107 Random Forest Jobs - Page 3

The Associate Manager, Compliance Analytics supports the development and implementation of compliance analytics across the global compliance organization. You will be responsible for designing and developing analytical solutions, generating insights, and fostering a culture of ethics and integrity. Your role will involve transforming data from multiple systems, designing the analytics approach, and executing the analytics. Your responsibilities will include designing, developing, and maintaining analytics to provide business insights, enabling risk-intelligent decisions, informing compliance risk assessment processes, and supporting remediation activities. You will be involved in scoping, gathering requirements, developing analytics models, validating and testing models, and communicating results to stakeholders for analytics projects. Additionally, you will support the execution of analytics initiatives to enhance the Global Compliance program and provide actionable insights through data and analysis to achieve business objectives. Furthermore, you will contribute to the development of standardized analytics processes and frameworks, including documentation and validation of work. You will also be responsible for setting up sustainable analytics solutions, including data pipelines and automated refresh schedules as necessary. Collaboration with compliance officers, IT, and stakeholders to understand business objectives and provide reliable and accurate reports, insights, and analysis to inform decision-making is an essential aspect of this role. As part of your duties, you will lead a culture of continuous improvement by enhancing existing databases, data collection methods, statistical methods, technology, procedures, and training. You will partner with data custodians and process experts to ensure the quality of data and definitions to support the building of reliable data models and analysis. Additionally, coaching and developing junior team members will be a key component of this role. To qualify for this position, you should have 8+ years of relevant work experience in Python, Advanced SQL, R, Azure, Databricks, PySpark, and PowerBI. A strong knowledge and experience in advanced analytics tools and languages to analyze large data sets from multiple sources are required. A BTech in Computer Science, IT, MSc in Mathematics/Statistics, or equivalent courses from an accredited university is necessary. You should possess a strong understanding of algorithms, mathematical models, statistical techniques, data mining, and experience implementing statistical and machine learning models. Experience with analyzing accounting and other financial data, as well as demonstrating excellent ability to exercise discretion and maintain confidentiality, are essential. Knowledge and experience with data transformation and cleansing, data modeling, and database concepts are also preferred.,

Why would you like to join us? TransOrg Analytics specializes in Data Science, Data Engineering and Generative AI, providing advanced analytics solutions to industry leaders and Fortune 500 companies across India, US, APAC and the Middle East. We leverage data science to streamline, optimize, and accelerate our clients' businesses. Visit at www.transorg.com to know more about us. What do we expect from you? - Analyze & interpret data and communicate results to clients, often with the aid of mathematical/statistical techniques and software. - Data exploration, statistical/ predictive modelling, data analysis and hypothesis testing. Design, development and deployment of Predictive models and frameworks. - Complex statistical concepts are explained in a way that clients can understand and advice on strategy. - Overall data analytics strategy and business development. - Responsible for providing thought leadership and support to the team to develop best in class analytics solutions for clients. - Responsible for managing existing relationships with multiple clients in various industries. - Responsible for working closely with the senior management in developing and implementing strategic plans. Team Development: - Manage a team of data Scientists. Lead team members, including personal development and set work direction. - Lead team members, including personal development and set work direction. - Group development by building expertise in new domains and processes. - Coaching and mentoring team members. - Responsible for productivity, utilization and quality of output of the group. - Development of training modules and imparting training to the group. Project Delivery: - Lead analytics engagements and responsible for delivering the analytics solutions required across multiple clients & projects. - Provide thought leadership in a number of areas, including predictive modeling, customer segmentation, reporting & analysis, data processing and cleansing. - Demonstrate strong functional expertise by providing content leadership on projects. - Hands-on experience in implementing machine-learning algorithms. - Improve existing delivery processes and lead automation where applicable. What are we looking for? - Bachelor's in Computer Science/ Engineering, Statistics, Math or any other relevant degree. - 5-9 years of total experience with at least 3+ yrs. of relevant experience in data science/technical experience. - Experience on multiple modeling techniques -Logistic Regression, Linear Regression, Random Forest, Boosting, Neural Networks etc. - Hands-on experience with Python and SQL is a must. - Experience with data visualization tools like Tableau or Power BI. - Team and client management experience. - Experience of stakeholder management - Experience in working with unstructured data and text analytics. - Must have a passion for data, structured and unstructured. - Should have sound experience in data mining and data analysis. Good presentation skills. -Track record of managing data project delivery including ability to meet deadlines, overcome challenges, manage stakeholder expectations, and produce clear deliverables -Strong problem-solving skills with a keen attention to detail. Ability to think critically and provide data-backed insights. - Excellent communication skills, both verbal and written. -Understanding of Cloud Platforms (e.g. Azure / AWS/GCP) and ability to use them for developing, training and testing deep learning models ( good to have) -Familiarity with cloud-based data warehousing platforms (snowflake) ( good to have)

You will be joining a leading Manufacturing company in Bengaluru (Bellandur Area) for a Full-Time role as a Data Scientist. As a member of the team, you will be responsible for various Data Science projects including Demand Forecasting, GenAI, Cross Sell, Churn Analytics, and Visual Analytics. Your main responsibilities will revolve around Data Analysis and Modeling, where you will work on collecting, cleaning, and preprocessing large datasets from manufacturing systems and sensors. You will develop and implement advanced statistical models and machine learning algorithms to analyze the data, identify patterns, trends, and anomalies to drive process improvements and predict failures. Another key aspect of your role will involve Process Optimization, where you will analyze and optimize manufacturing processes to increase efficiency, reduce waste, and enhance product quality. You will also be required to conduct root cause analysis for production issues and collaborate with engineering and production teams to implement data-driven solutions. In addition, you will be responsible for Reporting and Visualization by creating and maintaining dashboards and reports to convey key metrics and insights to stakeholders. Your ability to visualize complex data sets in a clear and concise manner will be crucial for decision-making purposes. Furthermore, you will engage in Cross-functional Collaboration by working closely with teams across engineering, production, quality assurance, and IT. Your role will involve translating business requirements into data-driven solutions and presenting your findings to stakeholders. To excel in this role, you should hold a Bachelor's degree in Data Science, Computer Science, Engineering, Statistics, or a related field, with a preference for a Master's or PhD. You should have at least 3 years of experience in data science, analytics, or a related field, particularly in a manufacturing environment. Strong proficiency in statistical modeling, machine learning, and data mining techniques is essential. Additionally, experience working on Cross Sales projects using Random Forest, Logistic Regression, SVM, Clustering, and other methods is preferred. Proficiency in programming languages such as Python, R, or Java will be advantageous for this position.,

As part of the Data Science team in Colruyt, youwill have an opportunity to work with culturally diversified group ofindividuals, ensure business take strategic decisions by providing right datainsights. We are looking for an individual with Passion, Innovation, out of the box thinking to join our team . Build a portfolio of data opportunities for specific business partners based on your knowledge of the data and the business. Support business partners in translating their needs into specific research questions that can be addressed in a data science project. Apply techniques of data preparation, quality control, completeness, distribution, consistency, outliers, data, or variable transformation. Apply mathematical , statistical , and modeling techniques in a suitable environment. Use statistical analysis to support strategic decision-making . Support partners in the correct interpretation and application of analysis results. Training Business partners interpret analysis results independently or translating analysis results into the right actions. Collaborate closely with Data Science Engineers to support the entire data pipeline process. Evaluate the long-term validity of the analytical solution. Follow up on developments in the field of statistical analysis, mathematical modeling, optimization, and integrate these into practice. Requirements Should have 12+ years of working experience in Data-related projects. At least 7+ years of relevant experience as a Data Scientist. In-depth knowledge of statistical methods for data analysis, interpretation , and application of these techniques to solve a business problem. Experience in applying a variety of analytical algorithms , including but not limited to linear and logistic regression, Bayesian analysis, decision trees, random forest, boosting techniques, forecasting, time series, clustering, neural networks, and others. Proficiency in Python is expected to perform Data Science activities. Strong analytical and problem-solving skills . Ability to work in a team-oriented, collaborative environment . Excellent communication and interpersonal skills Experiencein text mining, NLP, understanding of image processing. Bachelors or masters degree in a relevant field such as Statistics, AI / ML / NLP is an added value.

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,

-Build scalable ML pipelines (data ingestion to deployment). -Expertise in Python, pandas, scikit-learn, xgboost/lightgbm. -Strong grasp of model evaluation, validation, and generalisation. -Docker/MLflow for orchestration; AWS/GCP deployment.

Job Description: AI Developer Fresher Location: Bangalore Company: MagicBox Cybersec Pvt. Ltd. Employment Type: Full-time | Entry-level Position Overview: We're MagicBox Cybersec, and we're building a powerful Cybersecurity in a Box a fully automated, AI- driven platform to detect threats, prevent intrusions, and ensure compliance. We're on the hunt for fresh minds who think logically, solve problems creatively, and love building smart systems that make the digital world safer. Key Responsibilities: • • • • Build and train AI/ML models for threat detection, anomaly detection, and behavioral analysis. Develop intelligent automation pipelines for cybersecurity operations. Work closely with AI & security experts to integrate models into real-time environments. Apply your skills in Python, ML libraries, and Linux to develop scalable solutions. Qualifications: • • Education o B.E./B.Tech/M.Tech in CS, AI, Data Science, or related fields o 01 year experience. Freshers are welcome! Skills o o o o o o o o o o Strong analytical and logical reasoning skills. Passion for AI/ML and interest in Cybersecurity. Familiarity with Python and frameworks like TensorFlow, PyTorch, or Scikit-learn. Comfortable in Linux environments (CLI, scripting). Project experience in AI/ML (college / online / hackathon / personal). Supervised/Unsupervised learning. Classification algorithms. Decision Trees. Random Forest. Deep Learning Algorithms(ANN, RNN, CNN, LSTMP, LLMs). Additional Qualifications: • • • Basic understanding of cybersecurity workflows (IDS, SIEM, etc.) Exposure to NLP or AI-based automation tools Git, Bash, or scripting experience What We Offer: • • • Work on cutting-edge AI Cybersecurity projects from day one. Mentorship and rapid learning opportunities. Flat structure, startup vibe, innovation-friendly culture. Ready to join us? Apply Now! Send your CV and a short note on your AI interests to: careers@magicboxcysec.com

Job Brief: We are looking for a highly motivated Data Scientist with strong experience in machine learning and deep learning . The role involves building scalable predictive models and working on business-critical analytics solutions across industries such as insurance, banking, and healthcare. Requirements: 3+ years of hands-on experience in ML model development. Strong in Python , Pandas , NumPy , Scikit-learn , and XGBoost Knowledge of time series modeling , model validation techniques , and feature selections Experience with deep learning frameworks: TensorFlow , Keras , or PyTorch . Strong analytical thinking and problem-solving skills.

Greetings From Straive!!! We have an immediate opportunity for Data Scientist!!! !! Immediate to 15 days joiners preferrable!! JD: Role & responsibilities Design, develop, and deploy machine learning models to detect and prevent fraudulent activities, such as Merchant Fraud, transactional fraud, account takeover, and identity theft Work with large datasets to identify patterns, trends, and anomalies that may indicate fraudulent activity Utilize data analytics tools and methodologies to conduct in-depth assessments and generate Fraud rules and reports on fraud trends (including first-party and third-party fraud). Collaborate with cross-functional teams, including risk management, operations, and compliance, to enhance fraud prevention measures. Monitor industry trends, regulatory changes, and best practices to continually enhance fraud prevention strategies. Preferred candidate profile Bachelor's degree in engineering, technology, computer science or related field. 3+ years of proven data analytics experience in fraud prevention, risk management, or a related field Familiarity with fraud detection software, risk assessment methodologies, and regulatory compliance. Strong experience in SQL or Python Excellent communication and presentation skills with the ability to convey complex information clearly and concisely. Detail-oriented with a proactive mindset toward problem-solving and risk mitigation. Ability to work collaboratively in a cross-functional team environment. Thanks & Regards Human Resources Straive

Produce written reports, problem statements, methods interpretation & business implications Data Analysis & Data Science using Agile principles Analyze claims, cases, data requirements Build models of severity analysis Exp Insurance Domain or Project Required Candidate profile Exp in EDA, Azure MS DevOps Snowflake, Databricks, Python/Spark, CI/CD, Sci-Kit Learn, Git AI implementation Algorithms Agile Principles Business & Data Analysis Statistics Random Forest Case Study

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

Management Level Definition: Contributions impact technical components of HPE products, solutions, or services regularly and sustainable. Applies advanced subject matter knowledge to solve complex business issues and is regarded as a subject matter expert. Provides expertise and partnership to functional and technical project teams and may participate in cross-functional initiatives. Exercises significant independent judgment to determine best method for achieving objectives. May provide team leadership and mentoring to others. What you will do: Experiment, design, develop and maintain machine learning models and pipelines with a high potential for value and scale. Collaborate with other ML engineers, data scientists, product managers, and other engineers to ensure successful implementation of machine learning solutions. Perform research and testing to develop or customize machine learning algorithms; conduct model training and evaluation as needed; integrate, test, tune and monitor the solutions developed. Research and evaluate new technologies and tools for machine learning. Maintain and update existing machine learning systems. Hands-on develop, productionize, and operate Machine Learning models and pipelines at scale, including both batch and real-time use cases. Work with large scale structured and unstructured data, build and continuously improve cutting edge Machine Learning models. Leads the project team for design and development of complex products and platforms, including solution design, analysis, coding, testing, and integration for building efficient, scalable and robust cloud subsystems. Reviews and evaluates designs, test plans, and develops code for compliance with cloud design and development guidelines and standards. Provides tangible feedback to improve product quality and mitigate risks. Represents the engineering team in various technical forums and provides guidance and mentoring to less-experienced team members. Drives innovation and integration of new technologies into projects and activities in the software systems design organization. Analyzes science, engineering, business, and other data processing problems to develop and implement solutions to complex application problems, system administration issues, or network concerns. What you will need: Bachelor's or master's degree in computer science, engineering, information systems, or closely related quantitative discipline. Typically, 7-15 years experience. Knowledge and Skills: Strong programming skills in Python & preferrable familiar with Golang Understanding microservice architecture and how they can be built in a containerized, Kubernetes-managed environment is central to all modern cloud-native applications. Designing and integrating software systems running on multiple platform types into the overall architecture. Evaluating forms and processes for software systems testing and methodology, including writing and executing test plans, debugging, and testing scripts and tools. Excellent written and verbal communication skills. Ability to effectively communicate product architectures and design proposals at senior management levels.

Role Overview: As a Data Scientist within IBM's Chief Analytics Office, you will support AI-driven projects across the enterprise. You will apply your technical skills in AI, machine learning, and data analytics to assist in implementing data-driven solutions that align with business goals. This role involves working with team members to translate data insights into actionable recommendations. Key Responsibilities: Technical Execution and Leadership: Develop and deploy AI models and data analytics solutions. Support the implementation and optimization of AI-driven strategies per business stakeholder requirements. Help refine data-driven methodologies for transformation projects. Data Science and AI: Design and implement machine learning solutions and statistical models, from problem formulation through deployment, to analyze complex datasets and generate actionable insights. Learn and utilize cloud platforms to ensure the scalability of AI solutions. Leverage reusable assets and apply IBM standards for data science and development. Project Support: Lead and contribute to various stages of AI and data science projects, from data exploration to model development. Monitor project timelines and help resolve technical challenges. Design and implement measurement frameworks to benchmark AI solutions, quantifying business impact through KPIs. Collaboration: Ensure alignment to stakeholders’ strategic direction and tactical needs. Work with data engineers, software developers, and other team members to integrate AI solutions into existing systems. Contribute technical expertise to cross-functional teams. Required education Bachelor's Degree Preferred education Master's Degree Required technical and professional expertise Experience: 2-4 yearsof experience in data science, AI, or analytics with a focus on implementing data-driven solutions Experience with data cleaning, data analysis, A/B testing, and data visualization Experience with AI technologies through coursework or projects Technical Skills: Proficiency in SQL and Python for performing data analysis and developing machine learning models Knowledge of common machine learning algorithms and frameworkslinear regression, decision trees, random forests, gradient boosting (e.g., XGBoost, LightGBM), neural networks, and deep learning frameworks such as TensorFlow and PyTorch Experience with cloud-based platforms and data processing frameworks Understanding of large language models (LLMs) Familiarity with IBM’s watsonx product suite Familiarity with object-oriented programming Analytical Skills: Strong problem-solving abilities and eagerness to learn Ability to work with datasets and derive insights Other : Good communication skills, with the ability to explain technical concepts clearly. Enthusiasm for learning and applying new technologies Strong project management skills, with the ability to balance multiple initiatives, prioritize tasks effectively, and meet deadlines in a fast-paced environment Successful completion of Coding Assessment Preferred technical and professional experience Education: Bachelor’s or Master’s in Computer Science, Data Science, Statistics, or a related field is required; an advanced degree strongly preferred Advanced degree strongly preferred. * Good communication skills, with the ability to explain technical concepts clearly * Enthusiasm for learning and applying new technologies * Strong project management skills, with the ability to balance multiple initiatives, prioritize tasks effectively, and meet deadlines in a fast-paced environment * Successful completion of Coding Assessment

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

The ideal candidate must possess knowledge relevant to the functional area, and act as a subject matter expert in providing advice in the area of expertise, and also focus on continuous improvement for maximum efficiency. It is vital to focus on the high standard of delivery excellence, provide top-notch service quality and develop successful long-term business partnerships with internal/external customers by identifying and fulfilling customer needs. The candidate should be able to break down complex problems into logical and manageable parts in a systematic way, and generate and compare multiple options, and set priorities to resolve problems. The ideal candidate must be proactive, and go beyond expectations to achieve job results and create new opportunities. The role must positively influence the team, motivate high performance, promote a friendly climate, give constructive feedback, provide development opportunities, and manage career aspirations of direct reports. Communication skills are key here, to explain organizational objectives, assignments, and the big picture to the team, and to articulate team vision and clear objectives. Senior Process Manager Role and responsibilities: Understand business problem and requirements by building domain knowledge and translate to data science problem. Conceptualize and design cutting edge data science solution to solve the data science problem, apply design-thinking concepts. Identify the right algorithms, tech stack, sample outputs required to efficiently adder the end need. Prototype and experiment the solution to successfully demonstrate the value. Independently or with support from team, execute the conceptualized solution as per plan by following project management guidelines. Present the results to internal and client stakeholder in an easy to understand manner with great story telling, story boarding, insights and visualization. Help build overall data science capability for eClerx through support in pilots, pre sales pitches, product development, and practice development initiatives. Technical and Functional Skills: Bachelors degree in Computer Science with 7 to 10 years of work experience. Must have experience in Advance Analytics, Data Science, regression, forecasting, analytics, SQL, R, Python, decision tree, random forest, SAS, clustering classification. Ability to engage clients to understand business requirements and convert the same into technical/modelling problems for solution development. Demonstrate strong interpersonal skills and a comfort interacting with clients from the C-suite to marketing managers to technical specialists. Demonstrated knowledge of analytical/statistical techniques and their applications; a working knowledge of/experience in R and Python is a plus. Demonstrated excellent communications skills, both written and spoken, as well as being able to explain complex technical concepts in plain English. Ability to present results of statistical models in business language. Domain understanding of at least one preferably two verticals amongst Retail, Cable, Technology (not mandate). Knowledge of data visualization tools (Tableau, QlikView, etc.) is a plus. Demonstrate strong analytical and storytelling skills and the ability to find relevant stories from piles of reports. Ability to manage specific tasks to completion with minimal direction. Ideal candidate has been in a consulting role previously. Hands-on expertise on the applied statistical techniques including multi-variate regression, logistic regression, market-mix models, clustering, classification, survival, churn models, speech analytics, image analytics, etc. Ability to collaborate with onsite colleagues in the US & UK. Expert in handling large data, cleansing & preparation for modelling. Very high attention to detail and quality.

The ideal candidate must possess knowledge relevant to the functional area, and act as a subject matter expert in providing advice in the area of expertise, and also focus on continuous improvement for maximum efficiency. It is vital to focus on the high standard of delivery excellence, provide top-notch service quality and develop successful long-term business partnerships with internal/external customers by identifying and fulfilling customer needs. The candidate should be able to break down complex problems into logical and manageable parts in a systematic way, and generate and compare multiple options, and set priorities to resolve problems. The ideal candidate must be proactive, and go beyond expectations to achieve job results and create new opportunities. The role must positively influence the team, motivate high performance, promote a friendly climate, give constructive feedback, provide development opportunities, and manage career aspirations of direct reports. Communication skills are key here, to explain organizational objectives, assignments, and the big picture to the team, and to articulate team vision and clear objectives. Senior Process Manager Role and responsibilities: Understand business problem and requirements by building domain knowledge and translate to data science problem. Conceptualize and design cutting edge data science solution to solve the data science problem, apply design-thinking concepts. Identify the right algorithms, tech stack, sample outputs required to efficiently adder the end need. Prototype and experiment the solution to successfully demonstrate the value. Independently or with support from team, execute the conceptualized solution as per plan by following project management guidelines. Present the results to internal and client stakeholder in an easy to understand manner with great story telling, story boarding, insights and visualization. Help build overall data science capability for eClerx through support in pilots, pre sales pitches, product development, and practice development initiatives. Technical and Functional Skills: Bachelors degree in Computer Science with 7 to 10 years of work experience. Must have experience in Advance Analytics, Data Science, regression, forecasting, analytics, SQL, R, Python, decision tree, random forest, SAS, clustering classification. Ability to engage clients to understand business requirements and convert the same into technical/modelling problems for solution development. Demonstrate strong interpersonal skills and a comfort interacting with clients from the C-suite to marketing managers to technical specialists. Demonstrated knowledge of analytical/statistical techniques and their applications; a working knowledge of/experience in R and Python is a plus. Demonstrated excellent communications skills, both written and spoken, as well as being able to explain complex technical concepts in plain English. Ability to present results of statistical models in business language. Domain understanding of at least one preferably two verticals amongst Retail, Cable, Technology (not mandate). Knowledge of data visualization tools (Tableau, QlikView, etc.) is a plus. Demonstrate strong analytical and storytelling skills and the ability to find relevant stories from piles of reports. Ability to manage specific tasks to completion with minimal direction. Ideal candidate has been in a consulting role previously. Hands-on expertise on the applied statistical techniques including multi-variate regression, logistic regression, market-mix models, clustering, classification, survival, churn models, speech analytics, image analytics, etc. Ability to collaborate with onsite colleagues in the US & UK. Expert in handling large data, cleansing & preparation for modelling. Very high attention to detail and quality.

The ideal candidate must possess in-depth functional knowledge of the process area and apply it to operational scenarios to provide effective solutions. The role enables to identify discrepancies and propose optimal solutions by using a logical, systematic, and sequential methodology. It is vital to be open-minded towards inputs and views from team members and to effectively lead, control, and motivate groups towards company objects. Additionally, candidate must be self-directed, proactive, and seize every opportunity to meet internal and external customer needs and achieve customer satisfaction by effectively auditing processes, implementing best practices and process improvements, and utilizing the frameworks and tools available. Goals and thoughts must be clearly and concisely articulated and conveyed, verbally and in writing, to clients, colleagues, subordinates, and supervisors. Associate Process Manager Role and responsibilities: Understand business problem and requirements by building domain knowledge and translate to data science problem. Conceptualize and design cutting edge data science solution to solve the data science problem, apply design-thinking concepts. Identify the right algorithms, tech stack, sample outputs required to efficiently adder the end need. Prototype and experiment the solution to successfully demonstrate the value. Independently or with support from team, execute the conceptualized solution as per plan by following project management guidelines. Present the results to internal and client stakeholder in an easy to understand manner with great story telling, story boarding, insights and visualization. Help build overall data science capability for eClerx through support in pilots, pre sales pitches, product development, and practice development initiatives. Technical and Functional Skills: Bachelors degree in Computer Science with 4 to 6 years of work experience. Must have experience in Advance Analytics, Data Science, regression, forecasting, analytics, SQL, R, Python, decision tree, random forest, SAS, clustering classification. Ability to engage clients to understand business requirements and convert the same into technical/modelling problems for solution development. Demonstrate strong interpersonal skills and a comfort interacting with clients from the C-suite to marketing managers to technical specialists. Demonstrated knowledge of analytical/statistical techniques and their applications; a working knowledge of/experience in R and Python is a plus. Demonstrated excellent communications skills, both written and spoken, as well as being able to explain complex technical concepts in plain English. Ability to present results of statistical models in business language. Domain understanding of at least one preferably two verticals amongst Retail, Cable, Technology (not mandate). Knowledge of data visualization tools (Tableau, QlikView, etc.) is a plus. Demonstrate strong analytical and storytelling skills and the ability to find relevant stories from piles of reports. Ability to manage specific tasks to completion with minimal direction. Ideal candidate has been in a consulting role previously. Hands-on expertise on the applied statistical techniques including multi-variate regression, logistic regression, market-mix models, clustering, classification, survival, churn models, speech analytics, image analytics, etc. Ability to collaborate with onsite colleagues in the US & UK. Expert in handling large data, cleansing & preparation for modelling. Very high attention to detail and quality.

The candidate must possess in-depth functional knowledge of the process area and apply it to operational scenarios to provide effective solutions. He/she must be able to identify discrepancies and propose optimal solutions by using a logical, systematic, and sequential methodology. It is vital to be open-minded towards inputs and views from team members and to effectively lead, control, and motivate groups towards company objects. Additionally, he/she must be self-directed, proactive, and seize every opportunity to meet internal and external customer needs and achieve customer satisfaction by effectively auditing processes, implementing best practices and process improvements, and utilizing the frameworks and tools available. Goals and thoughts must be clearly and concisely articulated and conveyed, verbally and in writing, to clients, colleagues, subordinates and supervisors. Process Manager Role and responsibilities: Understand business problem and requirements by building domain knowledge and translate to data science problem. Conceptualize and design cutting edge data science solution to solve the data science problem, apply design-thinking concepts. Identify the right algorithms, tech stack, sample outputs required to efficiently adder the end need. Prototype and experiment the solution to successfully demonstrate the value. Independently or with support from team, execute the conceptualized solution as per plan by following project management guidelines. Present the results to internal and client stakeholder in an easy to understand manner with great story telling, story boarding, insights and visualization. Help build overall data science capability for eClerx through support in pilots, pre sales pitches, product development, and practice development initiatives. Technical and Functional Skills: Bachelors degree in Computer Science with 5+ years of work experience. Must have experience in Advance Analytics, Data Science, regression, forecasting, analytics, SQL, R, Python, decision tree, random forest, SAS, clustering classification. Ability to engage clients to understand business requirements and convert the same into technical/modelling problems for solution development. Demonstrate strong interpersonal skills and a comfort interacting with clients from the C-suite to marketing managers to technical specialists. Demonstrated knowledge of analytical/statistical techniques and their applications; a working knowledge of/experience in R and Python is a plus. Demonstrated excellent communications skills, both written and spoken, as well as being able to explain complex technical concepts in plain English. Ability to present results of statistical models in business language. Domain understanding of at least one preferably two verticals amongst Retail, Cable, Technology (not mandate). Knowledge of data visualization tools (Tableau, QlikView, etc.) is a plus. Demonstrate strong analytical and storytelling skills and the ability to find relevant stories from piles of reports. Ability to manage specific tasks to completion with minimal direction. Ideal candidate has been in a consulting role previously. Hands-on expertise on the applied statistical techniques including multi-variate regression, logistic regression, market-mix models, clustering, classification, survival, churn models, speech analytics, image analytics, etc. Ability to collaborate with onsite colleagues in the US & UK. Expert in handling large data, cleansing & preparation for modelling. Very high attention to detail and quality.

The candidate must possess in-depth functional knowledge of the process area and apply it to operational scenarios to provide effective solutions. He/she must be able to identify discrepancies and propose optimal solutions by using a logical, systematic, and sequential methodology. It is vital to be open-minded towards inputs and views from team members and to effectively lead, control, and motivate groups towards company objects. Additionally, he/she must be self-directed, proactive, and seize every opportunity to meet internal and external customer needs and achieve customer satisfaction by effectively auditing processes, implementing best practices and process improvements, and utilizing the frameworks and tools available. Goals and thoughts must be clearly and concisely articulated and conveyed, verbally and in writing, to clients, colleagues, subordinates, and supervisors. Process Manager Role and responsibilities: Collaborate with clients to understand their business objectives and provide analytic solutions that positively address their needs. Conduct discovery sessions, workshops and whiteboard sessions to identify, understand and define customer needs, objectives, roadmaps and/or business requirements to design solutions that can best address existing or prospective clients. Conducting stakeholder interviews and workshops to gather and prioritize business requirements. Analysing and documenting current business processes and systems. Identifying opportunities for process improvement, cost reduction, and efficiency gains. Translating business requirements into functional specifications for technical teams. Identify the right algorithms, tech stack, sample outputs required to efficiently adder the end need. Collaborating with stakeholders to validate requirements and ensure alignment with business goals. Supporting the implementation and testing of solutions to ensure they meet business needs. Technical and Functional skills: 5 years of experience as a customer facing business analyst with minimum graduation in any field. Analytical ExpertiseProficient in analysing business processes, systems, and requirements to identify areas for improvement and optimization. Communication Skills: Ability to effectively communicate with stakeholders from various backgrounds to gather requirements, facilitate meetings, and present findings. Problem-Solving Skills: Capable of identifying problems, proposing solutions, and implementing strategies to address business challenges. DocumentationSkilled in documenting business requirements, user stories, process flows, and other artefact to ensure clear communication and understanding among stakeholders. Data AnalysisComfortable with data analysis techniques and tools to derive insights and make data-driven recommendations. Domain KnowledgePossesses a deep understanding of the Hi-tech industry or Supply chain / logistics domain, enabling them to provide valuable insights and recommendations. Project ManagementFamiliarity with project management methodologies and practices to effectively manage project timelines, resources, and deliverables. Must have experience in Advance Analytics, Data Science, regression, forecasting, analytics, SQL, R, Python, decision tree, random forest, SAS, clustering classification. Hands-on expertise on the applied statistical techniques including multi-variate regression, logistic regression, market-mix models, clustering, classification, survival, churn models, speech analytics, image analytics, etc. Knowledge of data visualization tools like Power BI, Tableau, QlikSense etc. Demonstrate strong analytical and storytelling skills and the ability to find relevant stories from piles of reports. Very high attention to detail and quality.

Immediate Openings on Data Scientist _India Experience : 5 + Skill:- Data Scientist Location : India Notice Period :- Immediate . Employment Type: Contract . Job Description: Strong problem-solving skills with an emphasis on product development. Experience using statistical computer languages (R, Python, SLQ, etc.) to manipulate data and draw insights from large data sets. Experience working with and creating data architectures. Knowledge of a variety of machine learning techniques (clustering, decision tree learning, artificial neural networks, etc.) and their real-world advantages/drawbacks. Knowledge of advanced statistical techniques and concepts (regression, properties of distributions, statistical tests and proper usage, etc.) and experience with applications. Excellent written and verbal communication skills for coordinating across teams. A drive to learn and master new technologies and techniques. Were looking for someone with 5-7 years of experience manipulating data sets and building statistical models, has a Masters in Statistics, Mathematics, Computer Science or another quantitative field, and is familiar with the following software/tools: Coding knowledge and experience with several languages: C, C++, Java, JavaScript, etc. Knowledge and experience in statistical and data mining techniques: GLM/Regression, Random Forest, Boosting, Trees, text mining, social network analysis, etc. Experience querying databases and using statistical computer languages: R, Python, SLQ, etc. Experience using web services: Redshift, S3, Spark, etc. Experience creating and using advanced machine learning algorithms and statistics: regression, simulation, scenario analysis, modeling, clustering, decision trees, neural networks, etc. Experience analyzing data from 3rd party providers: Google Analytics, Crimson Hexagon, Facebook Insights, etc. Experience visualizing/presenting data for stakeholders using different tools. Working knowledge of message queuing (Kafka or Google Pub/Sub), stream processing, and highly scalable data stores.

A strong level of proficiency in python programming. Practical knowledge and working experience on Statistics and Operation Research methods. Practical knowledge and working experience in tools and frameworks like Flask, PySpark,Pytorch,tensorflow, keras, Databricks, OpenCV, Pillow/PIL, streamlit, d3js, dashplotly, neo4j. Hands on experience in Analytics/AI-ML AWS services like Sagemaker, Canvas, Bedrock. Good understanding of how to apply predictive and machine learning techniques like regression models, XGBoost, random forest, GBM, Neural Nets, SVM etc. Proficient with NLP techniques like RNN, LSTM and Attention based models and effectively handle readily available stanford, IBM, Azure, Open AI NLP models. Good understanding of SQL from a perspective of how to write efficient queries for pulling the data from database. Hands on experience on any version control tool (github, bitbucket). Experience of deploying ML models into production environment experience (MLOps) in any one of the cloud platforms like Azure and AWS. Understanding business needs / mapping it to the business processes. Hands on experience in agile project delivery. Good in conceptualizing and visualizing end to end business needs both at high level as well as detailed. Good in articulating the business needs. Good analytical and problem-solving skills. Good communication, listening and probing skills. Strong inter-personnel skills. Should collaborate with other team members and work as team. Job Description: Comprehend business issues and propose valuable business solutions. Design Factual or AI/profound learning models to address business issues. Design Statistical Models/ ML/DL models and deploy them for production. Formulate what information is accessible from where and how to augment it. Develop innovative graphs for data comprehension using d3js, dashplotly and neo4j. Preferred Certification: (Good to have) AWS Specialty Certification in Data Analytics, Machine Learning.

Requirement : Bachelor's Degree in Computer Science, Operations Research, Statistics, or related field. Knowledge of R, or Python Knowledge of building regression and classification models Familiarity with any or all of, Regularization methods: Lasso, Ridge Ensemble methods: Random Forest, Boosting Time Series analysis: Auto-regression, moving average, etc. Graphs modeling Support Vector Machines Decision trees Preferred : Master's or higher degrees. Industry experience in the field of Data Science. Participation in competitions like Kaggle, Netflix Data Challenge. Open source contributions in areas of Data Science (Machine Learning, Deep Learning, Statistical Learning). Worked on Scala and/or Spark. Understanding of generative AI concepts, such as transformers, diffusion models, and LLMs

In the IBM Chief Information Office,you wi be part of a dynamic team driving the future of AI and data science in arge-scae enterprise transformations. We offer a coaborative environment where your technica expertise wi be vaued, and your professiona deveopment wi be supported. Join us to work on chaenging projects, everage the atest technoogies, and make a tangibe impact on eading organisations. As a Data Scientist within IBM's Chief Information Office, you wi support AI-driven projects across the enterprise. You wi appy your technica skis in AI, machine earning, and data anaytics to assist in impementing data-driven soutions that aign with business goas. This roe invoves working with team members to transate data insights into actionabe recommendations. Key Responsibiities: Technica Execution and Leadership: Deveop and depoy AI modes and data anaytics soutions. Support the impementation and optimisation of AI-driven strategies per business stakehoder requirements. Hep refine data-driven methodoogies for transformation projects. Data Science and AI: Design and impement machine earning soutions and statistica modes, from probem formuation through depoyment, to anayse compex datasets and generate actionabe insights. Learn and utiise coud patforms to ensure the scaabiity of AI soutions. Leverage reusabe assets and appy IBM standards for data science and deveopment. Project Support: Lead and contribute to various stages of AI and data science projects, from data exporation to mode deveopment. Monitor project timeines and hep resove technica chaenges. Design and impement measurement frameworks to benchmark AI soutions, quantifying business impact through KPIs. Coaboration: Ensure aignment to stakehoders strategic direction and tactica needs. Work with data engineers, software deveopers, and other team members to integrate AI soutions into existing systems. Contribute technica expertise to cross-functiona teams. Required education Bacheor's Degree Preferred education Master's Degree Required technica and professiona expertise Bacheors or Masters in Computer Science, Data Science, Statistics, or a reated fied is required; an advanced degree is strongy preferred Experience: 5+ yearsof experience in data science, AI, or anaytics with a focus on impementing data-driven soutions Experience with data ceaning, data anaysis, A/B testing, and data visuaization Experience with AI technoogies through coursework or projects Technica Skis: Proficiency in SQL and Python for performing data anaysis and deveoping machine earning modes Knowedge of common machine earning agorithms and frameworksinear regression, decision trees, random forests, gradient boosting (e.g., XGBoost, LightGBM), neura networks, and deep earning frameworks such as TensorFow and PyTorch Experience with coud-based patforms and data processing frameworks Understanding of arge anguage modes (LLMs) Famiiarity with IBMs watsonx product suite Famiiarity with object-oriented programming Anaytica Skis: Strong probem-soving abiities and eagerness to earn

Job Title: Data Scientist Location: Bangalore, India Experience: 3+ Years Role & Responsibilities: We are looking for a highly motivated Data Scientist to join our analytics team in Bangalore. This role is ideal for individuals who possess strong machine learning and data engineering skills and are eager to solve complex problems in the financial technology space. You will work on developing predictive models, building scalable data solutions, and contributing to key decision-making processes. Design, build, and validate machine learning models including Logistic Regression, Random Forests, GBM, and Survival Models. Perform rigorous model evaluation using techniques such as K-Fold Cross Validation, Out-of-Time (OOT) validation, and X-Tab analysis. Utilize Python (via PyCharm/Jupiter), scikit-learn, PyTorch or TensorFlow for end-to-end model development. Analyse large datasets using SQL and Excel to derive actionable insights. Develop and deploy APIs to serve machine learning models in production environments. Apply statistical techniques such as mean/variance analysis, probability distributions, and simulations to drive model accuracy and relevance. (Optional) Work with lending-specific metrics such as vintage curves, roll forward tracking, and bounce rates to enhance financial models. Strong ML skills: Logistic, Random Forest, GBM, survival model, K fold test, OOT, X-Tab etc. Experience using scikit-learn, pytorch or tensor flow. Experience: 3+ Years Python and usage of PyCharm/ Jupiter, SQL, Excel. Well versed in API development - Strong mathematical ability. mean, variance, probability distributions, simulation etc. Understanding of lending metrics such as vintage curve, roll forward, bounces etc. (Good to have not mandatory) Engineering background preferred IIT/NIT plus not must. Prior experience in Lending Fintech preferred.

We're Hiring: Data Scientist Databricks & ML Deployment Expert Location: Mumbai/Pune Experience: 38 Years Apply Now! Are you passionate about deploying real-world machine learning solutions? We're looking for a versatile Data Scientist with deep expertise in Databricks, PySpark , and end-to-end ML deployment to drive impactful projects in the Retail and Automotive domains. What Youll Do Develop scalable ML models (Regression, Classification, Clustering) Deliver advanced use cases like CLV modeling , Predictive Maintenance , and Time Series Forecasting Design and automate ML workflows on Databricks using PySpark Build and deploy APIs to serve ML models (Flask, FastAPI, Django) Own model deployment and monitoring in production environments Work closely with Data Engineering and DevOps teams for CI/CD integration Optimize pipelines and model performance (code & infrastructure level) Must-Have Skills Strong hands-on with Databricks and PySpark Proven track record in ML model development & deployment (min. 2 production deployments) Solid grasp of Regression, Classification, Clustering & Time Series Proficiency in SQL , workflow automation, and ELT/ETL processes API development (Flask, FastAPI, Django) CI/CD, deployment automation, and ML pipeline optimization Familiarity with Medallion Architecture Domain Expertise Retail : CLV, Pricing, Demand Forecasting Automotive : Predictive Maintenance, Time Series Nice to Have MLflow, Docker, Kubernetes Cloud: Azure, AWS, or GCP If you're excited to build production-ready ML systems that create real business impact, we want to hear from you! Apply Now to chaity.mukherjee@celebaltech.com.