disparities and improves health outcomes - an enterprise priority reflected in our mission.

Strong proficiency in Python and/or R for data analysis and modeling. Advanced SQL skills for data querying and transformation. Hands-on experience with machine learning frameworks (e.g., scikit-learn, TensorFlow, PyTorch). Solid understanding of statistics, hypothesis testing, regression analysis, and data mining. Familiarity with cloud platforms (AWS, Azure, or GCP) and big data tools (Spark, Hadoop) is a plus. Excellent problem-solving skills and attention to detail.

Job Title - Data Scientist and Analytics Level 7:Manager Ind & Func AI Decision Science Manager S&C Management Level:07 - Manager Location Bangalore/Gurgaon/Hyderabad/Mumbai Must have skills: Technical (Python, SQL, ML and AI), Functional (Data Scientist and B2B Analytics preferably in Telco and S&P industries) Good to have skillsGEN AI, Agentic AI, cloud (AWS/Azure, GCP) Job Summary : About Global Network Data & AI:- Accenture Strategy & Consulting Global Network - Data & AI practice help our clients grow their business in entirely new ways. Analytics enables our clients to achieve high performance through insights from data - insights that inform better decisions and strengthen customer relationships. From strategy to execution, Accenture works with organizations to develop analytic capabilities - from accessing and reporting on data to predictive modelling - to outperform the competition About Comms & Media practice The Accenture Center for Data and Insights (CDI) team helps businesses integrate data and AI into their operations to drive innovation and business growth by designing and implementing data strategies, generating actionable insights from data, and enabling clients to make informed decisions. In CDI, we leverage AI (predictive + generative), analytics, and automation to build innovative and practical solutions, tools and capabilities. The team is also working on building and socializing a Marketplace to democratize data and AI solutions within Accenture and for clients. Globally, CDI practice works across industry to develop value growth strategies for its clients and infuse AI & GenAI to help deliver top their business imperatives i.e., revenue growth & cost reduction. From multi-year Data & AI transformation projects to shorter more agile engagements, we have a rapidly expanding portfolio of hyper-growth clients and an increasing footprint with next-gen solutions and industry practices. Roles & Responsibilities: Experienced in Analytics in B2B domain. Responsible to help the clients with designing & delivering AI/ML solutions. He/she should be strong in Telco and S&P domain, AI fundamentals and should have good hands-on experience working with the following: Ability to work with large data sets and present conclusions to key stakeholders; Data management using SQL. Data manipulation and aggregation using Python. Propensity modeling using various ML algorithms. Text mining using NLP/AI techniques Propose solutions to the client based on gap analysis for the existing Telco platforms that can generate long term & sustainable value to the client. Gather business requirements from client stakeholders via interactions like interviews and workshops with all stakeholders Track down and read all previous information on the problem or issue in question. Explore obvious and known avenues thoroughly. Ask a series of probing questions to get to the root of a problem. Ability to understand the as-is process; understand issues with the processes which can be resolved either through Data & AI or process solutions and design detail level to-be state Understand customer needs and identify/translate them to business requirements (business requirement definition), business process flows and functional requirements and be able to inform the best approach to the problem. Adopt a clear and systematic approach to complex issues (i.e. A leads to B leads to C). Analyze relationships between several parts of a problem or situation. Anticipate obstacles and identify a critical path for a project. Independently able to deliver products and services that empower clients to implement effective solutions. Makes specific changes and improvements to processes or own work to achieve more. Work with other team members and make deliberate efforts to keep others up to date. Establish a consistent and collaborative presence with clients and act as the primary point of contact for assigned clients; escalate, track, and solve client issues. Partner with clients to understand end clients' business goals, marketing objectives, and competitive constraints. Storytelling Crunch the data & numbers to craft a story to be presented to senior client stakeholders. Professional & Technical Skills: Overall 10+ years of experience in Data Science B.Tech Engineering from Tier 1 school or Msc in Statistics/Data Science from a Tier 1/Tier 2 Demonstrated experience in solving real-world data problems through Data & AI Direct onsite experience (i.e., experience of facing client inside client offices in India or abroad) is mandatory. Please note we are looking for client facing roles. Proficiency with data mining, mathematics, and statistical analysis Advanced pattern recognition and predictive modeling experience; knowledge of Advanced analytical fields in text mining, Image recognition, video analytics, IoT etc. Execution level understanding of econometric/statistical modeling packages Traditional techniques like Linear/logistic regression, multivariate statistical analysis, time series techniques, fixed/Random effect modelling. Machine learning techniques like - Random Forest, Gradient Boosting, XG boost, decision trees, clustering etc. Knowledge of Deep learning modeling techniques like RNN, CNN etc. Experience using digital & statistical modeling software Python (must), R, PySpark, SQL (must), BigQuery, Vertex AI Proficient in Excel, MS word, Power point, and corporate soft skills Knowledge of Dashboard creation platforms Excel, tableau, Power BI etc. Excellent written and oral communication skills with ability to clearly communicate ideas and results to non-technical stakeholders. Strong analytical, problem-solving skills and good communication skills Self-Starter with ability to work independently across multiple projects and set priorities Strong team player Proactive and solution oriented, able to guide junior team members. Execution knowledge of optimization techniques is a good-to-have Exact optimization Linear, Non-linear optimization techniques Evolutionary optimization Both population and search-based algorithms Cloud platform Certification, experience in Computer Vision are good-to-haves Qualifications Experience: B.Tech Engineering from Tier 1 school or Msc in Statistics/Data Science from a Tier 1/Tier 2 Educational Qualification: B.tech or MSC in Statistics and Data Science

Required Skills & Qualifications: 3-5 years of hands-on experience in data science, machine learning, and statistical modeling. Strong expertise in time series forecasting (ARIMA, XGBoost, RandomForest, TFT, NHITS, etc.) and familiarity with deep learning frameworks (TensorFlow, PyTorch). Excellent programming skills in Python (preferred), with proficiency in libraries such as NumPy, Pandas, scikit-learn, and visualization tools (Matplotlib, Seaborn, Plotly). Solid conceptual understanding of machine learning algorithms, deep learning architectures, and statistical methods. Experience with data preprocessing, feature engineering, and model evaluation. Ability to learn quickly and adapt to new technologies, tools, and methodologies. Strong problem-solving skills and a keen attention to detail. Excellent communication and presentation skills. Preferred Qualifications: Experience with cloud platforms and MLOps tools. Exposure to big data technologies (Spark, Hadoop) is a plus. Masters degree in Computer Science, Statistics, Mathematics, or a related field.

Job description Job description Job Summary: We are looking for a results-driven and innovative Data Scientist with 46 years of experience in data analysis, machine learning, and product optimization. The ideal candidate will have a strong foundation in Python, SQL, and cloud services, along with practical exposure to GenAI, LLMs, and MLOps frameworks. You will be responsible for building scalable data pipelines, developing machine learning models, and solving real-world business problems with data-driven solutions. Key Responsibilities: Design and deploy LLM-powered solutions (e.g., RAG, LangChain, Vector DB) to enhance business processes. Build and fine-tune traditional ML models (Random Forest, Decision Trees) for predictive analytics. Optimize LLM performance using LoRA fine-tuning and post-training quantization. Develop and deploy containerized AI applications using Docker and FastAPI. Collaborate with agents like CrewAI and LangSmith to automate document processing and data extraction workflows. Implement Python & SQL-based ETL pipelines for real-time data ingestion. Design dashboards and KPI monitoring tools using Metabase to enable data-driven decision-making. Create data consumption triggers and automate reporting for international stakeholders. Moderate large-scale live virtual data science classes and provide operational support. Required Skills: Programming: Python, SQL, FastAPI ML & AI: Random Forest, Decision Trees, Clustering, PCA, DL, NLP, Transformers, Gen AI Frameworks/Tools: LangChain, MLflow, Kubeflow, CrewAI, LangSmith DevOps: Docker, Git Databases: MySQL, PostgreSQL, MongoDB Cloud: AWS (S3, EC2) Visualization: Metabase Other: Experience with LLM fine-tuning and quantization Role & responsibilitiesRole & responsibilities Preferred candidate profile

Job Title - Data Scientist and Analytics Level 9:Consultant Ind & Func AI Decision Science Consultant S&C Management Level:09 - Consultant Location Bangalore/Gurgaon/Hyderabad/Mumbai Must have skills: Technical (Python, SQL, ML and AI), Functional (Data Scientist and B2B Analytics preferably in Telco and S&P industries) Good to have skills GEN AI, Agentic AI, cloud (AWS/Azure, GCP) Job Summary : About Global Network Data & AI:- Accenture Strategy & Consulting Global Network - Data & AI practice help our clients grow their business in entirely new ways. Analytics enables our clients to achieve high performance through insights from data - insights that inform better decisions and strengthen customer relationships. From strategy to execution, Accenture works with organizations to develop analytic capabilities - from accessing and reporting on data to predictive modelling - to outperform the competition About Comms & Media practice: The Accenture Center for Data and Insights (CDI) team helps businesses integrate data and AI into their operations to drive innovation and business growth by designing and implementing data strategies, generating actionable insights from data, and enabling clients to make informed decisions. In CDI, we leverage AI (predictive + generative), analytics, and automation to build innovative and practical solutions, tools and capabilities. The team is also working on building and socializing a Marketplace to democratize data and AI solutions within Accenture and for clients. Globally, CDI practice works across industry to develop value growth strategies for its clients and infuse AI & GenAI to help deliver top their business imperatives i.e., revenue growth & cost reduction. From multi-year Data & AI transformation projects to shorter more agile engagements, we have a rapidly expanding portfolio of hyper-growth clients and an increasing footprint with next-gen solutions and industry practices. Roles & Responsibilities: Experienced in Analytics in B2B domain. Responsible to help the clients with designing & delivering AI/ML solutions. He/she should be strong in Telco and S&P domain, AI fundamentals and should have good hands-on experience working with the following: Ability to work with large data sets and present conclusions to key stakeholders; Data management using SQL. Data manipulation and aggregation using Python. Propensity modeling using various ML algorithms. Text mining using NLP/AI techniques Propose solutions to the client based on gap analysis for the existing Telco platforms that can generate long term & sustainable value to the client. Gather business requirements from client stakeholders via interactions like interviews and workshops with all stakeholders Track down and read all previous information on the problem or issue in question. Explore obvious and known avenues thoroughly. Ask a series of probing questions to get to the root of a problem. Ability to understand the as-is process; understand issues with the processes which can be resolved either through Data & AI or process solutions and design detail level to-be state Understand customer needs and identify/translate them to business requirements (business requirement definition), business process flows and functional requirements and be able to inform the best approach to the problem. Adopt a clear and systematic approach to complex issues (i.e. A leads to B leads to C). Analyze relationships between several parts of a problem or situation. Anticipate obstacles and identify a critical path for a project. Independently able to deliver products and services that empower clients to implement effective solutions. Makes specific changes and improvements to processes or own work to achieve more. Work with other team members and make deliberate efforts to keep others up to date. Establish a consistent and collaborative presence with clients and act as the primary point of contact for assigned clients; escalate, track, and solve client issues. Partner with clients to understand end clients' business goals, marketing objectives, and competitive constraints. Storytelling Crunch the data & numbers to craft a story to be presented to senior client stakeholders. Professional & Technical Skills: Overall 8 years of experience in Data Science B.Tech Engineering from Tier 1 school or Msc in Statistics/Data Science from a Tier 1/Tier 2 Demonstrated experience in solving real-world data problems through Data & AI Direct onsite experience (i.e., experience of facing client inside client offices in India or abroad) is mandatory. Please note we are looking for client facing roles. Proficiency with data mining, mathematics, and statistical analysis Advanced pattern recognition and predictive modeling experience; knowledge of Advanced analytical fields in text mining, Image recognition, video analytics, IoT etc. Execution level understanding of econometric/statistical modeling packages Traditional techniques like Linear/logistic regression, multivariate statistical analysis, time series techniques, fixed/Random effect modelling. Machine learning techniques like - Random Forest, Gradient Boosting, XG boost, decision trees, clustering etc. Knowledge of Deep learning modeling techniques like RNN, CNN etc. Experience using digital & statistical modeling software Python (must), R, PySpark, SQL (must), BigQuery, Vertex AI Proficient in Excel, MS word, Power point, and corporate soft skills Knowledge of Dashboard creation platforms Excel, tableau, Power BI etc. Excellent written and oral communication skills with ability to clearly communicate ideas and results to non-technical stakeholders. Strong analytical, problem-solving skills and good communication skills Self-Starter with ability to work independently across multiple projects and set priorities Strong team player Proactive and solution oriented, able to guide junior team members. Execution knowledge of optimization techniques is a good-to-have Exact optimization Linear, Non-linear optimization techniques Evolutionary optimization Both population and search-based algorithms Cloud platform Certification, experience in Computer Vision are good-to-haves Qualifications Experience: B.Tech Engineering from Tier 1 school or Msc in Statistics/Data Science from a Tier 1/Tier 2 Educational Qualification: B.tech or MSC in Statistics and Data Science

Key Responsibilities: Leverage traditional machine learning techniques (decision trees, random forests, SVM, logistic regression) to build predictive models. Analyze complex datasets to identify key trends and provide data-driven insights for business decisions. Partner with cross-functional teams to understand business needs and translate them into effective ML solutions. Rigorously evaluate and optimize models for accuracy and real-world performance. Apply statistical and mathematical principles to enhance analytical outcomes. Communicate findings and model insights to both technical and non-technical stakeholders. Desired Skills and Qualifications: Deep understanding of traditional machine learning algorithms (decision trees, clustering, Naive Bayes, SVM, etc.). Strong proficiency in mathematics and statistics (linear algebra, probability, statistical inference). Proven ability to translate business problems into analytical frameworks and actionable insights. Expertise in data processing, cleaning, and feature engineering using Python (pandas, NumPy). Hands-on experience building and deploying ML models using Python and libraries like scikit-learn. Excellent analytical, problem-solving, and critical thinking skills. Strong communication and collaboration skills to effectively convey technical results. Familiarity with ML tools and frameworks (Scikit-learn, XGBoost, LightGBM). Experience with model evaluation, validation, and optimization techniques. Business acumen and the ability to apply ML to solve real-world business challenges. Preferred Qualifications: Bachelors or Masters degree in Data Science, Statistics, Mathematics, Computer Science, or a related quantitative field. 3+ years of experience as a Data Scientist with a focus on machine learning. Demonstrated experience in driving business decisions through data analysis and modeling. Familiarity with cloud platforms (AWS, Azure, GCP) for data science workflows.

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.