29 Gradient Boosting Jobs

As a leader in supporting AWM LFO Predictive Analytics Ameriprise India team, you will be responsible for leading advanced data science work and collaborating with cross-functional teams to recommend and implement analytical solutions for the Advise & Wealth Management business. **Key Responsibilities:** - Analyze, design, develop, and implement decision support models and data visualizations using tools like Python, Microsoft Excel/PowerBI. - Develop innovative analytical solutions such as segmentation, predictive modeling, simulation modeling, and optimization. - Maintain infrastructure systems connecting internal data sets and create new data collection frameworks. - Interact with business partners to analyze and interpret business needs, translating top-level goals into quantifiable analysis activities. - Develop presentation decks and effectively communicate with business leaders. - Demonstrate thought leadership in solving complex business problems. - Drive team performance and ensure strong people development for high performance. **Required Qualifications:** - Engineering (B.E./ B.Tech.) graduate or Masters in Stats, Quant, Mathematics, OR, etc. from a well-recognized institute; MBA degree preferred. - 12+ years of experience in Data Science. - Hands-on experience in complex analytics projects using advanced statistical methods. - Proficiency in Python, cloud computing (AWS), SQL, and Data Lake experience. - Ability to effectively present complex technical materials to business leaders. - Strategic thinker providing technical solutions for complex business problems. - Excellent knowledge of MS Office Suite. - In-depth knowledge of the financial services industry with a focus on risk. - People leadership experience with prior team management responsibilities. **Preferred Qualifications:** - Ability to engage business partners and finance personnel with clear, data-backed insights. - Experience working with AWS Cloud framework and associated tools. - Experience working in a data lake environment. - Knowledge of tools like DataIku, PowerBI, Tableau, and other BI and analytical tools. At Ameriprise India LLP, we have been providing client-based financial solutions for 125 years. Join our inclusive and collaborative culture that rewards contributions and offers opportunities for growth. Make your mark and a difference in your community by creating a career at Ameriprise India LLP. (Note: The additional details about the company have been omitted as they were not explicitly mentioned in the job description.),

About Info Edge: InfoEdge's mission is to create world-class platforms that transform lives by continuously innovating. Our products and services are built keeping our customers in mind. We always delight our customers by delivering superior value through enhanced offerings on the internet and other platforms. Through our continuous investment across various businesses, especially in cutting-edge technology, machine learning and artificial intelligence (AI), we have built a robust system that constantly increases our predictive powers on customer behaviour, and optimizes and improves our systems. Our various teams tirelessly work together to solve problems, innovate, and create something to empower our customers. At Info Edge, people are our core competitive advantage and we will continue doing all that is needed to attract and retain the best available talent. * About BU: Corporate Function * Required Educational Qualification: PhD/ MTech / BTech with relevant experience from Tier 1 Campus only. * Desired Experience: 0 - 5 Years * Job Objective: You will be building innovative Machine Learning solutions for vital and complex business problems. *Fill this form to proceed further: ( https://tinyurl.com/FAIscientist ) Job Description: As AI Scientist you will: Develop algorithms and build systems to extract seemingly unseen trends and information from user content such as resumes, job description and profile information available through various sources and in different modalities such as numeric, structure and unstructured texts and images. Identify potential new business problems that can be solved through machine learning. Ideate, formulate, create metrics and execute on such problems and get buy in from business. Identify potential data-driven machine learning solutions to improve user experience through personalization and prediction of user preferences. Build intelligent systems to capture and model the vast amount of behavior data to enrich the content understanding with behavioral information. Identify the appropriate and cutting edge machine learning tools for various supervised and unsupervised tasks in the NLP, deep learning, semantic search, LTR space for building highly accurate and scalable recommendation systems and information retrieval solutions. Design solutions for scalable and real-time performance on a significantly large data set. Use big data technologies to optimally use infrastructure and improve performance. Participate in external forums /discussions, publish research papers, keep up-to-date on latest publications and build external/internal networks. Required Skills: Strong fundamental understanding and research experience in machine learning/Deep Learning/NLP/Information Retrieval/Artificial Intelligence areas. Strong applied knowledge of machine learning in solving real-world business problems with a significantly broad number of algorithms covering the landscape of classification, regression; discriminative, generative; supervised, unsupervised, semi-supervised; linear and non-linear dimensionality reduction, feature-extraction, feature selection, feature-learning. Industry experience in applying a variety of machine learning solutions to real-world large-scale data to build intelligent systems. An excellent problem solving skills with a research oriented approach. Ability to capture, manage, create pipelines and process Big Data. Desired Skills: Ability to understand Business challenges and define solutions aligned to the needs.

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 you. We are counting on your unique voice and perspective to help EY become even better. Join us in building an exceptional experience for yourself and contribute to creating a better working world for all. As an AI/ML Developer in Technology Assurance at EY, you will have the opportunity to contribute technically to Risk Assurance client engagements and internal projects. Your role will involve assisting Seniors & Managers, actively participating in client engagement, anticipating and identifying risks, and ensuring that work is of high quality and reviewed thoroughly. By joining our team, you will help create a positive learning culture, assist fellow team members, and deliver assignments effectively. We are seeking professionals with a minimum of 2 years of experience to be part of a cross-functional team responsible for the full software development life cycle. This role offers a great opportunity to work with a leading firm and play a key role in the growth of a new service offering. Key Skills and Accountabilities: - Develop robust AI/ML models to drive insights and enhance decision-making processes across various business lines. - Use predictive modeling to optimize customer experiences, revenue generation, ad targeting, and other business outcomes. - Proficiency in Machine learning, NLP, LLM, GenAI, deep learning, and generative AI techniques. - Apply advanced machine learning techniques to solve complex problems. - Design and implement innovative solutions for workflow orchestration using Python, Airflow, and Terraform. - Collaborate with cross-functional teams to assess control effectiveness and facilitate remediation activities. To qualify for this role, you must have: - Minimum 2 years of experience working with Large Scale AI/ML models. - Technical knowledge of Big Data Platforms, AI technologies, and DevOps services. - Proficiency in AI/ML programming languages such as Python, R, SQL. - Experience with deep learning frameworks like TensorFlow, PyTorch, or Keras. - Implement monitoring and logging tools to ensure AI model performance. - Automation skills using Python scripting, databases, and advanced technologies. Preferred Qualifications: - Bachelor's Degree or higher in relevant disciplines. - Relevant certifications are considered a plus. - Self-driven problem-solver who thrives in the fast-paced world of software development. Join EY in building a better working world, creating long-term value for clients, people, and society, and building trust in the capital markets. Our diverse teams in over 150 countries provide assurance and help clients grow, transform, and operate by asking better questions to find new answers for today's complex issues.,

We are building Saulikh, a platform transforming agri-trade with data science and AI. Our goal is to bring trust, transparency, and intelligence to commodity trading at scale. Role Overview We are seeking a Data Scientist to lead data-driven initiatives across trade, pricing, risk, and logistics. The role involves working with real-world datasets, building dashboards, applying ML models, and assisting in the development of prototypes for trust scoring, fraud detection, and forecasting. Key Responsibilities Collect, clean, and preprocess financial, transactional, and behavioral datasets from multiple sources. Design and implement trust/credit scoring algorithms that assess buyer/seller reliability and default risk. Engineer features from trade history, payment timeliness, disputes, cancellations, and external market data. Apply statistical models and machine learning techniques (logistic regression, random forests, gradient boosting, neural networks) to predict trustworthiness. Develop scoring frameworks normalized to a range (e.g., 01000), similar to CIBIL standards. Validate and back-test models against historical data to ensure accuracy, fairness, and stability. Build monitoring pipelines to track score performance, drift, and anomalies in real time. Work with business and product teams to ensure scores align with practical trade and risk management requirements. Document methodologies and communicate insights to technical and non-technical stakeholders. Requirements Bachelors or Masters degree in Computer Science, Statistics, Mathematics, Economics, or a related field. 25 years of experience as a Data Scientist, preferably in credit scoring, risk modeling, or fraud detection. Strong proficiency in Python (pandas, numpy, scikit-learn, statsmodels) or R. Experience with machine learning algorithms such as logistic regression, decision trees, random forests, gradient boosting (XGBoost/LightGBM), and neural networks. Strong SQL skills for handling large datasets; experience with data pipelines and API integrations. Domain knowledge of credit scoring principles, risk assessment, and regulatory considerations . Experience in model validation, back-testing, and ensuring fairness and interpretability. Excellent analytical and problem-solving skills with attention to detail. Strong communication skills for presenting findings to technical and business stakeholders. The interested candidates may apply here. Show more Show less

Citi is seeking an energetic and motivated professional to join its Fraud Analytics team as a Specialized Analytics Sr. Analyst. In this role, you will be part of the Global Fraud Analytics team, responsible for developing and validating fraud models to support Citis North American Cards business. As a strategic professional, you will stay updated on the latest trends in the field and apply them to your work. Strong communication skills are essential for negotiating internally and collaborating with Strategy partners and Model Risk Management validators. Your responsibilities will include model development, validation, and testing of fraud detection models, ensuring compliance with regulatory requirements and industry best practices. You will work with large and complex data sets to evaluate business strategies, identify data sets using tools like Hive and SQL, and document data requirements. Specialization in fraud or risk domain is preferred. Additionally, you will assess risks when making business decisions, ensuring compliance with laws and regulations while safeguarding Citigroup, its clients, and assets. The ideal candidate will have 8+ years of hands-on analytical experience and 5+ years of experience in statistical analysis with proficiency in Python (Must), Hive, Spark, or SAS. Strong quantitative, analytical, and problem-solving skills are required, along with knowledge of statistical concepts, modelling techniques, and model evaluation techniques. You should also have strong communication and interpersonal skills, project management abilities, and the capacity to work independently. A Master's, Bachelor's, or PhD degree in Statistics, Economics, Finance, Mathematics, or a related quantitative field is required, with an Engineering or MBA background from a premier institute being an advantage. This is a full-time position in the Decision Management department, specifically in the Specialized Analytics (Data Science/Computational Statistics) job family at Citi. Citi is an equal opportunity and affirmative action employer, inviting all qualified and interested applicants to apply for career opportunities.,

As a Senior Data Scientist at Zinnia, you will be a vital member of our team, playing a key role in developing cutting-edge solutions to drive the growth of life and annuities products. Your expertise in machine learning and forecasting will be instrumental in influencing decision-makers and shaping the future of our business. In this high-impact role, you will independently own and build forecasting models, working closely with stakeholders from Product, Data Engineering & Analytics, and Business Strategy. By leveraging data from various sources, you will provide valuable insights and develop new data-driven tools to enhance customer experiences and streamline internal processes. Your responsibilities will include developing machine learning applications using Python, implementing supervised and unsupervised models such as random forest, gradient boosting, and support vector machines. You will also work on advanced modeling techniques like reinforcement learning and neural networks to deliver prescriptive insights and automated decision-making capabilities. Moreover, you will collaborate with data engineering teams to ensure the quality of data, conduct experiments to measure model impact, and manage training pipelines effectively. Your role will involve translating complex business problems into actionable data science projects and deploying models to production infrastructure. As a mentor and collaborator, you will work with other data scientists and data analysts to foster a culture of learning and innovation within the team. Additionally, you will partner with marketing teams to conceptualize applications that drive company growth and strategy, connecting machine learning solutions with business needs. To excel in this role, you should have a minimum of 5 years of experience in building and validating machine learning models in Python. Your expertise should cover a range of model techniques including supervised and unsupervised learning, as well as advanced techniques like neural networks and natural language modeling. Experience with relational cloud databases and unstructured datasets will also be crucial for success in this position. If you are a highly motivated individual with a passion for data science, a drive to solve complex business challenges, and a desire to make a significant impact in the insurance industry, we invite you to join us at Zinnia and be part of our mission to protect financial futures through innovation and data-driven insights.,

About Citi: Citi's Mission and Value Proposition explain what we do and Citi Leadership Standards explain how we do it. Our mission is to serve as a trusted partner,

This role for Group Lead - Data Scientist is to provide people leadership and analytical support to our business partners in the AWM Finance. The candidate should be hands on in advanced programing, visualization, and Analytics algorithms. Work in a matrix organization with data scientists, data engineers and decision science managers, collaborate with cross-functional teams, recommend, and implement analytical solutions to Advise & Wealth Management business Key Responsibilities Responsible for the analysis, design, development and implementation of decision support models and data visualizations using Python, Microsoft Excel/PowerBI based tools like PowerPivot/PowerView. Develop innovative analytical solutions, like segmentation, predictive modeling, simulation modeling, and optimization. Develops and maintains infrastructure systems that connect organization&aposs internal data sets; creates new data collection frameworks for structured and unstructured data of client organization. Interact with business partner to analyze and interpret business needs. Ensure to translate top level business goals into quantifiable analysis activities. Test and measure effectiveness of new approaches as well as process improvements. Coordinate tasks and assignments across many individuals Develop presentation decks and communicate clearly to business leaders. Analytical thought leader participates in discovery sessions to identify opportunities to leverage analytics to automate and enhance business processes Deliver on advanced analytical requests related to targeting and/or segmentation related problems Participate in solving multiple complex problems. Mentor junior team members in solving business problems through the use of advanced analytics algorithms. Required Qualifications Engineering (B.E./ B. Tech.) graduate or Masters (Stats, Quant, Mathematics, OR, etc.) from a well-recognized institute 7 - 10 years of experience in advanced analytical skill-oriented work profiles Experience in conducting hands-on complex analytics projects using advanced statistical methods such GLM, Bayesian methods, random forest, gradient boosting, neural network, and machine learning methods etc. Proficient in Python programming, cloud computing (AWS), SQL and Data Lake experience Proven ability to present/communicate effectively complex technical materials to business leaders Strategic thinker who can provide technical solutions for very complex business problems Excellent knowledge of MS Office Suite In-depth knowledge of financial services industry with a focus in risk and ability to articulate key concepts to others Experience with Finance industry 5+ years, specifically supporting Wealth management, Insurance, Banking, and other investment instruments Experience on working with AWS Cloud framework and associated tools Experience on working in data lake environment Preferred Qualifications About Our Company Ameriprise India LLP has been providing client based financial solutions to help clients plan and achieve their financial objectives for 125 years. We are a U.S. based financial planning company headquartered in Minneapolis with a global presence. The firms focus areas include Asset Management and Advice, Retirement Planning and Insurance Protection. Be part of an inclusive, collaborative culture that rewards you for your contributions and work with other talented individuals who share your passion for doing great work. Youll also have plenty of opportunities to make your mark at the office and a difference in your community. So if you&aposre talented, driven and want to work for a strong ethical company that cares, take the next step and create a career at Ameriprise India LLP. Ameriprise India LLP is an equal opportunity employer. We consider all qualified applicants without regard to race, color, religion, sex, genetic information, age, sexual orientation, gender identity, disability, veteran status, marital status, family status or any other basis prohibited by law. Full-Time/Part-Time Full time Timings (2:00p-10:30p) India Business Unit AWMPO AWMP&S President&aposs Office Job Family Group Data Show more Show less

About the role: This is a unique opportunity to join our fast-growing Data Science team. In the role of Data Scientist, you will execute large scale, high impact data modeling projects with responsibility for designing, developing, validating, socializing, operationalizing, and maintaining data-driven analytics that provide business insights to increase operational efficiency and customer value. What you will do: Deliver modeling and analytical insights to inform strategic and operational initiatives Conduct all phases of the model development process. Including: Understanding business issues, proposing technical solutions, data wrangling, data cleaning, data analysis, feature engineering, model selection, model development, model validation, model operationalization, presentation of results and insights, model implementation, model documentation Convert top-down business initiative requirements into actionable data analytics projects as well as conceiving and proposing a bottom-up analytics innovations Communicate technical solutions and results to business stakeholders Partner with business stakeholders, IT and lead the design and delivery ML solutions Inject the most applicable technology, including Machine Learning, Artificial Intelligence, Natural Language Processing and Statistical Modeling Continuously innovate with state of art techniques to improve the model What you will need: For Data Scientist 3-6 years & for Associate Data Scientist 1-3 years of experience in solving real life business problems using ML & Data Science Bachelor's degree is required. Master's degree preferred. Technical degrees with a concentration in statistics, data science, computer science or related field preferred In-depth knowledge of statistical methods & principles and its usage in the model building & data analysis Experience in applying descriptive, predictive, prescriptive models & data visualization to solve real life business problems Understanding of NLP concepts and its application is preferred Expertise in Python, SQL, Spark Experience with multiple modeling techniques such as: Time Series, Random Forests, Clustering, Neural Networks, Generalized Linear Models, Optimization, DOE, Dimensionality Reduction MLOps experience is preferred (implementing models/algorithms into production systems) Ability to work in a fast-paced environment and deliver against milestones Excellent communication skills in technical and business domains Proven ability to influence key stakeholders and leaders What you will get: Competitive salary, generous paid time off policy, charity match program, Group Medical Insurance, Parental Leave, Employee Assistance Program (EAP) and more! Collaborative, team-oriented culture that embraces diversity Professional development and unlimited growth opportunities

You will be taking up a leadership role within the AWM LFO Predictive Analytics Ameriprise India team, where your primary responsibility will involve leading advanced data science initiatives. Working within a matrix organizational structure alongside data scientists, data engineers, and decision science managers, you will collaborate with cross-functional teams to recommend and implement analytical solutions that support the Advise & Wealth Management business. Your active participation in strategic planning, project management, and hands-on complex data analysis will be crucial in aiding business decisions. Your key responsibilities will include analyzing, designing, developing, and implementing decision support models and data visualizations using tools such as Python, Microsoft Excel, and PowerBI. You will be expected to develop innovative analytical solutions like segmentation, predictive modeling, simulation modeling, and optimization. Additionally, you will play a role in developing and maintaining infrastructure systems connecting internal data sets, creating new data collection frameworks for structured and unstructured data of client organizations, and liaising with business partners to interpret business needs. Furthermore, you will be tasked with translating high-level business objectives into quantifiable analysis activities, testing and measuring the effectiveness of new approaches, coordinating tasks across individuals, developing presentation decks, and effectively communicating with business leaders. Thought leadership in solving complex business problems, driving team performance, ensuring people development, and building high-performing teams will also be part of your responsibilities. To be eligible for this role, you must hold a degree in Engineering (B.E./ B.Tech.) or Masters in Stats, Quant, Mathematics, OR, etc., from a reputable institute, with an MBA degree being preferred. You should have a minimum of 12 years of relevant experience in the field of Data Science, hands-on experience in complex analytics projects, proficiency in Python programming, cloud computing, SQL, Data Lake experience, and the ability to effectively present technical materials to business leaders. Moreover, you are expected to possess a strategic mindset, excellent knowledge of MS Office Suite, in-depth understanding of the financial services industry with a focus on risk, and people leadership experience. Preferred qualifications include experience in a data lake environment, knowledge of tools such as DataIku, PowerBI, Tableau, and other BI tools. This leadership opportunity at Ameriprise India LLP offers a chance to be part of a global financial planning company with a strong ethical culture, collaborative environment, and rewarding opportunities for making a difference in both the organization and the community.,

Genpact (NYSE: G) is a global professional services and solutions firm dedicated to shaping the future through the delivery of impactful outcomes. With a workforce of over 125,000 individuals spanning across 30+ countries, we are inspired by our innate curiosity, entrepreneurial agility, and commitment to creating enduring value for our clients. Our purpose, driven by the relentless pursuit of a world that works better for people, empowers us to serve and transform major enterprises, including the Fortune Global 500, leveraging our deep business and industry expertise, digital operations services, and proficiency in data, technology, and AI. We are currently seeking applications for the position of Business Analyst - Data Scientist. As a part of this role, you will be tasked with the development and implementation of NLP models and algorithms, extracting insights from textual data, and collaborating with cross-functional teams to deliver AI solutions. Responsibilities: Model Development: - Proficiency in various statistical, ML, and ensemble algorithms. - Demonstrated expertise in Time series algorithms and forecasting use cases. - Ability to discern model-specific strengths and weaknesses and identify suitable models for different problem types. - Understanding of evaluation metrics and the ability to recommend the correct evaluation metric for a given problem. Data Analysis: - Extraction of meaningful insights from structured data. - Data preprocessing for ML/AI applications. Collaboration: - Close collaboration with data scientists, engineers, and business stakeholders. - Providing technical guidance and mentorship to team members. Integration and Deployment: - Integration of ML models into production systems. - Implementation of CI/CD pipelines for continuous integration and deployment. Documentation and Training: - Documentation of processes, models, and results. - Provision of training and support to stakeholders on NLP techniques and tools. Qualifications we seek in you: Minimum Qualifications/Skills: - Bachelor's degree in computer science, Engineering, or a related field. - Strong programming skills in Python and R. - Experience with DS frameworks (SKLEARN, NUMPY). - Knowledge of machine learning concepts and frameworks (TensorFlow, PyTorch). - Strong problem-solving and analytical skills. - Excellent communication and collaboration abilities. Preferred Qualifications/Skills: - Experience in Predictive Analytics and Machine Learning techniques. - Proficiency in Python/R/Any other open-source programming language. - Experience with visualization tools such as Tableau, Power BI, Qlikview, etc. - Applied statistics skills including distributions, statistical testing, regression, etc. - Knowledge and experience with various tools and techniques in Forecasting, Linear Regression, Logistic Regression, Regularization, Segmentation, Cluster Analysis, Factor Analysis, Machine Learning (Random Forest, Gradient Boosting, SVM, XGBoost, Deep Learning), etc. - Familiarity with big data technologies (Hadoop, Spark) and cloud platforms (AWS, Azure, GCP). This is a full-time position located in India-Hyderabad. If you are a dynamic professional with a passion for driving innovation and creating impactful solutions, we invite you to apply for this exciting opportunity.,

As a Senior Analyst, Internal Audit - Data Scientist at Synchrony, you will play a crucial role in enhancing the organization's governance, risk management, and controls through data science and data engineering development within the Internal Audit department. Reporting to the VP, Internal Audit - Innovation and Advanced Analytics leader, you will be responsible for creating advanced analytics solutions to improve decision-making processes and provide robust data analytics support to audit teams. Your work will focus on generating actionable insights to enhance audit efficiency, automate processes, and drive continuous improvement in audit practices. Your key responsibilities will include delivering advanced analytics to support the audit plan, designing and deploying analytic scripts and dashboards, ensuring data accuracy and integrity through data transformation techniques, and collaborating with internal audit teams and stakeholders to drive data-driven opportunities and integration of data insights into action plans. Additionally, you will lead projects from ideation to presentation of results and recommendations, leveraging your skills in SQL/SAS queries, Python coding, data visualization tools like Tableau or Power BI, and model development techniques. To be successful in this role, you should possess a Bachelor's degree in Engineering, Computer Science, Data Science, or a related field with at least 3+ years of experience in writing and optimizing SQL/SAS queries in a business environment. Knowledge of data warehouse architecture, ETL tools, and proficiency in Python coding are essential, along with experience in data manipulation from multiple sources and familiarity with segmentation and model development techniques. Strong communication, relationship building, project management, and collaboration skills are also required. Desired skills include the ability to drive change and transformation, experience in internal audit functions, project management skills, and proficiency in Tableau, Power BI, and the Microsoft Power Platform. This remote position offers flexibility and choice, allowing you to work from home with occasional in-person engagement activities. The work timings require availability between 06:00 AM Eastern Time and 11:30 AM Eastern Time, with flexibility in the remaining hours. Eligibility criteria include the specified educational background and experience with SQL/SAS queries. If you are an internal applicant, ensure you understand the role requirements, inform your manager and HRM before applying, update your professional profile, and meet the eligibility criteria based on your current grade/level within the organization. This role is at Grade/Level 09 in the Internal Audit job family group at Synchrony.,

The role of S&C Global Network - AI - Marketing Analytics (MMM) Consultant at Accenture involves driving strategic initiatives, managing business transformations, and leveraging industry expertise to create value-driven solutions. As part of the Analytics practice, you will collaborate with a global network of colleagues skilled in leading statistical tools and applications. From data analysis to actionable insights, you will provide issue-based recommendations to help clients achieve high performance. Accenture is committed to investing in your learning and growth, supporting you in expanding your tech stack and certifications. In Applied Intelligence, you will execute projects in the context of business performance improvement initiatives, emphasizing sound analytical decision-making. Responsibilities include providing strategic advisory services, conducting market research, and developing data-driven recommendations to enhance business performance. The ideal candidate will have relevant experience in the domain, strong analytical and problem-solving skills, and the ability to thrive in a dynamic environment. In this role, you will be responsible for defining data requirements, cleaning and analyzing data, and developing AI/ML models. You should have at least 3 years of experience in Market Mix Modeling, proficiency in Statistical and Probabilistic methods, and hands-on experience with Python data science libraries. Additionally, you will work on developing and managing data pipelines, leveraging machine learning architectures, and deploying marketing mix models on cloud platforms. The desired candidate should have knowledge of SQL and cloud-based technologies, expertise in Market mix modeling techniques, and experience in data migration from cloud to Snowflake. Understanding of econometric/statistical modeling, machine learning algorithms, and proficiency in tools such as Excel, MS Word, and PowerPoint are essential requirements. This role offers the opportunity to work on innovative projects, grow your career, and gain leadership exposure. If you have 8 to 10 years of experience and a B.Com educational qualification, and if you possess the mentioned skills and expertise, we are looking for you to join our team at Accenture.,

As a Machine Learning Engineer, you will play a key role in developing and enhancing a Telecom Artificial Intelligence Product. This role requires a strong background in machine learning and deep learning, along with extensive experience in implementing advanced algorithms and models to solve complex problems. You will be working on cutting-edge technologies to develop solutions for anomaly detection, forecasting, event correlation, and fraud detection. Your responsibilities will include developing production-ready implementations of proposed solutions using various machine learning and deep learning algorithms. You will test these solutions on live customer data to ensure efficacy and robustness. Additionally, you will research and test novel machine learning approaches for large-scale distributed computing applications. In this role, you will be responsible for implementing and managing the full machine learning operations lifecycle using tools such as Kubeflow, MLflow, AutoML, and Kserve for model deployment. You will develop and deploy machine learning models using PyTorch and TensorFlow to ensure high performance and scalability. Furthermore, you will run and manage PySpark and Kafka on distributed systems with large-scale, non-linear network elements. To excel in this position, you should be proficient in Python programming and experienced with machine learning libraries such as Scikit-Learn and NumPy. Experience in time series analysis, data mining, text mining, and creating data architectures will be beneficial. You should also be able to utilize batch processing and incremental approaches to manage and analyze large datasets. As a Machine Learning Engineer, you will experiment with multiple algorithms, optimizing hyperparameters to identify the best-performing models. You will execute machine learning algorithms in cloud environments, leveraging cloud resources effectively. Continuous feedback gathering, model retraining, and updating will be essential to maintain and improve model performance. Moreover, you should have expertise in network characteristics, transformer architectures, GAN AI techniques, and end-to-end machine learning projects. Experience with leading supervised and unsupervised machine learning methods and familiarity with Python packages like Pandas, Numpy, and DL frameworks like Keras, TensorFlow, PyTorch are required. Knowledge of Big Data tools and environments, as well as MySQL/NoSQL databases, will be advantageous. You will collaborate with cross-functional teams of data scientists, software engineers, and stakeholders to integrate implemented systems into the SaaS platform. Your innovative thinking and creative ideas will contribute to improving the overall platform. Additionally, you will create use cases specific to the domain to solve business problems effectively. Ideally, you should have a Bachelor's degree in Science/IT/Computing or equivalent with at least 4 years of experience in a QA Engineering role. Strong quantitative and applied mathematical skills are essential, along with certification courses in Data Science/ML. In-depth knowledge of statistical techniques, machine learning techniques, and experience with Telecom Product development are preferred. Experience in MLOps is a plus for deploying developed models, and familiarity with scalable SaaS platforms is advantageous for this role.,

Who We Are Zinnia is the leading technology platform for accelerating life and annuities growth. With innovative enterprise solutions and data insights, Zinnia simplifies the experience of buying, selling, and administering insurance products. All of which enables more people to protect their financial futures. Our success is driven by a commitment to three core values: be bold, team up, deliver value and that we do. Zinnia has over $180 billion in assets under administration, serves 100+ carrier clients, 2500 distributors and partners, and over 2 million policyholders. Who You Are We are seeking a highly motivated Senior Data Scientist with strong technical expertise, business acumen, and strategic problem-solving abilities . In this role, you will independently own and build forecasting models. You will work closely with stakeholders across Product, Data Engineering & Analytics, and Business Strategy to identify opportunities to resolve business problems. This is a high-impact individual contributor role. What Youll Do Work in a dynamic and innovative company to develop cutting-edge solutions. Perform advanced data analytics to influence decision makers. Leverage data from diverse sources to provide insights and build new data driven tools. Partner with engineering teams to continuously improve our data quality. Develop machine learning based applications using supervised and unsupervised models using Python that optimize and personalize customer experiences or reduce manual effort on our internal teams through automated decision making. Develop and support models to enable things such as prescriptive insights, automated decisioning, and insights. Develop experiments to understand model impact, monitor live model analytics, and manage training and retraining pipelines. Work with stakeholders to intake complicated business problems and translate them into solvable data science projects. Partner with data engineering to take your model from development to deployed infrastructure. Brainstorm future use cases and contribute to the learning culture of the data science team. Partner with and mentor other data scientists and data analysts. Partner with multiple marketing teams, manage multiple projects and help conceptualize applications that directly drive company growth and strategy. You will connect machine learning applications to business needs and help facilitate process changes based on algorithmic solution implementation. What Youll Need You have Data Science experience building and validating machine learning and forecasting models in Python for a minimum of 5 years. You love performing advanced analytics to find insights and patterns. You have experience in supervised and unsupervised model techniques such as random forest, gradient boosting, support vector machines, k-means and hierarchical clustering, causal models, mixture models and experience in advanced modeling techniques such as reinforcement learning, neural networks, and natural language modeling. You have experience in delivering natural language projects utilizing techniques such as text summarization, topic modeling, entity extraction, semantic encoding, and valence analysis You have experience working in an agile business setting. You have experience with relational cloud databases like BigQuery and Snowflake and are comfortable working with unstructured datasets such as unstructured text. WHATS IN IT FOR YOU At Zinnia, you collaborate with smart, creative professionals who are dedicated to delivering cutting-edge technologies, deeper data insights, and enhanced services to transform how insurance is done. Visit our website at www.zinnia.com for more information. Apply by completing the online application on the careers section of our website. We are an Equal Opportunity employer committed to a diverse workforce. We do not discriminate based on race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability. Show more Show less

Genpact (NYSE: G) is a global professional services and solutions firm dedicated to shaping the future by delivering impactful outcomes. With a team of over 125,000 professionals spread across more than 30 countries, we are characterized by our inherent curiosity, entrepreneurial spirit, and commitment to creating enduring value for our clients. Fueled by our overarching purpose of continually striving towards a world that functions better for individuals, we partner with and enhance leading enterprises, including members of the prestigious Fortune Global 500. Our core competencies revolve around in-depth business and industry expertise, digital operational services, and proficiency in data, technology, and AI. We are currently seeking applications for the position of Business Analyst - Data Scientist to join our dynamic team. As a Business Analyst - Data Scientist at Genpact, you will play a pivotal role in the development and implementation of NLP (Natural Language Processing) models and algorithms, extracting actionable insights from textual data, and collaborating with cross-functional teams to deliver innovative AI solutions. **Responsibilities:** **Model Development:** - Proficiency in various statistical, machine learning, and ensemble algorithms. - Strong understanding of time series algorithms and forecasting use cases. - Ability to discern the strengths and weaknesses of different models and select appropriate ones for specific problems. - Proficiency in evaluating metrics and recommending suitable evaluation metrics for different problem types. **Data Analysis:** - Extracting meaningful insights from structured data. - Preprocessing data for machine learning/artificial intelligence applications. **Collaboration:** - Close collaboration with data scientists, engineers, and business stakeholders. - Providing technical guidance and mentorship to team members. **Integration and Deployment:** - Integrating machine learning models into production systems. - Implementing CI/CD pipelines for continuous integration and deployment. **Documentation and Training:** - Documenting processes, models, and results. - Providing training and support to stakeholders on NLP techniques and tools. **Qualifications we seek in you:** **Minimum Qualifications / Skills:** - Bachelor's degree in computer science, engineering, or a related field. - Proficient programming skills in Python and R. - Experience with data science frameworks such as SKLEARN and NUMPY. - Knowledge of machine learning concepts and frameworks like TensorFlow and PyTorch. - Strong problem-solving and analytical capabilities. - Excellent communication and collaboration skills. **Preferred Qualifications/Skills:** - Experience in predictive analytics and machine learning techniques. - Proficiency in Python/R or any other open-source programming language. - Building and implementing models, using algorithms, and running simulations with various tools. - Familiarity with visualization tools such as Tableau, Power BI, Qlikview, etc. - Proficiency in applied statistics skills, including distributions, statistical testing, regression, etc. - Knowledge and experience in various tools and techniques like forecasting, linear regression, logistic regression, machine learning algorithms (e.g., Random Forest, Gradient Boosting, SVM, XGBoost, Deep Learning), etc. - Experience with big data technologies (Hadoop, Spark). - Familiarity with cloud platforms like AWS, Azure, GCP. **Job Details:** **Title:** Business Analyst - Data Scientist **Primary Location:** India-Hyderabad **Education Level:** Bachelor's / Graduation / Equivalent **Job Posting:** Apr 1, 2025, 2:47:23 AM **Unposting Date:** May 1, 2025, 1:29:00 PM **Master Skills List:** Digital **Job Category:** Full Time,

You will be working as a Machine Learning Intern for a duration of 6 months with a stipend of 20k per month. The internship involves a hybrid mode of working, with 3 days in the office and 2 days working from home. Your primary responsibilities will include designing and implementing cutting-edge machine learning models for complex tabular and time series data problems. Additionally, you will be tasked with developing innovative feature engineering techniques to maximize the value extracted from datasets. Researching and applying state-of-the-art algorithms in areas like automated machine learning (AutoML) and neural architecture search will also be part of your role. Furthermore, you will optimize models for performance and scalability in resource-constrained environments, contribute to the development of the company's core ML infrastructure and pipelines, and collaborate on end-to-end ML projects from problem definition to deployment and monitoring. Your involvement in strategic discussions to identify new opportunities for ML applications within the business and conducting independent research to stay updated on the latest ML advancements for tabular and time series data will be crucial. To excel in this role, you should possess a strong theoretical understanding of machine learning concepts, statistical modeling, and optimization techniques. Proven experience in developing and deploying ML models for tabular and time series data, along with advanced programming skills in Python and expertise in ML libraries and frameworks, is essential. Proficiency in working with large-scale datasets and distributed computing environments, as well as experience with modern ML techniques such as gradient boosting, neural networks, and ensemble methods, are also required. Preferred qualifications include contributions to open-source ML projects or research publications, as well as experience with cloud-native ML development and deployment. This internship offers a unique opportunity to work on cutting-edge AI and blockchain intersection projects, contributing to the company's growth and innovation in the field of machine learning.,

About Info Edge InfoEdge’s mission is to create world-class platforms that transform lives by continuously innovating. Our products and services are built keeping our customers in mind. We always delight our customers by delivering superior value through enhanced offerings on the internet and other platforms. Through our continuous investment across various businesses, especially in cutting-edge technology, machine learning and artificial intelligence (AI), we have built a robust system that constantly increases our predictive powers on customer behavior, and optimizes and improves our systems. Our various teams tirelessly work together to solve problems, innovate, and create something to empower our customers. At Info Edge, people are our core competitive advantage and we will continue doing all that is needed to attract and retain the best available talent. About BU: Corporate Function – Data Science Designation: AI Scientist Desired Experience: 0-3 Year Required Educational Qualification : PhD/ M.Tech / B.Tech with relevant experience from Tier 1 Campus As AI Scientist you will: Develop algorithms and build systems to extract seemingly unseen trends and information from user content such as resumes, job description and profile information available through various sources and in different modalities such as numeric, structure and unstructured texts and images. Identify potential new business problems that can be solved through machine learning. Ideate, formulate, create metrics and execute on such problems and get buy in from business. Identify potential data-driven machine learning solutions to improve user experience through personalization and prediction of user preferences. Build intelligent systems to capture and model the vast amount of behavior data to enrich the content understanding with behavioral information. Identify the appropriate and cutting edge machine learning tools for various supervised and unsupervised tasks in the NLP, deep learning, semantic search, LTR space for building highly accurate and scalable recommendation systems and information retrieval solutions. Design solutions for scalable and real-time performance on a significantly large data set. Use big data technologies to optimally use infrastructure and improve performance. Participate in external forums /discussions, publish research papers, keep up-to-date on latest publications and build external/internal networks. Required Skills: Strong fundamental understanding and research experience in machine learning/Deep Learning/NLP/Information Retrieval/Artificial Intelligence areas. Strong applied knowledge of machine learning in solving real-world business problems with a significantly broad number of algorithms covering the landscape of classification, regression; discriminative, generative; supervised, unsupervised, semi-supervised; linear and non-linear dimensionality reduction, feature-extraction, feature selection, feature-learning. Industry experience in applying a variety of machine learning solutions to real-world large-scale data to build intelligent systems. An excellent problem solving skills with a research oriented approach. Ability to capture, manage, create pipelines and process Big Data Desired Skills: Ability to understand Business challenges and define solutions aligned to the needs. Why Join us: This is a unique opportunity to work on innovative and disruptive technologies that are shaping the future of the industry. We are looking for candidates who are willing to work passionately in a fast- paced environment and are ready to enhance their skills by learning something new. Being a part of the InfoEdge team, you will be engaged in innovations, product development, integration with mobile and social media, technology, research and development, quality assurance, sales and marketing. To learn more about Info Edge visit http://www.infoedge.in/

As a Senior Data Scientist in the Global Data Science & Advanced Analytics team at Colgate-Palmolive, your role will involve leading projects within the Analytics Continuum. You will be responsible for conceptualizing and developing machine learning, predictive modeling, simulations, and optimization solutions to address business questions with clear dollar objectives. Your work will have a significant impact on revenue growth management, price elasticity, promotion analytics, and marketing mix modeling. Your responsibilities will include: - Conceptualizing and building predictive modeling solutions to address business use cases - Applying machine learning and AI algorithms to develop scalable solutions for business deployment - Developing end-to-end business solutions from data extraction to statistical modeling - Conducting model validations and continuous improvement of algorithms - Deploying models using Airflow and Docker on Google Cloud Platforms - Leading pricing, promotion, and marketing mix initiatives from scoping to delivery - Studying large datasets to discover trends and patterns - Presenting insights in a clear and interpretable manner to business teams - Developing visualizations using frameworks like Looker, PyDash, Flask, PlotLy, and streamlit - Collaborating closely with business partners across different geographies To qualify for this position, you should have: - A degree in Computer Science, Information Technology, Business Analytics, Data Science, Economics, or Statistics - 5+ years of experience in building statistical models and deriving insights - Proficiency in Python and SQL for coding and statistical modeling - Hands-on experience with statistical models such as linear regression, random forest, SVM, logistic regression, clustering, and Bayesian regression - Knowledge of GitHub, Airflow, and visualization frameworks - Understanding of Google Cloud and related services like Kubernetes and Cloud Build Preferred qualifications include experience with revenue growth management, pricing, marketing mix models, and third-party data. Knowledge of machine learning techniques and Google Cloud products will be advantageous for this role. Colgate-Palmolive is committed to fostering an inclusive environment where diversity is valued, and every individual is treated with respect. As an Equal Opportunity Employer, we encourage applications from candidates with diverse backgrounds and perspectives. If you require accommodation during the application process due to a disability, please complete the request form provided. Join us in building a brighter, healthier future for all.,

As a NLP & Generative AI Engineer at Gigaforce, you will be part of our dynamic AI/ML team based in Noida, working on cutting-edge technologies to revolutionize the insurance claims processing industry. We are a California-based InsurTech company with a strong focus on innovation and digital transformation in the Property and Casualty sector. You must have a minimum of 2 years of hands-on experience in traditional machine learning, natural language processing, and modern generative AI techniques to be considered for this role. We are looking for individuals who are passionate about deploying GenAI solutions to production, working with open-source technologies, and handling document-centric pipelines efficiently. Your main responsibilities will include building and deploying NLP and GenAI-driven products focusing on document understanding, summarization, classification, and retrieval. You will be designing and implementing models using LLMs such as GPT, T5, and BERT, along with working on scalable, cloud-based pipelines for training, serving, and monitoring models. Collaboration is key at Gigaforce, and you will work closely with cross-functional teams including data scientists, ML engineers, product managers, and developers. Additionally, you will contribute to open-source tools and frameworks in the ML ecosystem, deploying production-ready solutions using MLOps practices, and working on distributed/cloud systems with GPU-accelerated workflows. To be successful in this role, you should have a strong grasp of traditional ML algorithms, NLP fundamentals, and modern NLP & GenAI models. Proficiency in Python, experience with cloud platforms like AWS SageMaker, GCP, or Azure ML, and familiarity with MLOps tools and distributed computing are essential. Experience with document processing pipelines and understanding insurance-related documents is a plus. If you are looking for a challenging role where you can lead the design, development, and deployment of innovative AI/ML solutions in the insurance industry, then this position at Gigaforce is the perfect opportunity for you. Join us in our mission to transform the claims lifecycle into an intelligent, end-to-end digital experience.,

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.,

Genpact is a global professional services and solutions firm with over 125,000 employees in 30+ countries. Driven by curiosity, entrepreneurial agility, and the desire to create value for clients, we serve leading enterprises worldwide with deep business knowledge, digital operations services, and expertise in data, technology, and AI. Our purpose is the relentless pursuit of a world that works better for people. We are currently seeking a Business Analyst - Data Scientist to join our team. In this role, you will be responsible for developing and implementing NLP models and algorithms, extracting insights from textual data, and working collaboratively with cross-functional teams to deliver AI solutions. Responsibilities: Model Development: - Proficiency in various statistical, ML, and ensemble algorithms - Strong understanding of Time series algorithms and forecasting use cases - Ability to evaluate model strengths and weaknesses for different problems Data Analysis: - Extracting meaningful insights from structured data - Preprocessing data for ML/AI applications Collaboration: - Working closely with data scientists, engineers, and business stakeholders - Providing technical guidance and mentorship to team members Integration and Deployment: - Integrating ML models into production systems - Implementing CI/CD pipelines for continuous integration and deployment Documentation and Training: - Documenting processes, models, and results - Providing training and support on NLP techniques and tools to stakeholders Qualifications: Minimum Qualifications / Skills: - Bachelor's degree in computer science, Engineering, or a related field - Strong programming skills in Python and R - Experience with DS frameworks (SKLEARN, NUMPY) - Knowledge of machine learning concepts and frameworks (TensorFlow, PyTorch) - Strong problem-solving and analytical skills - Excellent communication and collaboration abilities Preferred Qualifications / Skills: - Experience in Predictive Analytics and Machine Learning techniques - Proficiency in Python/R/Any other open-source programming language - Knowledge of visualization tools such as Tableau, Power BI, Qlikview, etc. - Applied statistics skills - Experience with big data technologies (Hadoop, Spark) - Knowledge of cloud platforms (AWS, Azure, GCP) If you are passionate about leveraging your skills in data science and analytics to drive innovation and value creation, we encourage you to apply for this exciting opportunity at Genpact.,

Genpact (NYSE: G) is a global professional services and solutions firm delivering outcomes that shape the future. Our 125,000+ people across 30+ countries are driven by our innate curiosity, entrepreneurial agility, and desire to create lasting value for clients. Powered by our purpose the relentless pursuit of a world that works better for people we serve and transform leading enterprises, including the Fortune Global 500, with our deep business and industry knowledge, digital operations services, and expertise in data, technology, and AI. Inviting applications for the role of Business Analyst Data Scientist In this role, the person is responsible for developing and implementing NLP models and algorithms, extracting insights from textual data, and collaborating with cross-functional teams to deliver AI solutions. Responsibilities Model Development: Familiar with different statistical, ML and ensemble algorithms Proficient with Time series algorithms and forecasting usecases Understand model specific strengths and weaknesses and know-how of suitable and unsuitable models for different problems Understand evaluation metrics and recommend the correct evaluation metric for a problem type Data Analysis: Extract meaningful insights from structured data. Preprocess data for ML / AI applications Collaboration: Work closely with data scientists, engineers, and business stakeholders. Provide technical guidance and mentorship to team members. Integration and Deployment: Integrate ML models into production systems. Implement CI/CD pipelines for continuous integration and deployment. Documentation and Training: Document processes, models, and results. Provide training and support to stakeholders on NLP techniques and tools. Qualifications we seek in you! Minimum Qualifications / Skills Bachelor's degree in computer science, Engineering, or a related field. Strong programming skills in Python and R Experience with DS frameworks (SKLEARN, NUMPY). Knowledge of machine learning concepts and frameworks (TensorFlow, PyTorch). Strong problem-solving and analytical skills. Excellent communication and collaboration abilities. Preferred Qualifications/ Skills Predictive Analytics Experience inMachine Learning techniques Experience in Python/R/ Any other open-source programming language Building and implementing models, using/creating algorithms and creating/running simulations using a variety of Tools Good to have - Experience in visualization tools such as Tableau, Power BI, Qlikview etc. Good applied statistics skills, such as distributions, statistical testing, regression, etc. Knowledge and experience of tools/techniques: Forecasting, Linear Regression, Logistic Regression, Regularization, Segmentation (Decision Trees, CHAID, CART), Cluster Analysis, Factor Analysis, variable screening, Machine Learning Random Forest, Gradient Boosting, SVM, XGBoost, Deep Learning etc. Experience with big data technologies (Hadoop, Spark). Knowledge of cloud platforms (AWS, Azure, GCP). Job Business Analyst Primary Location India-Hyderabad Education Level Bachelor's / Graduation / Equivalent Job Posting Apr 1, 2025, 8:47:23 AM Unposting Date May 1, 2025, 7:29:00 PM Master Skills List Digital Job Category Full Time,

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.