5 Decision Trees Jobs

AI/ML Engineer to join our fast-growing. The ideal candidate will be responsible for designing, developing, and deploying machine learning models and AI-driven applications that deliver business value and customer impact. Key Responsibilities Research and develop machine learning models using supervised, unsupervised, or reinforcement learning techniques. Deploy models into production using MLOps best practices (e.g., containerization, CI/CD, model monitoring). Work on datasets involving structured and unstructured data (e.g., text, image, video, time-series). Collaborate with data engineers, product managers, and other stakeholders to define problem statements and deliver solutions. Continuously improve model performance and scalability using experimentation and model evaluation techniques. Stay updated with the latest trends and breakthroughs in AI/ML (e.g., LLMs, transformers, generative AI). Required Qualifications Bachelors/Masters/Ph.D. in Computer Science, Artificial Intelligence, Data Science, or a related field. Strong coding skills in Python (must), with knowledge of libraries like scikit-learn, PyTorch, TensorFlow, Hugging Face, OpenCV , etc. Experience building and tuning ML models from scratch. Solid understanding of ML lifecycle, from data preprocessing to model deployment. Hands-on with SQL , data manipulation tools ( Pandas , NumPy ), and visualization tools ( Matplotlib , Seaborn , Plotly ). Experience with cloud platforms (AWS/GCP/Azure) and tools like Docker, Kubernetes, MLflow is a plus. Preferred Skills Exposure to NLP , LLMs , chatbots , speech processing , or computer vision applications. Experience with GenAI models like GPT, DALL•E, or stable diffusion. Knowledge of prompt engineering, vector databases (like FAISS, Pinecone ), or LangChain is a bonus. Publications or participation in AI/ML competitions (e.g., Kaggle, NeurIPS, CVPR) is a strong plus.

Overview Provide advanced analytics support for the LATAM Sector in the Insights Services Center; a part of the broader Global Business Services function in Hyderabad, India. This role will help to enable accelerated growth for PepsiCo by developing custom descriptive analytics approaches for LATAM to drive deeper understanding of business performance drivers both at the National / Regional / State /City level. Primary responsibilities include developing/enhancing statistical models to address key business questions associated with Growth Driver Modeling, Pricing, Assortment, Market Structure, Innovation Forecasting, and Category Growth Forecasts, Portfolio growth model, Ambition related assignments for the key markets of LATAM. Additionally, this role will also support the consumer insight team by collating learnings from a variety of sources, to help inform the development of future insights strategies for various brands with in Bevareages / Snacks . The role will have short-term responsibilities for knowledge transfer from the Vendors and effectively establishing business process and communication methods with teams they support; both are crucial requirements to enabling the organization to deliver answers to on-going business questions Responsibilities Functional Responsibilities: Support delivery of descriptive and predictive analytics as defined by the SLA (Service Level Agreement) within the LATAM Business Service Service Center Execute deep descriptive analytics of business performance and drivers to supplement standard reporting and inform data-driven decisions Identify, assess, and visualize key market share drivers for LATAM Categories, as a growth catalyst to prioritize and enable brand planning across portfolio Support LATAM regions annual SKU optimization process for the portfolio; analyzing impact by channel, customers and region as needed based on HQ delivered recommendations & targets Advise and share Advanced Analytics models and best practices with Regional Category Managers to leverage and build Advanced Analytics capability. Develop, maintain, and apply statistical models to business questions - including forecasting, price sensitivities/corridors, drivers analysis, market structure, etc. Forecast market growth leveraging (PGM an internal tool) on an annual basis to inform PEPs long-term expectations for growth Collate and format consumer learnings from custom insight outputs, sales performace reporting, industry periodicals, and social listening resources, etc to help inform and develop future consumer insights strategies Provide responses to ad-hoc follow-ups when double-click (additional questions) required with tables/charts for relevant data Support relationships with the key end-user stakeholders in LATAM and region offices Own flawless execution of analytics exercises Responsible for managing multiple priorities; being able to manage deadlines and deliverables Lead communication with Business Partners and potentially end-users on matters such as available capacity, changes of scope of existing projects and planning of future projects Deliver outputs in line with the agreed timelines and formats Flag and monitor any business risks related to delivering the requested outputs Partner with stakeholders and service center leadership to develop and finetune internal COE processes (work-flow mapping, pain-points and bottlenecks management) both related to service delivery and internal center operations Improve existing processes based on frequent Business Partner & end-user feedback loop People and Project Management Responsibilities Develop new skillsets among team members related to advanced analytics by conducting training and period review Promotes cross functional seamless communication, sharing know how and creating same quality of experience across sector markets Qualifications 6+ years of experience in the field of analytics Ability to convert insights into story that answers critical business questions. Hands on in coding in tools like R and Python ( both or at least Hands on in MS excel(advanced) and SQL Understanding of data structures, adept in data cleaning, structure, and aggregation as per need End-to-end project management. Expert of statistical techniques like regression, forecasting, decision trees and modelling process- concept and coding. Ability to design model architecture and translate business problem into analytical problem Ability to visualize data set and identify KPIs that will help decision making. Good PowerPoint skills. Experience in ML techniques, cloud compatible tech stacks, understanding of data pipeline creation preferable

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

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.

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