10 Random Forests Jobs

A career within Actuarial Services will provide you with the opportunity to contribute general insurance advice and consulting services to clients such as insurers, banks, regulators, and third-party administrators. You will provide advice covering solvency, economic capital, risk management, mergers and acquisitions, company restructuring and risk control, financial modeling, underwriting, new legislation, and the efficiency of claims or reporting processes. Simply put, you might help analyze the impact that new regulation will have on an insurance company's balance sheet or you could be revising business projections and making sure they have adequate reserves. To really stand out and make us fit for the future in a constantly changing world, each and every one of us at PwC needs to be a purpose-led and values-driven leader at every level. To help us achieve this, we have the PwC Professional; our global leadership development framework. It gives us a single set of expectations across our lines, geographies, and career paths, and provides transparency on the skills we need as individuals to be successful and progress in our careers, now and in the future. Responsibilities As a Senior Associate, you'll work as part of a team of problem solvers, helping to solve complex business issues from strategy to execution. PwC Professional skills and responsibilities for this management level include but are not limited to: - Use feedback and reflection to develop self-awareness, personal strengths, and address development areas. - Delegate to others to provide stretch opportunities, coaching them to deliver results. - Demonstrate critical thinking and the ability to bring order to unstructured problems. - Use a broad range of tools and techniques to extract insights from current industry or sector trends. - Review your work and that of others for quality, accuracy, and relevance. - Know how and when to use tools available for a given situation and can explain the reasons for this choice. - Seek and embrace opportunities that give exposure to different situations, environments, and perspectives. - Use straightforward communication, in a structured way, when influencing and connecting with others. - Able to read situations and modify behavior to build quality relationships. - Uphold the firm's code of ethics and business conduct. - Help contribute to the development of GenAI solutions, including prompt engineering, retrieval-augmented generation (RAG), fine-tuning, AI agents, and multi-agent systems (MAS). - Apply econometric modeling techniques such as generalized linear models (GLMs), time series analysis, and semi-parametric models (e.g., fractional response models). - Utilize machine learning models including XGBoost, random forests, and support vector machines. - During the development, validation, and monitoring of models, ensure compliance with model-related regulatory requirements and standards such as SR 11-7, Colorado SB21-169, NIST, ISO 42001, and the NAIC Model Bulletin. - Experience with programming languages and environments such as Python, R, Databricks, and React. - Enforce DevOps best practices, including version control (Git), CI/CD, test automation, infrastructure as code, system monitoring, and cross-functional collaboration. - Design, develop, and deploy AI models in real-world client and business environments. - Monitor and research emerging AI trends, fostering an agile, forward-looking development environment. - Support project delivery and work with clients to process structured and unstructured data to improve business processes, workflows, and decision-making. - Support the documentation and technical analysis efforts for validators, auditors, and regulators; clearly communicate complex concepts to non-technical stakeholders. - Work with cross-functional teamsdata engineers, architects, and data scientiststo deliver efficient, high-quality solutions aligned with client needs. - Support business development efforts, including the technical sales cycles and the client proposal process. - Support the development of internal GenAI assets and foundational capabilities to grow the firm's practice. Qualifications Minimum Educational Qualifications: A degree in statistics, mathematics, electrical engineering, physics, econometrics, computer science, or another related technical field. Credentials - Good To Have A master's degree or PhD in a related field from a premium institute is preferred but is not required. Min years of Experience Requirement (Credential) - 3-4 years,

About the Role: We are seeking an experienced and highly skilled Data Science Expert to join our growing team at our Mumbai office. This is a full-time, onsite role focused not only on solving complex data problems but also on mentoring and training Junior Data Science Engineers. The ideal candidate will bring deep technical expertise in data science and machine learning, along with a passion for teaching and developing talent. ________________________________________ Key Responsibilities: Lead the development of end-to-end data science solutions using advanced ML, NLP, and Computer Vision techniques. Train, mentor, and support junior data science engineers in coding, model development, and best practices. Architect and implement AI-driven solutions such as chatbots, OCR systems, and facial recognition applications. Translate complex business problems into actionable data science projects and deliver measurable results. Design and lead internal workshops, code reviews, and learning sessions to upskill the team. Collaborate with engineering and product teams to deploy models and insights into production environments. Stay abreast of the latest AI/ML trends and integrate cutting-edge techniques into projects where applicable. ________________________________________ Desired Skills & Qualifications: Experience: 6+ years in Data Science/Machine Learning with at least 12 years of team mentoring or leadership experience. Education: Bachelors or Masters degree in Computer Science, Data Science, Statistics, or a related field. ________________________________________ Technical Expertise Required: Strong proficiency in Python and SQL; R is a plus. Solid hands-on experience with Deep Learning and Neural Networks, particularly in Natural Language Processing (NLP), Generative AI, and Computer Vision. Familiarity with frameworks and libraries such as TensorFlow, Keras, PyTorch, OpenCV, SpaCy, NLTK, BERT, ELMo, etc. Experience developing Chatbots, OCR, and Face Recognition systems is preferred. Hands-on knowledge of cloud platforms (AWS, Azure, or Google Cloud Platform). Experience applying statistical and data mining techniques such as GLM, regression, clustering, random forests, boosting, decision trees, etc. Strong understanding of model validation, performance tuning, and deployment strategies. ________________________________________ Soft Skills: Excellent communication and presentation skills, especially in explaining complex models to non-technical audiences. Demonstrated ability to mentor, train, and lead junior team members effectively. Strong analytical and problem-solving mindset with a detail-oriented approach. ________________________________________ What We Offer: Competitive salary and benefits A collaborative and intellectually stimulating environment Career growth and leadership development opportunities within a fast-paced team Show more Show less

As the Manager- Data Science at Holcim, you will play a crucial role in the Groups Global Advanced Analytics CoE by enabling our Businesses for Insights Driven Operations and Decision making through the utilization of cutting edge Analytics tools and techniques. Your primary responsibility will involve working closely with Business / Domain Subject Matter Experts to understand pain points and opportunities, and develop analytical models to identify patterns and predict outcomes of key business processes. You will be required to identify the most suitable modeling techniques and apply Machine Learning and Deep Learning Algorithms to create self-correcting models and algorithms. It will be essential to collaborate with Product Development teams to industrialize AI / ML models and conduct rapid and iterative prototyping of minimum viable solutions. Additionally, you will test hypotheses on raw datasets to derive meaningful insights and identify new opportunity areas. Your role will encompass all aspects of data including data acquisition, data exploration, feature engineering, building and optimizing models, and deploying Gen AI Solutions. You will be involved in designing full stack ML solutions in a distributed computing environment such as AWS and GCP, with the possibility of developing ML solutions for deployment on the edge or mobile devices if required. To be successful in this role, you should possess a total experience of 12-15 years with at least 8 years of relevant Analytics experience. Industry Experience and knowledge, particularly in Manufacturing/ Operations Functions within the Building Material Industry, Manufacturing, Process, or Pharma sectors, is preferred. Hands-on experience in statistical and data science techniques, as well as developing and deploying Gen AI Solutions, will be critical for this position. In terms of technical skills, you should have over 8 years of hands-on experience in advanced Machine Learning & Deep Learning techniques and algorithms, such as Decision Trees, Random Forests, SVMs, Regression, Clustering, Neural Networks, CNNs, RNNs, LSTMs, and Transformers. Proficiency in statistical computer languages like Python and PySpark to manipulate data and draw insights from large datasets is essential. Experience with Cloud platforms like AWS, DL frameworks such as TensorFlow, Keras, or PyTorch, and familiarity with business intelligence tools and data frameworks will be advantageous. In addition to technical skills, leadership and soft skills are equally important for this role. You should lead by example on values and culture, be open-minded, collaborative, and an effective team player. Working in a multicultural and diverse team, dealing with ambiguity, and communicating openly and effectively with various stakeholders are key aspects of this position. Being driven for success, aspiring to a culture of service excellence, and always prioritizing customer satisfaction, people, and business are qualities that will set you up for success in this role. If you are motivated by the opportunity to make a significant impact through data-driven decisions and innovative solutions, we invite you to build your future with us at Holcim by applying for this role.,

As an AI/ML Developer at our Gurugram location, you will be responsible for designing and implementing end-to-end machine learning models using Python for various tasks such as regression, classification, clustering, NLP, and deep learning. Your expertise in developing AI applications based on Machine Learning and Large Language Model (LLM) using tools like LangChain, RAG pipelines, vector databases, and more will be crucial in driving AI innovation. You will work on building and deploying AI applications leveraging technologies such as Retrieval Augmented Generation (RAG), LangChain, LLMs (OpenAI, Huggingface Transformers), and Vector Databases (FAISS, Pinecone, Milvus). Your role will involve developing robust pipelines for semantic search and retrieval chains in real-world production systems, writing clean and efficient Python code, and collaborating with cross-functional teams to deliver scalable AI/ML solutions. If you have front-end skills in React, it would be considered a big plus as you may also contribute to UI components for interactive AI applications. To be successful in this role, you should have at least 5 years of hands-on experience in AI/ML development using Python and a strong knowledge of ML algorithms such as XGBoost, SVM, Random Forests, Logistic Regression, as well as deep learning models like CNNs, RNNs, Transformers (BERT, GPT), and unsupervised learning techniques including K-Means and PCA. Experience with RAG architecture, LangChain, advanced prompt engineering, vector search techniques, and Python libraries like scikit-learn, TensorFlow, PyTorch, and Huggingface Transformers is essential. Proficiency in working with cloud environments such as AWS, Azure, or GCP is also required. It would be nice to have front-end development experience using React.js, familiarity with MLOps tools like MLflow, Kubeflow, Airflow, and knowledge of self-supervised or contrastive learning methods such as SimCLR and CLIP. In this role, you will have the opportunity to work on cutting-edge AI/ML technologies, collaborate in a fast-paced and innovative environment, contribute to impactful production-level AI solutions, and enjoy competitive compensation and benefits.,

As a Data Science Instructor at our dynamic team, you will play a crucial role in preparing students for the evolving data science landscape. Your primary focus will be on delivering immersive and hands-on learning experiences to equip future data professionals with practical skills in SQL, Python, Machine Learning, and real-world project development. Your responsibilities will include developing and conducting engaging lessons and workshops covering core data science topics, with a notable emphasis on SQL and Python programming. You will guide students through foundational machine learning models such as linear regression, logistic regression, decision trees, and random forests, ensuring they comprehend both the theoretical concepts and practical applications. Moreover, you will be tasked with designing and facilitating hands-on projects to help students apply their knowledge effectively and build a robust portfolio of work. Your ability to explain complex technical concepts in a clear and concise manner will be pivotal in making the material accessible to a diverse group of learners. As a mentor, you will provide constructive feedback and guidance to support students in overcoming challenges and enhancing their understanding. Collaboration with our team to continuously enhance and refine our curriculum to ensure its relevance and cutting-edge nature will also be part of your role. To excel in this position, you must have proven experience as a Data Scientist, Machine Learning Engineer, or similar role, backed by a strong portfolio that demonstrates your expertise in Python and machine learning projects. Your proficiency in Python for data analysis, manipulation, and model building, along with practical experience in common machine learning models, is essential. Additionally, your exceptional ability to design and lead hands-on projects that foster practical skill development, coupled with strong communication and presentation skills, will be key in your success. Proficiency in SQL for data querying and management is also required. Preferred qualifications include familiarity with Python libraries like Streamlit, experience with Natural Language Processing (NLP) concepts, exposure to Large Language Models (LLMs) or chatbot development, and prior experience in teaching, mentoring, or training roles. If you are enthusiastic about empowering the next generation of data scientists and possess a proven track record in building and explaining data science projects, we encourage you to reach out to us at hr@ndmit.com. Join us in shaping the future of data science education!,

You will be responsible for building and interpreting machine learning models on real business data from the SigView platform, such as Logistic Regression, Boosted trees (Gradient boosting), Random Forests, and Decision Trees. Your tasks will include identifying data sources, integrating multiple sources or types of data, and applying data analytics expertise within a data source to develop methods to compensate for limitations and extend the applicability of the data. Moreover, you will be expected to extract data from relevant data sources, including internal systems and third-party data sources, through manual and automated web scrapping. Your role will involve validating third-party metrics by cross-referencing various syndicated data sources and determining the numerical variables to be used in the same form as they are from the raw datasets, categorized into buckets, and used to create new calculated numerical variables. You will perform exploratory data analysis using PySpark to finalize the list of compulsory variables necessary to solve the business problem and transform formulated problems into implementation plans for experiments by applying appropriate data science methods, algorithms, and tools. Additionally, you will work with offshore teams post data preparation to identify the best statistical model/analytical solution that can be applied to the available data to solve the business problem and derive actionable insights. Your responsibilities will also include collating the results of the models, preparing detailed technical reports showcasing how the models can be used and modified for different scenarios in the future to develop predictive insights. You will develop multiple reports to facilitate the generation of various business scenarios and provide features for users to generate scenarios. Furthermore, you will be interpreting the results of tests and analyses to develop insights into formulated problems within the business/customer context and provide guidance on risks and limitations. Acquiring and using broad knowledge of innovative data analytics methods, algorithms, and tools, including Spark, Elasticsearch, Python, Databricks, Azure, Power BI, Azure Cloud services, LLMs-Gen AI, and Microsoft Suite will be crucial for success in this role. This position may involve telecommuting and requires 10% travel nationally to meet with clients. The minimum requirements for this role include a Bachelor's Degree in Electronics Engineering, Computer Engineering, Data Analytics, Computer Science, or a related field plus five (5) years of progressive experience in the job offered or related occupation. Special skill requirements for this role include applying statistical methods to validate results and support strategic decisions, building and interpreting advanced machine learning models, using various tools such as Python, Scikit-Learn, XGBoost, Databricks, Excel, and Azure Machine Learning for data preparation and model validation, integrating diverse data sources using data analytics techniques, and performing data analysis and predictive model development using AI/ML algorithms. Your mathematical knowledge in Statistics, Probability, Differentiation and Integration, Linear Algebra, and Geometry will be beneficial. Familiarity with Data Science libraries such as NumPy, SciPy, and Pandas, Azure Data Factory for data pipeline design, NLTK, Spacy, Hugging Face Transformers, Azure Text Analytics, OpenAI, Word2Vec, and BERT will also be advantageous. The base salary for this position ranges from $171,000 to $190,000 per annum for 40 hours per week, Monday to Friday. If you have any applications, comments, or questions regarding the job opportunity described, please contact Piyush Khemka, VP, Business Operations, at 111 Town Square Pl., Suite 1203, Jersey City, NJ 07310.,

At EY, you'll have the chance to build a career as unique as you are, with the global scale, support, inclusive culture, and technology to become the best version of yourself. Your unique voice and perspective are valued to help EY become even better. Join us and contribute to building an exceptional experience for yourself and creating a better working world for all. As a part of our EY - Technology Risk team, you will contribute technically to IT Risk and Assurance client engagements as well as internal projects. Your role will involve actively establishing, maintaining, and strengthening internal and external relationships. You will also be responsible for identifying potential business opportunities for Ernst & Young within existing engagements and escalating them as appropriate. Anticipating and identifying risks within engagements and sharing any issues with senior team members will also be part of your responsibilities. The opportunity entails helping clients navigate the complex world of modern data science and analytics. You will provide advice to clients on designing, implementing, stabilizing, and optimizing internal controls using cutting-edge and scalable AI & Big Data technologies. Your key responsibilities include: - Building and leveraging cutting-edge Gen AI & Big Data platforms to deliver insights for comprehensive Risk & Controls monitoring mechanisms. - Creating executive reporting, proposals, and marketing material with the highest quality deliverables. - Collaborating within the team to solve technical challenges in the design and development of the next-generation AI & Data-led Risk technology platform. To qualify for this role, you must have: - 4+ years of working experience in Large Scale AI/ML models and data science. - Deep understanding of statistics, AI/ML algorithms, and predictive modeling. - Proficiency in AI/ML programming languages like Python, R, and SQL. - Expertise in machine learning algorithms and data mining techniques including deep learning algorithms. - Strong programming skills in Python with machine learning libraries such as Scikit-learn, Pandas, NumPy, etc. - Knowledge of tools such as Docker, Kubernetes, Git, and deep learning frameworks like TensorFlow, PyTorch, or Keras. Ideally, you'll also have a Bachelor's Degree or above in mathematics, information systems, statistics, computer science, Data Science, or related disciplines. Relevant certifications are considered a plus. Being self-driven, a creative problem solver, and enjoying the fast-paced environment of software development are qualities that are valued. At EY, you will have opportunities to work with leading businesses globally and develop your skills and career. You will work on inspiring and meaningful projects, receive support, coaching, and feedback from engaging colleagues, and have the freedom and flexibility to handle your role in a way that suits you. EY is committed to building a better working world by creating long-term value for clients, people, and society through trust, data, and technology.,

Key Responsibilities: 1. 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 2. 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. 3. 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. 4. 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.

Job Title: Senior Data Scientist Location: Bengaluru Experience: 8+ Years About Linarc: Linarc is revolutionizing the construction industry. As the emerging leader in construction technology, we are redefining how projects are planned, executed, and delivered. Built for general contractors, construction managers, and trade partners, Linarc is a next-generation platform that brings unmatched collaboration, automation, and real-time intelligence to construction projects. Our mission is to eliminate inefficiencies, streamline workflows, and drive profitabilityhelping teams deliver projects faster, smarter, and with greater control. Join us and be part of a high-impact, fast-growing team thats shaping the future of construction tech. If you thrive in a dynamic environment and want to make a real difference in the industry, Linarc is the place to be. This is a full-time position and you will be working out of our Bengaluru office. Roles and Responsibilities: Data Analysis & Modeling: Develop and implement machine learning models to solve business problems. Build predictive models and algorithms for customer behavior, product usage, and business outcomes. Conduct statistical analysis and hypothesis testing to uncover insights. Data Engineering & Processing: Clean, preprocess, and transform large-scale datasets from multiple sources. Develop and optimize data pipelines for real-time and batch processing. Business Insights & Reporting: Collaborate with business teams to define key performance indicators (KPIs). Develop dashboards and reports to communicate findings and performance. Present insights and recommendations to stakeholders and leadership. Product Improvement: Partner with product managers to integrate data-driven insights into product features. Monitor model performance and continuously improve accuracy and scalability. Run A/B tests to evaluate the impact of product changes. Research & Development: Stay updated with the latest developments in machine learning, AI, and data science. Explore and implement new data science techniques and tools to improve outcomes. Qualifications: Minimum 7+years of professional experience in Data Analytics/ Data Science/ AI/ Machine Learning. Deep analytical expertise in applying statistical solutions to business problems. Experience with exploratory data analysis with large data sets using SQL, Hive, Spark, or other tools. ML/DL tools, Scikit-learn, Tensorflow or PyTorch and proficiency in one or more statistical techniques: Neural Networks, Gradient Boosting, Linear & Logistic Regression, Decision Trees, Random Forests, Markov Chains, Support Vector Machines, Clustering, Principal Component Analysis, Factor analysis, etc. Experience working with visualization tools such as Tableau and Power BI. Demonstrated ability to innovate solutions and solve business problems. What will also help: Four or more years of experience in data science or machine learning in a product-focused environment. Four or more years of experience with one or more: C, Python, PyTorch, Java, JavaScript, NodeJs, ReactJs, VueJs. Four or more years of experience with relational or document databases. Adept at hypothesis testing and regression analysis. Experience in a SaaS product environment. Bachelors / Masters degree in Computer Science, Data Science, Mathematics, Statistics, or a related field.

Job Description Job Title: Data Scientist Location: Bengaluru / Chennai Experience: 3+ Years About Linarc: Linarc is revolutionizing the construction industry. As the emerging leader in construction technology, we are redefining how projects are planned, executed, and delivered. Built for general contractors, construction managers, and trade partners, Linarc is a next-generation platform that brings unmatched collaboration, automation, and real-time intelligence to construction projects. Our mission is to eliminate inefficiencies, streamline workflows, and drive profitabilityhelping teams deliver projects faster, smarter, and with greater control. Join us and be part of a high-impact, fast-growing team thats shaping the future of construction tech. If you thrive in a dynamic environment and want to make a real difference in the industry, Linarc is the place to be. This is a full-time position and you will be working out of our Bengaluru office. Roles and Responsibilities: Data Analysis & Modeling: Develop and implement machine learning models to solve business problems. Build predictive models and algorithms for customer behavior, product usage, and business outcomes. Conduct statistical analysis and hypothesis testing to uncover insights. Data Engineering & Processing: Clean, preprocess, and transform large-scale datasets from multiple sources. Develop and optimize data pipelines for real-time and batch processing. Business Insights & Reporting: Collaborate with business teams to define key performance indicators (KPIs). Develop dashboards and reports to communicate findings and performance. Present insights and recommendations to stakeholders and leadership. Product Improvement: Partner with product managers to integrate data-driven insights into product features. Monitor model performance and continuously improve accuracy and scalability. Run A/B tests to evaluate the impact of product changes. Research & Development: Stay updated with the latest developments in machine learning, AI, and data science. Explore and implement new data science techniques and tools to improve outcomes. Qualifications: Minimum 3+years of professional experience in Data Analytics/ Data Science/ AI/ Machine Learning. Deep analytical expertise in applying statistical solutions to business problems. Experience with exploratory data analysis with large data sets using SQL, Hive, Spark, or other tools. ML/DL tools, Scikit-learn, Tensorflow or PyTorch and proficiency in one or more statistical techniques: Neural Networks, Gradient Boosting, Linear & Logistic Regression, Decision Trees, Random Forests, Markov Chains, Support Vector Machines, Clustering, Principal Component Analysis, Factor analysis, etc. Experience working with visualization tools such as Tableau and Power BI. Demonstrated ability to innovate solutions and solve business problems. What will also help: Four or more years of experience in data science or machine learning in a product-focused environment. Four or more years of experience with one or more: C, Python, PyTorch, Java, JavaScript, NodeJs, ReactJs, VueJs. Four or more years of experience with relational or document databases. Adept at hypothesis testing and regression analysis. Experience in a SaaS product environment. Bachelors / Masters degree in Computer Science, Data Science, Mathematics, Statistics, or a related field.