61 Arima Jobs - Page 2

Job Title: Associate Data Scientist Location: Mumbai Job Type: Full-time Experience: 0-6months About The Role We are seeking a highly motivated Associate Data Scientist with a strong passion for energy, technology, and data-driven decision-making. In this role, you will be responsible for developing and refining energy load forecasting models , analyzing customer demand patterns , and improving forecasting accuracy using advanced time series analysis and machine learning techniques . Your insights will directly support risk management, operational planning, and strategic decision-making across the company. If you thrive in a fast-paced, dynamic environment and enjoy solving complex data science challenges , we’d love to hear from you! Key Responsibilities Develop and enhance energy load forecasting models using time series forecasting, statistical modeling, and machine learning techniques. Analyze historical and real-time energy consumption data to identify trends and improve forecasting accuracy. Investigate discrepancies between forecasted and actual energy usage, providing actionable insights. Automate data pipelines and forecasting workflows to streamline processes across departments. Monitor day-over-day forecast variations and communicate key insights to stakeholders. Work closely with internal teams and external vendors to refine forecasting methodologies. Perform scenario analysis to assess seasonal patterns, anomalies, and market trends. Continuously optimize forecasting models, leveraging techniques like ARIMA, Prophet, LSTMs, and regression-based models. Qualifications & Skills 0-6months of experience in data science, preferably in energy load forecasting, demand prediction, or a related field. Strong expertise in time series analysis, forecasting algorithms, and statistical modeling. Proficiency in Python, with experience using libraries such as pandas, NumPy, scikit-learn, statsmodels, and TensorFlow/PyTorch. Experience working with SQL and handling large datasets. Hands-on experience with forecasting models like ARIMA, SARIMA, Prophet, LSTMs, XGBoost, and random forests. Familiarity with feature engineering, anomaly detection, and seasonality analysis. Strong analytical and problem-solving skills with a data-driven mindset. Excellent communication skills, with the ability to translate technical findings into business insights. Ability to work independently and collaboratively in a fast-paced, dynamic environment. Strong attention to detail, time management, and organizational skills. Preferred Qualifications (Nice To Have) Experience working with energy market data, smart meter analytics, or grid forecasting. Knowledge of cloud platforms (AWS) for deploying forecasting models. Experience with big data technologies such as Spark or Hadoop. Show more Show less

Job Description Vice President, Data Management & Quantitative Analysis I At BNY, our culture empowers you to grow and succeed. As a leading global financial services company at the center of the world’s financial system we touch nearly 20% of the world’s investible assets. Every day around the globe, our 50,000+ employees bring the power of their perspective to the table to create solutions with our clients that benefit businesses, communities and people everywhere. We continue to be a leader in the industry, awarded as a top home for innovators and for creating an inclusive workplace. Through our unique ideas and talents, together we help make money work for the world. This is what is all about. We’re seeking a future team member for the role of Vice President I to join our Data Management & Quantitative Analysis team. This role is located in Pune, MH or Chennai, TN (Hybrid). In this role, you’ll make an impact in the following ways: BNY Data Analytics Reporting and Transformation (“DART”) has grown rapidly and today it represents a highly motivated and engaged team of skilled professionals with expertise in financial industry practices, reporting, analytics, and regulation. The team works closely with various groups across BNY to support the firm’s Capital Adequacy, Counterparty Credit as well as Enterprise Risk modelling and data analytics; alongside support for the annual Comprehensive Capital Analysis and Review (CCAR) Stress Test. The Counterparty Credit Risk Data Analytics Team within DART designs and develops data-driven solutions aimed at strengthening the control framework around our risk metrics and reporting. For the Counterparty Credit Risk Data Analytics Team, we are looking for a Counterparty Risk Analytics Developer to support our Counterparty Credit Risk control framework. Develop analytical tools using SQL & Python to drive business insights Utilize outlier detection methodologies to identify data anomalies in the financial risk space, ensuring proactive risk management Analyze business requirements and translate them into practical solutions, developing data-driven controls to mitigate potential risks Plan and execute projects from concept to final implementation, demonstrating strong project management skills Present solutions to senior stakeholders, effectively communicating technical concepts and results Collaborate with internal and external auditors and regulators to ensure compliance with prescribed standards, maintaining the highest level of integrity and transparency. To be successful in this role, we’re seeking the following: A Bachelor's degree in Engineering, Computer Science, Data Science, or a related discipline (Master's degree preferred) At least 3 years of experience in a similar role or in Python development/data analytics Strong proficiency in Python (including data analytics, data visualization libraries) and SQL, basic knowledge of HTML and Flask. Ability to partner with technology and other stakeholders to ensure effective functional requirements, design, construction, and testing Knowledge of financial risk concepts and financial markets is strongly preferred Familiarity with outlier detection techniques (including Autoencoder method, random forest, etc.), clustering (k-means, etc.), and time series analysis (ARIMA, EWMA, GARCH, etc.) is a plus. Practical experience working with Python (Pandas, NumPy, Matplolib, Plotly, Dash, Scikit-learn, TensorFlow, Torch, Dask, Cuda) Intermediate SQL skills (including querying data, joins, table creation, and basic performance optimization techniques) Knowledge of financial risk concepts and financial markets Knowledge of outlier detection techniques, clustering, and time series analysis Strong project management skills Show more Show less

At BNY, our culture empowers you to grow and succeed. As a leading global financial services company at the center of the world’s financial system we touch nearly 20% of the world’s investible assets. Every day around the globe, our 50,000+ employees bring the power of their perspective to the table to create solutions with our clients that benefit businesses, communities and people everywhere. We continue to be a leader in the industry, awarded as a top home for innovators and for creating an inclusive workplace. Through our unique ideas and talents, together we help make money work for the world. This is what is all about. We’re seeking a future team member for the role of Vice President I to join our Data Management & Quantitative Analysis team. This role is located in Pune, MH or Chennai, TN (Hybrid). In this role, you’ll make an impact in the following ways: BNY Data Analytics Reporting and Transformation (“DART”) has grown rapidly and today it represents a highly motivated and engaged team of skilled professionals with expertise in financial industry practices, reporting, analytics, and regulation. The team works closely with various groups across BNY to support the firm’s Capital Adequacy, Counterparty Credit as well as Enterprise Risk modelling and data analytics; alongside support for the annual Comprehensive Capital Analysis and Review (CCAR) Stress Test. The Counterparty Credit Risk Data Analytics Team within DART designs and develops data-driven solutions aimed at strengthening the control framework around our risk metrics and reporting. For the Counterparty Credit Risk Data Analytics Team, we are looking for a Counterparty Risk Analytics Developer to support our Counterparty Credit Risk control framework. Develop analytical tools using SQL & Python to drive business insights Utilize outlier detection methodologies to identify data anomalies in the financial risk space, ensuring proactive risk management Analyze business requirements and translate them into practical solutions, developing data-driven controls to mitigate potential risks Plan and execute projects from concept to final implementation, demonstrating strong project management skills Present solutions to senior stakeholders, effectively communicating technical concepts and results Collaborate with internal and external auditors and regulators to ensure compliance with prescribed standards, maintaining the highest level of integrity and transparency. To be successful in this role, we’re seeking the following: A Bachelor's degree in Engineering, Computer Science, Data Science, or a related discipline (Master's degree preferred) At least 3 years of experience in a similar role or in Python development/data analytics Strong proficiency in Python (including data analytics, data visualization libraries) and SQL, basic knowledge of HTML and Flask. Ability to partner with technology and other stakeholders to ensure effective functional requirements, design, construction, and testing Knowledge of financial risk concepts and financial markets is strongly preferred Familiarity with outlier detection techniques (including Autoencoder method, random forest, etc.), clustering (k-means, etc.), and time series analysis (ARIMA, EWMA, GARCH, etc.) is a plus. Practical experience working with Python (Pandas, NumPy, Matplolib, Plotly, Dash, Scikit-learn, TensorFlow, Torch, Dask, Cuda) Intermediate SQL skills (including querying data, joins, table creation, and basic performance optimization techniques) Knowledge of financial risk concepts and financial markets Knowledge of outlier detection techniques, clustering, and time series analysis Strong project management skills Show more Show less

Job Title : Senior Data Scientist (SDS 2) Experience: 4+ years Location : Bengaluru (Hybrid) Company Overview: Akaike Technologies is a dynamic and innovative AI-driven company dedicated to building impactful solutions across various domains . Our mission is to empower businesses by harnessing the power of data and AI to drive growth, efficiency, and value. We foster a culture of collaboration , creativity, and continuous learning , where every team member is encouraged to take initiative and contribute to groundbreaking projects. We value diversity, integrity, and a strong commitment to excellence in all our endeavors. Job Description: We are seeking an experienced and highly skilled Senior Data Scientist to join our team in Bengaluru. This role focuses on driving innovative solutions using cutting-edge Classical Machine Learning, Deep Learning, and Generative AI . The ideal candidate will possess a blend of deep technical expertise , strong business acumen, effective communication skills , and a sense of ownership . During the interview, we look for a proven track record in designing, developing, and deploying scalable ML/DL solutions in a fast-paced, collaborative environment. Key Responsibilities: ML/DL Solution Development & Deployment: Design, implement, and deploy end-to-end ML/DL, GenAI solutions, writing modular, scalable, and production-ready code. Develop and implement scalable deployment pipelines using Docker and AWS services (ECR, Lambda, Step Functions). Design and implement custom models and loss functions to address data nuances and specific labeling challenges. Ability to model in different marketing scenarios of a product life cycle ( Targeting, Segmenting, Messaging, Content Recommendation, Budget optimisation, Customer scoring, risk and churn ), and data limitations(Sparse or incomplete labels, Single class learning) Large-Scale Data Handling & Processing: Efficiently handle and model billions of data points using multi-cluster data processing frameworks (e.g., Spark SQL, PySpark ). Generative AI & Large Language Models (LLMs): Leverage in-depth understanding of transformer architectures and the principles of Large and Small Language Models . Practical experience in building LLM-ready Data Management layers for large-scale structured and unstructured data . Apply foundational understanding of LLM Agents, multi-agent systems (e.g., Agent-Critique, ReACT, Agent Collaboration), advanced prompting techniques, LLM eval uation methodologies, confidence grading, and Human-in-the-Loop systems. Experimentation, Analysis & System Design: Design and conduct experiments to test hypotheses and perform Exploratory Data Analysis (EDA) aligned with business requirements. Apply system design concepts and engineering principles to create low-latency solutions capable of serving simultaneous users in real-time. Collaboration, Communication & Mentorship: Create clear solution outlines and e ffectively communicate complex technical concepts to stakeholders and team members. Mentor junior team members, providing guidance and bridging the gap between business problems and data science solutions. Work closely with cross-functional teams and clients to deliver impactful solutions. Prototyping & Impact Measurement: Comfortable with rapid prototyping and meeting high productivity expectations in a fast-paced development environment. Set up measurement pipelines to study the impact of solutions in different market scenarios. Must-Have Skills: Core Machine Learning & Deep Learning: In-depth knowledge of Artificial Neural Networks (ANN), 1D, 2D, and 3D Convolutional Neural Networks (ConvNets), LSTMs , and Transformer models. Expertise in modeling techniques such as promo mix modeling (MMM) , PU Learning , Customer Lifetime Value (CLV) , multi-dimensional time series modeling, and demand forecasting in supply chain and simulation. Strong proficiency in PU learning, single-class learning, representation learning, alongside traditional machine learning approaches. Advanced understanding and application of model explainability techniques. Data Analysis & Processing: Proficiency in Python and its data science ecosystem, including libraries like NumPy, Pandas, Dask, and PySpark for large-scale data processing and analysis. Ability to perform effective feature engineering by understanding business objectives. ML/DL Frameworks & Tools: Hands-on experience with ML/DL libraries such as Scikit-learn, TensorFlow/Keras, and PyTorch for developing and deploying models. Natural Language Processing (NLP): Expertise in traditional and advanced NLP techniques, including Transformers (BERT, T5, GPT), Word2Vec, Named Entity Recognition (NER), topic modeling, and contrastive learning. Cloud & MLOps: Experience with the AWS ML stack or equivalent cloud platforms. Proficiency in developing scalable deployment pipelines using Docker and AWS services (ECR, Lambda, Step Functions). Problem Solving & Research: Strong logical and reasoning skills. Good understanding of the Python Ecosystem and experience implementing research papers. Collaboration & Prototyping: Ability to thrive in a fast-paced development and rapid prototyping environment. Relevant to Have: Expertise in Claims data and a background in the pharmaceutical industry . Awareness of best software design practices . Understanding of backend frameworks like Flask. Knowledge of Recommender Systems, Representative learning, PU learning. Benefits and Perks: Competitive ESOP grants. Opportunity to work with Fortune 500 companies and world-class teams. Support for publishing papers and attending academic/industry conferences. Access to networking events, conferences, and seminars. Visibility across all functions at Akaike, including sales, pre-sales, lead generation, marketing, and hiring. Appendix Technical Skills (Must Haves) Having deep understanding of the following Data Processing : Wrangling : Some understanding of querying database (MySQL, PostgresDB etc), very fluent in the usage of the following libraries Pandas, Numpy, Statsmodels etc. Visualization : Exposure towards Matplotlib, Plotly, Altair etc. Machine Learning Exposure : Machine Learning Fundamentals, For ex: PCA, Correlations, Statistical Tests etc. Time Series Models, For ex: ARIMA, Prophet etc. Tree Based Models, For ex: Random Forest, XGBoost etc.. Deep Learning Models, For ex: Understanding and Experience of ConvNets, ResNets, UNets etc. GenAI Based Models : Experience utilizing large-scale language models such as GPT-4 or other open-source alternatives (such as Mistral, Llama, Claude) through prompt engineering and custom finetuning. Code Versioning Systems : Github, Git If you're interested in the job opening, please apply through the Keka link provided here: https://akaike.keka.com/careers/jobdetails/26215 Show more Show less

Description AWS Infrastructure Services owns the design, planning, delivery, and operation of all AWS global infrastructure. In other words, we’re the people who keep the cloud running. We support all AWS data centers and all of the servers, storage, networking, power, and cooling equipment that ensure our customers have continual access to the innovation they rely on. We work on the most challenging problems, with thousands of variables impacting the supply chain — and we’re looking for talented people who want to help. You’ll join a diverse team of software, hardware, and network engineers, supply chain specialists, security experts, operations managers, and other vital roles. You’ll collaborate with people across AWS to help us deliver the highest standards for safety and security while providing seemingly infinite capacity at the lowest possible cost for our customers. And you’ll experience an inclusive culture that welcomes bold ideas and empowers you to own them to completion. Do you love problem solving? Are you looking for real world Supply Chain challenges? Do you have a desire to make a major contribution to the future, in the rapid growth environment of Cloud Computing? Amazon Web Services is looking for a highly motivated, Data Scientist to help build scalable, predictive and prescriptive business analytics solutions that supports AWS Supply Chain and Procurement organization. You will be part of the Supply Chain Analytics team working with Global Stakeholders, Data Engineers, Business Intelligence Engineers and Business Analysts to achieve our goals. We are seeking an innovative and technically strong data scientist with a background in optimization, machine learning, and statistical modeling/analysis. This role requires a team member to have strong quantitative modeling skills and the ability to apply optimization/statistical/machine learning methods to complex decision-making problems, with data coming from various data sources. The candidate should have strong communication skills, be able to work closely with stakeholders and translate data-driven findings into actionable insights. The successful candidate will be a self-starter, comfortable with ambiguity, with strong attention to detail and ability to work in a fast-paced and ever-changing environment. Key job responsibilities Demonstrate thorough technical knowledge on feature engineering of massive datasets, effective exploratory data analysis, and model building using industry standard time Series Forecasting techniques like ARIMA, ARIMAX, Holt Winter and formulate ensemble model. Proficiency in both Supervised(Linear/Logistic Regression) and UnSupervised algorithms(k means clustering, Principle Component Analysis, Market Basket analysis). Experience in solving optimization problems like inventory and network optimization . Should have hands on experience in Linear Programming. Work closely with internal stakeholders like the business teams, engineering teams and partner teams and align them with respect to your focus area Detail-oriented and must have an aptitude for solving unstructured problems. You should work in a self-directed environment, own tasks and drive them to completion. Excellent business and communication skills to be able to work with business owners to develop and define key business questions and to build data sets that answer those questions Work with distributed machine learning and statistical algorithms to harness enormous volumes of data at scale to serve our customers About The Team Diverse Experiences Amazon values diverse experiences. Even if you do not meet all of the preferred qualifications and skills listed in the job description, we encourage candidates to apply. If your career is just starting, hasn’t followed a traditional path, or includes alternative experiences, don’t let it stop you from applying. Why AWS Amazon Web Services (AWS) is the world’s most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and never stopped innovating — that’s why customers from the most successful startups to Global 500 companies trust our robust suite of products and services to power their businesses. Work/Life Balance We value work-life harmony. Achieving success at work should never come at the expense of sacrifices at home, which is why we strive for flexibility as part of our working culture. When we feel supported in the workplace and at home, there’s nothing we can’t achieve. Inclusive Team Culture AWS values curiosity and connection. Our employee-led and company-sponsored affinity groups promote inclusion and empower our people to take pride in what makes us unique. Our inclusion events foster stronger, more collaborative teams. Our continual innovation is fueled by the bold ideas, fresh perspectives, and passionate voices our teams bring to everything we do. Mentorship and Career Growth We’re continuously raising our performance bar as we strive to become Earth’s Best Employer. That’s why you’ll find endless knowledge-sharing, mentorship and other career-advancing resources here to help you develop into a better-rounded professional. Basic Qualifications Masters with 5+ years of experience or Bachelors with 8+ years of experience in quantitative field (Computer Science, Mathematics, Machine Learning, AI, Statistics, Operational research or equivalent) Experience in Python, R or another scripting language; command line / notebook usage. Knowledge and expertise with Data modelling skills, SQL, MySQL, and Databases (RDBMS, NOSQL) Extensive knowledge and practical experience in several of the following areas: machine learning, statistics, Optimization using Linear Programming. Evidence of using of relevant statistical measures such as Hypothesis testing, confidence intervals, significance of error measurements, development and evaluation data sets, etc. in data analysis projects Excellent written and verbal communication skills for both technical and non-technical audiences Preferred Qualifications Experience in Python, Perl, or another scripting language Experience in a ML or data scientist role with a large technology company Functional knowledge of AWS platforms such as S3, Glue, Athena, Sagemaker, Lambda, EC2, Batch, Step Function. Experience in creating powerful data driven visualizations to describe your ML modeling results to stakeholders Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner. Company - ADSIPL - Karnataka Job ID: A2959646 Show more Show less

Entity :- Accenture Strategy & Consulting Job location :- Mumbai About S&C - Global Network :- Accenture Global Network - Data & AI practice help our clients grow their business in entirely new ways. Analytics enables our clients to achieve high performance through insights from data - insights that inform better decisions and strengthen customer relationships. From strategy to execution, Accenture works with organizations to develop analytic capabilities - from accessing and reporting on data to predictive modelling - to outperform the competition WHAT'S IN IT FOR YOU? Accenture CFO & EV team under Data & AI team has comprehensive suite of capabilities in Risk, Fraud, Financial crime, and Finance. Within risk realm, our focus revolves around the model development, model validation, and auditing of models. Additionally, our work extends to ongoing performance evaluation, vigilant monitoring, meticulous governance, and thorough documentation of models. Get to work with top financial clients globally Access resources enabling you to utilize cutting-edge technologies, fostering innovation with the world's most recognizable companies. Accenture will continually invest in your learning and growth and will support you in expanding your knowledge. You'll be part of a diverse and vibrant team collaborating with talented individuals from various backgrounds and disciplines continually pushing the boundaries of business capabilities, fostering an environment of innovation. What you would do in this role Engagement Execution Work independently/with minimal supervision in client engagements that may involve model development, validation, governance, strategy, transformation, implementation and end-to-end delivery of risk solutions for Accenture's clients. Ability to manage workstream of large projects / small projects with responsibilities of managing quality of deliverables for junior team members. Demonstrated ability of managing day to day interactions with the Client stakeholders Practice Enablement Guide junior team members. Support development of the Practice by driving innovations, initiatives. Develop thought capital and disseminate information around current and emerging trends in Risk. Qualifications Who we are looking for? 7 - 12 years of relevant Risk Analytics experience at one or more Financial Services firms, or Professional Services / Risk Advisory with significant exposure to one or more of the following areas: Development, validation, and audit of: Credit Risk- PD/LGD/EAD Models, CCAR/DFAST Loss Forecasting and Revenue Forecasting Models, IFRS9/CECL Loss Forecasting Models across Retail and Commercial portfolios Credit Acquisition/Behavior/Collections/Recovery Modeling and Strategies, Credit Policies, Limit Management, Acquisition Frauds, Collections Agent Matching/Channel Allocations across Retail and Commercial portfolios Regulatory Capital and Economic Capital Models Liquidity Risk Liquidity models, stress testing models, Basel Liquidity reporting standards Anti Money Laundering AML scenarios/alerts, Network Analysis Operational risk AMA modeling, operational risk reporting Conceptual understanding of Basel/CCAR/DFAST/CECL/IFRS9 and other risk regulations Experience in conceptualizing and creating risk reporting and dashboarding solutions. Experience in modeling with statistical techniques such as linear regression, logistic regression, GLM, GBM, XGBoost, CatBoost, Neural Networks, Time series ARMA/ARIMA, ML interpretability and bias algorithms etc. Programing Languages - SAS, R, Python, Spark, Scala etc., Tools such as Tableau, QlikView, PowerBI, SAS VA etc. Strong understanding of Risk function and ability to apply them in client discussions and project implementation. Academic Requirements: Masters degree in a quantitative discipline mathematics, statistics, economics, financial engineering, operations research or related field or MBA from top-tier universities. Strong academic credentials and publications, if applicable. Industry certifications such as FRM, PRM, CFA preferred. Excellent communication and interpersonal skills.

Our Purpose Mastercard powers economies and empowers people in 200+ countries and territories worldwide. Together with our customers, we’re helping build a sustainable economy where everyone can prosper. We support a wide range of digital payments choices, making transactions secure, simple, smart and accessible. Our technology and innovation, partnerships and networks combine to deliver a unique set of products and services that help people, businesses and governments realize their greatest potential. Title And Summary Senior Data Scientist, Product Data & Analytics Senior Data Scientist, Product Data & Analytics Our Vision: Product Data & Analytics team builds internal analytic partnerships, strengthening focus on the health of the business, portfolio and revenue optimization opportunities, initiative tracking, new product development and Go-To Market strategies. We are a hands-on global team providing scalable end-to-end data solutions by working closely with the business. We influence decisions across Mastercard through data driven insights. We are a team on analytics engineers, data architects, BI developers, data analysts and data scientists, and fully manage our own data assets and solutions. Are you excited about Data Assets and the value they bring to an organization? Are you an evangelist for data driven decision making? Are you motivated to be part of a Global Analytics team that builds large scale Analytical Capabilities supporting end users across the continents? Are you interested in proactively looking to improve data driven decisions for a global corporation? Role Responsible for developing data-driven innovative scalable analytical solutions and identifying opportunities to support business and client needs in a quantitative manner and facilitate informed recommendations / decisions. Accountable for delivering high quality project solutions and tools within agreed upon timelines and budget parameters and conducting post- implementation reviews. Contributes to the development of custom analyses and solutions, derives insights from extracted data to solve critical business questions. Activities include developing and creating predictive models, behavioural segmentation frameworks, profitability analyses, ad hoc reporting, and data visualizations. Able to develop AI/ML capabilities, as needed on large volumes of data to support analytics and reporting needs across products, markets and services. Able to build end to end reusable, multi-purpose AI models to drive automated insights and recommendations. Leverage open and closed source technologies to solve business problems. Work closely with global & regional teams to architect, develop, and maintain advanced reporting and data visualization capabilities on large volumes of data to support analytics and reporting needs across products, markets, and services. Support initiatives in developing predictive models, behavioural segmentation frameworks, profitability analyses, ad hoc reporting, and data visualizations. Translates client/ stakeholder needs into technical analyses and/or custom solutions in collaboration with internal and external partners, derive insights and present findings and outcomes to clients/stakeholders to solve critical business questions. Create repeatable processes to support development of modelling and reporting Delegate and reviews work for junior level colleagues to ensure downstream applications and tools are not compromised or delayed. Serves as a mentor for junior-level colleagues, and develops talent via ongoing technical training, peer review etc. All About You 6-8 years of experience in data management, data mining, data analytics, data reporting, data product development and quantitative analysis. Advanced SQL skills, ability to write optimized queries for large data sets. Experience on Platforms/Environments: Cloudera Hadoop, Big data technology stack, SQL Server, Microsoft BI Stack, Cloud, Snowflake, and other relevant technologies. Data visualization tools (Tableau, Domo, and/or Power BI/similar tools) experience is a plus Experience with data validation, quality control and cleansing processes to new and existing data sources. Experience on Classical and Deep Machine Learning Algorithms like Logistic Regression, Decision trees, Clustering (K-means, Hierarchical and Self-organizing Maps), TSNE, PCA, Bayesian models, Time Series ARIMA/ARMA, Random Forest, GBM, KNN, SVM, Bayesian, Text Mining techniques, Multilayer Perceptron, Neural Networks - Feedforward, CNN, NLP, etc. Experience on Deep Learning algorithm techniques, open-source tools and technologies, statistical tools, and programming environments such as Python, R, and Big Data platforms such as Hadoop, Hive, Spark, GPU Clusters for deep learning. Experience in automating and creating data pipeline via tools such as Alteryx, SSIS. Nifi is a plus Financial Institution or a Payments experience a plus Additional Competencies Excellent English, quantitative, technical, and communication (oral/written) skills. Ownership of end-to-end Project Delivery/Risk Mitigation Virtual team management and manage stakeholders by influence Analytical/Problem Solving Able to prioritize and perform multiple tasks simultaneously Able to work across varying time zone. Strong attention to detail and quality Creativity/Innovation Self-motivated, operates with a sense of urgency. In depth technical knowledge, drive, and ability to learn new technologies. Must be able to interact with management, internal stakeholders Corporate Security Responsibility All activities involving access to Mastercard assets, information, and networks comes with an inherent risk to the organization and, therefore, it is expected that every person working for, or on behalf of, Mastercard is responsible for information security and must. Abide by Mastercard’s security policies and practices. Ensure the confidentiality and integrity of the information being accessed. Report any suspected information security violation or breach, and Complete all periodic mandatory security trainings in accordance with Mastercard’s guidelines. Corporate Security Responsibility All Activities Involving Access To Mastercard Assets, Information, And Networks Comes With An Inherent Risk To The Organization And, Therefore, It Is Expected That Every Person Working For, Or On Behalf Of, Mastercard Is Responsible For Information Security And Must: Abide by Mastercard’s security policies and practices; Ensure the confidentiality and integrity of the information being accessed; Report any suspected information security violation or breach, and Complete all periodic mandatory security trainings in accordance with Mastercard’s guidelines. R-244065 Show more Show less

Job Description: We are looking for a Data Scientist with expertise in Python, Azure Cloud, NLP, Forecasting, and large-scale data processing. The role involves enhancing existing ML models, optimising embeddings, LDA models, RAG architectures, and forecasting models, and migrating data pipelines to Azure Databricks for scalability and efficiency. Key Responsibilities: Model Development Model Development & Optimisation Train and optimise models for new data providers, ensuring seamless integration. Enhance models for dynamic input handling. Improve LDA model performance to handle a higher number of clusters efficiently. Optimise RAG (Retrieval-Augmented Generation) architecture to enhance recommendation accuracy for large datasets. Upgrade Retrieval QA architecture for improved chatbot performance on large datasets. Forecasting & Time Series Modelling Develop and optimise forecasting models for marketing, demand prediction, and trend analysis. Implement time series models (e.g., ARIMA, Prophet, LSTMs) to improve business decision-making. Integrate NLP-based forecasting, leveraging customer sentiment and external data sources (e.g., news, social media). Data Pipeline & Cloud Migration Migrate the existing pipeline from Azure Synapse to Azure Databricks and retrain models accordingly - Note: this is required only for the AUB role(s) Address space and time complexity issues in embedding storage and retrieval on Azure Blob Storage. Optimise embedding storage and retrieval in Azure Blob Storage for better efficiency. MLOps & Deployment Implement MLOps best practices for model deployment on Azure ML, Azure Kubernetes Service (AKS), and Azure Functions. Automate model training, inference pipelines, and API deployments using Azure services. Experience: Experience in Data Science, Machine Learning, Deep Learning and Gen AI. Design, Architect and Execute end to end Data Science pipelines which includes Data extraction, data preprocessing, Feature engineering, Model building, tuning and Deployment. Experience in leading a team and responsible for project delivery. Experience in Building end to end machine learning pipelines with expertise in developing CI/CD pipelines using Azure Synapse pipelines, Databricks, Google Vertex AI and AWS. Experience in developing advanced natural language processing (NLP) systems, specializing in building RAG (Retrieval-Augmented Generation) models using Langchain. Deploy RAG models to production. Have expertise in building Machine learning pipelines and deploy various models like Forecasting models, Anomaly Detection models, Market Mix Models, Classification models, Regression models and Clustering Techniques. Maintaining Github repositories and cloud computing resources for effective and efficient version control, development, testing and production. Developing proof-of-concept solutions and assisting in rolling these out to our clients. Required Skills & Qualifications: Hands-on experience with Azure Databricks, Azure ML, Azure Synapse, Azure Blob Storage, and Azure Kubernetes Service (AKS). Experience with forecasting models, time series analysis, and predictive analytics. Proficiency in Python (NumPy, Pandas, TensorFlow, PyTorch, Statsmodels, Scikit-learn, Hugging Face, FAISS). Experience with model deployment, API optimisation, and serverless architectures. Hands-on experience with Docker, Kubernetes, and MLflow for tracking and scaling ML models. Expertise in optimising time complexity, memory efficiency, and scalability of ML models in a cloud environment. Experience with Langchain or equivalent and RAG and multi-agentic generation Location: DGS India - Bengaluru - Manyata N1 Block Brand: Merkle Time Type: Full time Contract Type: Permanent Show more Show less

Hi , We are hiring for the role of Management Associate so I am sharing the JD or the role of Management Associate for the FMCG MNC, based in Mumbai location . You'll be hired on the payroll of Ashkom Media India Pvt. Ltd. Kindly go through the attached JD and if interested revert me back with your feedback and updated resume. Designation : Management Associate Function : MPD Required Qualification : B. Pharm/M. Pharm Experience -With minimum 2 years experience in a similar discipline in a reputed pharma company Job Location- Chakala, Andheri-E, Mumbai 400099 Job description : 1) To raise Change control in Veeva GTRAQ QA system for MPD depts. in scope CCPs. Scope- CCPS to be raised for MPD teams located at different locations PAN India) 2) To maintain track of on-going/work in progress CCPs /closer of change controls 3) To keep track of timely completion of action items (In scope- CCPs raised by MPD )& to maintain action log of work completed/ongoing & pending action items. 4) Support the MPD Process/ADL technical team in making batch records & other MPD documentation. 5) QC Soft entries for report generation of various stability, Raw material samples, protocol printing. 6) Supporting MPD/ADL Team at Goa (through email & Team space, common folders) for - Segregation and sending laboratory waste for destruction. - Sending samples for outside testing with proper documentation - Support in updating destruction records of leftover stability samples. 7) To participate in other tasks assigned by MPD- team members e.g., TT document review 8) Supplier qualification technical document review, 9) To liaison with RM suppliers for receipt of material qualification document, safety document & its review.

Hi, Hi, We are hiring for r the role of Senior Construction Manager for the company name FMCG MNC , position based at Ahmedabad (Sanand) You'll be hired on the payroll of Ashkom Media India Pvt. Ltd. Kindly go through the attached JD and if interested revert me back with your feedback and updated resume. Roles & responsibilities- Providing services as: 'Managing & monitoring of procurement, design & construction activates as per P&G standards. Planning & tracking of project timelines & prepare & implementing of catch up plan of slipped off activities. Liasoning with Stakeholder, consultant & Supplier to deliver the project as per P&G Standards. Responsible to provide Value added services. Responsible to maintain Constructability tracker. Review of BIM model & Clash detection & share the best possibilities to suit as per site condition Maintain & review CSPA/CCIP documents. Lead CMO Team. Interested candidates drop their updated cv on sapna.b.ashkom@gmail.com Regards, Sapna Banger HR

Having clinical background, preferably working in the US healthcare domain. Review the medical records and apply for authorization with various insurance companies Calling experience & core authorization background is preferable.

Our client is one of the global banking firms which provides industry-focused services for clients across geographies. We are looking for a Principal Advisor to join our global Model Risk Management (MRM) team. As part of a collaborative, and dynamic team, you will be responsible for validating, reviewing, and challenging models across the bank to ensure compliance with regulatory guidelines and best practices. Some of the key responsibilities will include: Conduct comprehensive validations of models across Treasury, ALM, balance sheet forecasting, and credit risk. Review model design, data integrity, code accuracy, and stress testing frameworks. Prepare high-quality validation reports and documentation, adhering to internal and regulatory standards. Interact with model owners, users, data scientists, and global MRM teams to ensure robust oversight. Provide effective challenge and identify model risks and control gaps, recommending enhancements. Support audits, regulatory exams and ongoing model monitoring and governance. Stay current with regulatory trends (e.g., SR 11-7, OCC 2011–2012) and industry best practices. To be eligible for this role you will require: 5-12 years of experience in model development, validation or implementation within financial services. Proficiency in Python, R, SQL, and statistical methods (regression, ARIMA, etc.). Experience with Treasury, ALM, or balance sheet forecasting models is a plus. Strong understanding of model governance frameworks and regulatory expectations. Bachelor’s or master’s degree in statistics, mathematics, economics or a related quantitative field. Excellent written and verbal communication skills and the ability to mentor junior analysts. Please contact Malavika or email your cv directly in word format with Job ID: 14910 to Malavika@theedgepartnership.com Please note that due to the high number of applications, only shortlisted candidates will be contacted. If you do not hear from us in the next 7 business days, we regret to inform you that your application for this position was unsuccessful . Show more Show less

Required Skills: Successful candidates will have demonstrated the following skills and characteristics: Must Have: Proven expertise in supply chain analytics across domains such as demand forecasting, inventory optimization, logistics, segmentation, and network design Well versed and hands-on experience of working on optimization methods like linear programming, mixed integer programming, scheduling optimization. Having understanding of working on third party optimization solvers like Gurobi will be an added advantage Proficiency in forecasting techniques (e.g., Holt-Winters, ARIMA, ARIMAX, SARIMA, SARIMAX, FBProphet, NBeats) and machine learning techniques (supervised and unsupervised) Strong command of statistical modeling, testing, and inference Proficient in using GCP tools: BigQuery, Vertex AI, Dataflow, Looker Building data pipelines and models for forecasting, optimization, and scenario planning Strong SQL and Python programming skills; experience deploying models in GCP environment Knowledge of orchestration tools like Cloud Composer (Airflow) Nice to have: Familiarity with MLOps, containerization (Docker, Kubernetes), and orchestration tools (e.g., Cloud composer) Strong communication and stakeholder engagement skills at the executive level Roles and Responsibilities: Assist analytics projects within the supply chain domain, driving design, development, and delivery of data science solutions Develop and execute on project & analysis plans under the guidance of Project Manager Interact with and advise consultants/clients in US as a subject matter expert to formalize data sources to be used, datasets to be acquired, data & use case clarifications that are needed to get a strong hold on data and the business problem to be solved Drive and Conduct analysis using advanced analytics tools and coach the junior team members Implement necessary quality control measures in place to ensure the deliverable integrity like data quality, model robustness, and explainability for deployments. Validate analysis outcomes, recommendations with all stakeholders including the client team Build storylines and make presentations to the client team and/or PwC project leadership team Contribute to the knowledge and firm building activities Role & responsibilities Preferred candidate profile

Job Description : Assistant General Manager - Human Resources and Administration Position: AGM/DGM- Human Resources and Administration Location: Hyderabad Cluster Job Summary: The Assistant General Manager/ Deputy General Manager- Human Resources and Administration at Aurobindo Pharma Limited will lead and manage all HR and Administration functions at the Visakhapatnam cluster location, with a particular focus on industrial relations, trade unions, public relations and General Adminstration. This role requires a strategic thinker with extensive experience in the pharmaceutical industry, capable of navigating complex labor relations, General Administration, Liasoning and fostering a positive workplace culture. The ideal candidate will be adept at aligning HR strategies with business objectives, ensuring compliance with legal standards, and promoting effective communication across the organization. Aligning and Cascading with Corporate HR & Administration business strategies and ensuring Statutory compliances. Qualifications: Masters degree in Human Resources, Business Administration (MBA/M.H.R.M). Minimum of 18+ years of progressive HR experience, with at least 15 years in a leadership role within the pharmaceutical industry. Extensive experience in industrial relations and working with trade unions. Proven track record in developing and implementing HR strategies that align with business objectives. Strong understanding of labor laws, regulations, and compliance requirements. Excellent negotiation, conflict resolution, and interpersonal skills. Superior communication skills, both verbal and written. Ability to work effectively in a fast-paced and dynamic environment. Strong leadership and team management skills. Preferred Skills: Knowledge of the latest HR trends and best practices. Public speaking and media handling skills.

⚠️ Applications without a GitHub or Portfolio link in the resume will be automatically rejected. Please include it to be considered At NilAi, we’re building an AI-powered platform that helps hospitals (starting with the NHS) optimize energy and water consumption, reduce carbon emissions, and meet Net Zero goals—without any new hardware. We're looking for a passionate AI Intern to join our mission-driven team and help us shape the future of sustainable healthcare. 🌍 Company: NilAI 📍 Location: India (Remote) 💼 Position: AI Intern 💰 Stipend: ₹5,000/month Responsibilities Clean, preprocess, and analyze large datasets related to hospital energy usage, water consumption, and operational workflows. Develop and implement machine learning models (e.g., regression, time-series forecasting, anomaly detection) using Scikit-learn, TensorFlow/PyTorch to predict and optimize energy consumption. Explore the application of LLMs (Large Language Models) for automating reports or extracting insights from unstructured data (e.g., maintenance logs, audit reports). Create interactive dashboards and visualizations using Power BI or Tableau to communicate findings to stakeholders. Integrate open-source APIs (e.g., OpenAI API) for enhancing data processing or generating sustainability recommendations. Assist in deploying lightweight models or prototypes using Flask or Streamlit for internal testing. Collaborate with the team to refine AI-driven recommendations for reducing carbon emissions and improving resource efficiency. Take ownership of complex challenges, demonstrating a commitment to continuous learning and delivering innovative, scalable solutions. Required Skills & Qualifications - Pursuing or recently completed a degree in Data Science, Computer Science, Engineering, Statistics, or a related field. - Proficiency in Python and experience with data science libraries (e.g., Pandas, NumPy, Scikit-learn). - Familiarity with machine learning frameworks (TensorFlow/PyTorch) and model deployment. - Experience with data visualization tools (Power BI, Tableau) and storytelling with data. - Basic understanding of LLMs and API integrations (e.g., OpenAI, Hugging Face). - Exposure to time-series forecasting (e.g., Prophet, ARIMA) or anomaly detection techniques. - Experience with ETL pipelines (e.g., Apache Airflow, Alteryx, or custom Python scripts) and data warehousing concepts. - Knowledge of SQL for data querying and manipulation. - Ability to work with messy, real-world datasets and strong problem-solving skills. - Passion for sustainability, healthcare innovation, or energy efficiency is a plus! Nice-to-Have Skills Experience with cloud platforms (AWS, GCP) or big data tools. What You’ll Gain Hands-on experience with AI for sustainability in a high-impact startup. Mentorship from experienced data scientists and exposure to real-world energy challenges. Opportunity to contribute to a product that directly reduces carbon emissions and saves costs for hospitals. Flexible work environment and potential for future full-time roles. Please Note: Kindly attach your CV with portfolios for review. Let’s build something that matters. 🌍 #AIforGood #ClimateTech #HealthcareInnovation #NilAi Show more Show less

We are seeking a talented and versatile Analytics & AI Specialist to join our dynamic team. This role combines expertise in General Analytics , Artificial Intelligence (AI) , Generative AI (GenAI) , forecasting techniques , and client management to deliver innovative solutions that drive business success. The ideal candidate will work closely with clients, leverage AI technologies to enhance data-driven decision-making, and apply forecasting models to predict business trends and outcomes. Responsibilities: Data Analytics & Insights : Conduct advanced data analysis across various datasets, identify patterns, trends, and insights that provide actionable business intelligence. Work with cross-functional teams to interpret business problems and develop data-driven strategies for performance optimization. Design and implement interactive dashboards and reports using data visualization tools like Power BI , AI & Machine Learning : Apply AI and machine learning techniques (e.g., supervised learning , unsupervised learning , deep learning ) to solve complex business problems. Develop, train, and deploy machine learning models for predictive analysis, classification, and recommendation systems. Utilize Generative AI (GenAI) models to create synthetic data, automate processes, and develop AI-driven content or solutions. Forecasting & Predictive Modeling : Build and maintain statistical forecasting models (e.g., ARIMA , Exponential Smoothing , Prophet ) and machine learning-based models to predict future trends and business outcomes. Perform demand forecasting, sales forecasting, and trend analysis for business planning and resource allocation. Continuously refine models based on historical data, seasonality, and external factors to improve prediction accuracy. Client Management & Consulting : Serve as a trusted advisor to clients, understanding their business needs and providing tailored data-driven solutions to improve performance. Communicate technical concepts and results to non-technical stakeholders in a clear, actionable manner. Develop presentations and reports for clients, highlighting insights, recommendations, and the value of AI-driven solutions. Collaborate with clients to define KPIs, metrics, and objectives for analytics projects and ensure the delivery of high-quality outcomes. AI Strategy & Innovation : Stay updated on the latest advancements in AI , Generative AI , and machine learning techniques, integrating these technologies into business solutions. Identify new opportunities to apply AI and analytics to improve efficiency, productivity, and customer experience for clients. Assist clients in scaling their AI initiatives, from proof-of-concept to full-scale deployment, and guide them through the AI lifecycle. Key Technical Skills: General Analytics : Strong knowledge of statistical analysis , data visualization , and data wrangling techniques. Proficiency with analytics tools such as Excel , R , Python (pandas, NumPy), and SQL for querying and analyzing large datasets. AI & Machine Learning : Experience with machine learning frameworks and libraries (e.g., TensorFlow , scikit-learn , PyTorch , Keras ). Knowledge of Generative AI (GenAI) tools and technologies, including GPT models , GANs (Generative Adversarial Networks) , and transformer models . Familiarity with AI cloud platforms (e.g., Google AI , AWS SageMaker , Azure AI ). Forecasting : Expertise in time series forecasting methods (e.g., ARIMA , Exponential Smoothing , Prophet ) and machine learning-based forecasting models. Experience applying predictive analytics and building forecasting models for demand, sales, and resource planning. Data Visualization & Reporting : Expertise in creating interactive reports and dashboards with tools like Tableau , Power BI , or Google Data Studio . Ability to present complex analytics and forecasting results in a clear and compelling way to stakeholders. Client Management & Communication : Strong client-facing skills with the ability to manage relationships and communicate complex technical concepts to non-technical audiences. Ability to consult and guide clients on best practices for implementing AI-driven solutions. Excellent written and verbal communication skills for client presentations, technical documentation, and report writing. Desired Qualifications: Bachelor’s or Master’s degree in Computer Science , Data Science , Statistics , Engineering , or a related field. 7-10 years of experience in data analytics , AI , forecasting , and client management , preferably in a consulting or client-facing role. Proven experience in implementing AI models, forecasting solutions, and data-driven strategies in a business context. A passion for continuous learning and staying updated with the latest trends in AI and machine learning technologies. Show more Show less

Required Skills: Successful candidates will have demonstrated the following skills and characteristics: Must Have: Proven expertise in supply chain analytics across domains such as demand forecasting, inventory optimization, logistics, segmentation, and network design Well versed and hands-on experience of working on optimization methods like linear programming, mixed integer programming, scheduling optimization. Having understanding of working on third party optimization solvers like Gurobi will be an added advantage Proficiency in forecasting techniques (e.g., Holt-Winters, ARIMA, ARIMAX, SARIMA, SARIMAX, FBProphet, NBeats) and machine learning techniques (supervised and unsupervised) Strong command of statistical modeling, testing, and inference Proficient in using GCP tools: BigQuery, Vertex AI, Dataflow, Looker Building data pipelines and models for forecasting, optimization, and scenario planning Strong SQL and Python programming skills; experience deploying models in GCP environment Knowledge of orchestration tools like Cloud Composer (Airflow) Nice to have: Familiarity with MLOps, containerization (Docker, Kubernetes), and orchestration tools (e.g., Cloud composer) Strong communication and stakeholder engagement skills at the executive level Roles and Responsibilities: Assist analytics projects within the supply chain domain, driving design, development, and delivery of data science solutions Develop and execute on project & analysis plans under the guidance of Project Manager Interact with and advise consultants/clients in US as a subject matter expert to formalize data sources to be used, datasets to be acquired, data & use case clarifications that are needed to get a strong hold on data and the business problem to be solved Drive and Conduct analysis using advanced analytics tools and coach the junior team members Implement necessary quality control measures in place to ensure the deliverable integrity like data quality, model robustness, and explainability for deployments. Validate analysis outcomes, recommendations with all stakeholders including the client team Build storylines and make presentations to the client team and/or PwC project leadership team Contribute to the knowledge and firm building activities Role & responsibilities Preferred candidate profile

Job Description We are looking for an experienced Data Scientist with a specialization in forecasting to join our data science team. The ideal candidate will have a deep understanding of statistical and machine learning techniques for time series forecasting and demand prediction. In this role, you will drive business value by developing accurate forecasting models and delivering actionable insights to optimize decision-making processes across the organization . Key Responsibilitie s: Develop and implement advanced time series forecasting models to predict key business metrics (e.g., sales, demand, inventory, etc .).Analyze historical data to identify trends, seasonality, and other patterns that can be leveraged for accurate forecasti ng.Collaborate closely with client’s cross-functional teams such as Supply Chain, Finance, and Marketing to understand business needs and deliver tailored forecasting solutio ns.Build and optimize machine learning models for forecasting using state-of-the-art techniques (e.g., ARIMA, Prophet, LSTM, etc .).Design and run experiments to validate forecasting models and continuously improve their accuracy and reliabili ty.Communicate complex data-driven insights and forecasting results to both technical and non-technical stakeholde rs.Ensure high-quality data inputs for forecasting models by working with data engineering teams to improve data collection, transformation, and integration process es.Stay current with the latest advancements in forecasting methodologies, tools, and techniques, and apply them to enhance existing mode ls.Provide thought leadership in forecasting and predictive analytics, driving innovation within the data science te am.Mentor junior team members and help establish best practices for forecasting across the organizati on. Qualificat ions Master’s or Ph.D. in Data Science, Statistics, Economics, Applied Mathematics, or a related quantitative f ield.4+ years of experience in developing and deploying forecasting models in a business environ ment.Expertise in time series analysis and forecasting techniques, including ARIMA, SARIMA, Holt-Winters, and advanced machine learning methods like gradient boosting, neural networks (e.g., LSTM, GRU), etc.Proficiency in programming languages such as Python or R, with strong experience in data manipulation, model building, and statistical anal ysis.Hands-on experience with forecasting tools and libraries, such as Prophet, scikit-learn, TensorFlow, PyTorch, etc.Strong understanding of data structures, data wrangling, and working with large data sets.Experience with cloud computing platforms (e.g., AWS, Azure, Google Cloud) and working in a distributed data environment is a plus.Excellent problem-solving skills and ability to translate complex data into actionable insi ghts.Strong communication and presentation skills, with the ability to convey complex concepts to both technical and non-technical audie nces.Experience with visualization tools like Tableau, Power BI, or similar to present forecasting outc omes.Ability to work independently and collaboratively in a fast-paced environ ment. Preferred Qualifica tions:Experience with demand forecasting, sales forecasting, or supply chain optimization in industries such as retail, manufacturing, or fi nance.Familiarity with statistical testing and experimentation (e.g., A/B tes ting).Experience deploying models in production environments and collaborating with engineering teams to build scalable solu tions.Previous experience in a consulting or client-facing role is a plus. Show more Show less

Job Title: RCM Trainee Credentialing and Billing Operations Location: Gurugram, India Company: Neolytix Experience Required: Freshers (0–1 year) Employment Type: Full-time (Onsite role, 5-day work week) About Us Neolytix is a fast-growing healthcare services company looking to onboard fresh graduates as Management Trainees to build future-ready professionals in the field of Revenue Cycle Management (RCM) . This role is ideal for individuals who are looking to build a long-term career in medical billing, healthcare operations, and client delivery. You will be part of a structured, in-depth training and career progression journey where you’ll gain domain knowledge, hands-on experience, and the opportunity to grow into leadership roles. Why Join Neolytix? Get comprehensive training in US healthcare and RCM processes Gain hands-on exposure in a live business environment Work in a collaborative and fast-paced team Build your career with opportunities to specialize, lead, and mentor Enjoy a professional work culture with growth-driven mentorship Program Overview As a Management Trainee, your first three months will be a probationary period. This includes one week of onboarding followed by one month of service-specific training and continuous assessments. The training covers key areas such as the US healthcare system, insurance types, CPT coding, and RCM workflows. After training, you’ll begin working in a specific operational domain to apply your learning in real scenarios. Within 3 to 6 months, you will be groomed into a specialist in the RCM function. After one-year, top performers will have the opportunity to lead accounts, mentor new trainees, or manage small teams. Key Responsibilities Participate in structured training on RCM, medical billing, insurance, and healthcare workflows Assist operational teams in live projects and understand key performance metrics Apply theoretical concepts in assigned functional areas such as claims processing, payment posting, or denial management Support team leads in achieving client SLAs and compliance targets Continuously learn and adapt to changes in US healthcare rules and client requirements Progress into specialized or leadership roles based on performance and initiative Qualifications & Skills Recent graduates with a background in Science or Commerce with Math (preferred degrees: B.Sc, BCA, BBA, B.Com, or similar analytical/technical courses ) Minimum 65% aggregate in 12th grade (CBSE/ICSE or equivalent) Strong English communication and comprehension skills Basic proficiency in Microsoft Excel and Word Schooling from Delhi-NCR or other Tier-1/Cosmopolitan cities is preferred Strong analytical skills, willingness to learn, and high attention to detail Note: Applications not meeting the above eligibility criteria will not be considered. Salary Up to 3 LPA (based on performance and evaluation during training period) How to Apply If you're looking to start your career in healthcare operations, learn industry-leading skills, and grow with a forward-thinking team — Neolytix is the place for you. Apply now and start your journey in Revenue Cycle Management with us!

Flexing It is a freelance consulting marketplace that connects freelancers and independent consultants with organisations seeking independent talent. Flexing It has partnered with Our client, A leading global FMCG firm is seeking a detail-oriented and analytical Statistical Forecasting Analyst. The ideal candidate will be responsible for developing, maintaining, and improving statistical models to forecast demand, sales, or other key business metrics. This role requires strong analytical skills, proficiency in statistical software, and the ability to translate complex data into actionable insights that support strategic decision-making. Key responsibilities: ● Develop and maintain statistical models for short-term and long-term forecasting. ● Analyze historical data and identify trends, seasonality, and outliers to enhance forecast accuracy. ● Collaborate with cross-functional teams (e.g., sales, marketing, finance, supply chain) to understand forecasting requirements and business drivers. ● Perform scenario analysis and sensitivity testing to evaluate forecast robustness. ● Utilize software tools and programming languages (e.g., Python, R, SQL, Excel, SAS) for data manipulation and model development. ● Communicate forecasting results and insights through clear visualizations, dashboards, and presentations. ● Continuously refine forecasting processes and recommend improvements to enhance accuracy and efficiency. ● Monitor forecast performance using key metrics (e.g., MAPE, RMSE) and adjust models accordingly. ● Support demand planning or financial planning functions with accurate forecast inputs Skills required: ● Bachelor’s or Master’s degree in Statistics, Mathematics, Data Science, Economics, or a related quantitative field. ● 3+ years of experience in statistical modeling, forecasting, or related analytics roles. ● Strong knowledge of time series analysis and forecasting methodologies (e.g., ARIMA, exponential smoothing, regression, machine learning approaches). ● Proficiency in statistical and data analysis tools such as Python, R, SQL, Excel, or SAS. ● Experience with data visualization tools like Power BI, Tableau, or similar. ● Strong problem-solving, critical thinking, and communication skills. ● Ability to work independently and collaboratively in a fast-paced environment Show more Show less

About Hakkoda Hakkoda, an IBM Company, is a modern data consultancy that empowers data driven organizations to realize the full value of the Snowflake Data Cloud. We provide consulting and managed services in data architecture, data engineering, analytics and data science. We are renowned for bringing our clients deep expertise, being easy to work with, and being an amazing place to work! We are looking for curious and creative individuals who want to be part of a fast-paced, dynamic environment, where everyone’s input and efforts are valued. We hire outstanding individuals and give them the opportunity to thrive in a collaborative atmosphere that values learning, growth, and hard work. Our team is distributed across North America, Latin America, India and Europe. If you have the desire to be a part of an exciting, challenging, and rapidly-growing Snowflake consulting services company, and if you are passionate about making a difference in this world, we would love to talk to you!. We are seeking an exceptional and highly motivated Lead Data Scientist with a PhD in Data Science, Computer Science, Applied Mathematics, Statistics, or a closely related quantitative field, to spearhead the design, development, and deployment of an automotive OEM’s next-generation Intelligent Forecast Application. This pivotal role will leverage cutting-edge machine learning, deep learning, and statistical modeling techniques to build a robust, scalable, and accurate forecasting system crucial for strategic decision-decision-making across the automotive value chain, including demand planning, production scheduling, inventory optimization, predictive maintenance, and new product introduction. The successful candidate will be a recognized expert in advanced forecasting methodologies, possess a strong foundation in data engineering and MLOps principles, and demonstrate a proven ability to translate complex research into tangible, production-ready applications within a dynamic industrial environment. This role demands not only deep technical expertise but also a visionary approach to leveraging data and AI to drive significant business impact for a leading automotive OEM. Role Description Strategic Leadership & Application Design: Lead the end-to-end design and architecture of the Intelligent Forecast Application, defining its capabilities, modularity, and integration points with existing enterprise systems (e.g., ERP, SCM, CRM). Develop a strategic roadmap for forecasting capabilities, identifying opportunities for innovation and the adoption of emerging AI/ML techniques (e.g., generative AI for scenario planning, reinforcement learning for dynamic optimization). Translate complex business requirements and automotive industry challenges into well-defined data science problems and technical specifications. Advanced Model Development & Research: Design, develop, and validate highly accurate and robust forecasting models using a variety of advanced techniques, including: Time Series Analysis: ARIMA, SARIMA, Prophet, Exponential Smoothing, State-space models. Machine Learning: Gradient Boosting (XGBoost, LightGBM), Random Forests, Support Vector Machines. Deep Learning: LSTMs, GRUs, Transformers, and other neural network architectures for complex sequential data. Probabilistic Forecasting: Quantile regression, Bayesian methods to capture uncertainty. Hierarchical & Grouped Forecasting: Managing forecasts across multiple product hierarchies, regions, and dealerships. Incorporate diverse data sources, including historical sales, market trends, economic indicators, competitor data, internal operational data (e.g., production schedules, supply chain disruptions), external events, and unstructured data. Conduct extensive exploratory data analysis (EDA) to identify patterns, anomalies, and key features influencing automotive forecasts. Stay abreast of the latest academic researchand industry advancements in forecasting, machine learning, and AI, actively evaluating and advocating for their practical application within the OEM. Application Development & Deployment (MLOps): Architect and implement scalable data pipelines for ingestion, cleaning, transformation, and feature engineering of large, complex automotive datasets. Develop robust and efficient code for model training, inference, and deployment within a production environment. Implement MLOps best practices for model versioning, monitoring, retraining, and performance management to ensure the continuous accuracy and reliability of the forecasting application. Collaborate closely with Data Engineering, Software Development, and IT Operations teams to ensure seamless integration, deployment, and maintenance of the application. Performance Evaluation & Optimization: Define and implement rigorous evaluation metrics for forecasting accuracy (e.g., MAE, RMSE, MAPE, sMAPE, wMAPE, Pinball Loss) and business impact. Perform A/B testing and comparative analyses of different models and approaches to continuously improve forecasting performance. Identify and mitigate sources of bias and uncertainty in forecasting models. Collaboration & Mentorship: Work cross-functionally with various business units (e.g., Sales, Marketing, Supply Chain, Manufacturing, Finance, Product Development) to understand their forecasting needs and integrate solutions. Communicate complex technical concepts and model insights clearly and concisely to both technical and non-technical stakeholders. Provide technical leadership and mentorship to junior data scientists and engineers, fostering a culture of innovation and continuous learning. Potentially contribute to intellectual property (patents) and present findings at internal and external conferences. Qualifications Education: PhD in Data Science, Computer Science, Statistics, Applied Mathematics, Operations Research, or a closely related quantitative field. Experience: 5+ years of hands-on experience in a Data Scientist or Machine Learning Engineer role, with a significant focus on developing and deploying advanced forecasting solutions in a production environment. Demonstrated experience designing and developing intelligent applications, not just isolated models. Experience in the automotive industry or a similar complex manufacturing/supply chain environment is highly desirable. Technical Skills: Expert proficiency in Python (Numpy, Pandas, Scikit-learn, Statsmodels) and/or R. Strong proficiency in SQL. Machine Learning/Deep Learning Frameworks: Extensive experience with TensorFlow, PyTorch, Keras, or similar deep learning libraries. Forecasting Specific Libraries: Proficiency with forecasting libraries like Prophet, Statsmodels, or specialized time series packages. Data Warehousing & Big Data Technologies: Experience with distributed computing frameworks (e.g., Apache Spark, Hadoop) and data storage solutions (e.g., Snowflake, Databricks, S3, ADLS). Cloud Platforms: Hands-on experience with at least one major cloud provider (Azure, AWS, GCP) for data science and ML deployments. MLOps: Understanding and practical experience with MLOps tools and practices (e.g., MLflow, Kubeflow, Docker, Kubernetes, CI/CD pipelines). Data Visualization: Proficiency with tools like Tableau, Power BI, or similar for creating compelling data stories and dashboards. Analytical Prowess: Deep understanding of statistical inference, experimental design, causal inference, and the mathematical foundations of machine learning algorithms. Problem Solving: Proven ability to analyze complex, ambiguous problems, break them down into manageable components, and devise innovative solutions. Preferred Qualifications Publications in top-tier conferences or journals related to forecasting, time series analysis, or applied machine learning. Experience with real-time forecasting systems or streaming data analytics. Familiarity with specific automotive data types (e.g., telematics, vehicle sensor data, dealership data, market sentiment). Experience with distributed version control systems (e.g., Git). Knowledge of agile development methodologies. Soft Skills Exceptional Communication: Ability to articulate complex technical concepts and insights to a diverse audience, including senior management and non-technical stakeholders. Collaboration: Strong interpersonal skills and a proven ability to work effectively within cross-functional teams. Intellectual Curiosity & Proactiveness: A passion for continuous learning, staying ahead of industry trends, and proactively identifying opportunities for improvement. Strategic Thinking: Ability to see the big picture and align technical solutions with overall business objectives. Mentorship: Desire and ability to guide and develop less experienced team members. Resilience & Adaptability: Thrive in a fast-paced, evolving environment with complex challenges. Benefits Health Insurance Paid leave Technical training and certifications Robust learning and development opportunities Incentive Toastmasters Food Program Fitness Program Referral Bonus Program Hakkoda is committed to fostering diversity, equity, and inclusion within our teams. A diverse workforce enhances our ability to serve clients and enriches our culture. We encourage candidates of all races, genders, sexual orientations, abilities, and experiences to apply, creating a workplace where everyone can succeed and thrive. Ready to take your career to the next level? 🚀 💻 Apply today👇 and join a team that’s shaping the future!! Hakkoda is an IBM subsidiary which has been acquired by IBM and will be integrated in the IBM organization. Hakkoda will be the hiring entity. By Proceeding with this application, you understand that Hakkoda will share your personal information with other IBM subsidiaries involved in your recruitment process, wherever these are located. More information on how IBM protects your personal information, including the safeguards in case of cross-border data transfer, are available here. Show more Show less

Position : AI / ML Engineer Job Type : Full-Time Location : Gurgaon, Haryana, India Experience : 2 Years Industry : Information Technology Domain : Demand Forecasting in Retail/Manufacturing Job Summary We are seeking a skilled Time Series Forecasting Engineer to enhance existing Python microservices into a modular, scalable forecasting engine. The ideal candidate will have a strong statistical background, expertise in handling multi-seasonal and intermittent data, and a passion for model interpretability and real-time insights. Key Responsibilities Develop and integrate advanced time-series models: MSTL, Croston, TSB, Box-Cox. Implement rolling-origin cross-validation and hyperparameter tuning. Blend models such as ARIMA, Prophet, and XGBoost for improved accuracy. Generate SHAP-based driver insights and deliver them to a React dashboard via GraphQL. Monitor forecast performance with Prometheus and Grafana; trigger alerts based on degradation. Core Technical Skills Languages : Python (pandas, statsmodels, scikit-learn) Time Series : ARIMA, MSTL, Croston, Prophet, TSB Tools : Docker, REST API, GraphQL, Git-flow, Unit Testing Database : PostgreSQL Monitoring : Prometheus, Grafana Nice-to-Have : MLflow, ONNX, TensorFlow Probability Soft Skills Strong communication and collaboration skills Ability to explain statistical models in layman terms Proactive problem-solving attitude Comfort working cross-functionally in iterative development environments Job Type: Full-time Pay: ₹400,000.00 - ₹800,000.00 per year Application Question(s): Do you have at least 2 years of hands-on experience in Python-based time series forecasting? Have you worked in retail or manufacturing domains where demand forecasting was a core responsibility? Are you currently authorized to work in India without sponsorship? Have you implemented or used ARIMA, Prophet, or MSTL in any of your projects? Have you used Croston or TSB models for forecasting intermittent demand? Are you familiar with SHAP for model interpretability? Have you containerized a forecasting pipeline using Docker and exposed it through a REST or GraphQL API? Have you used Prometheus and Grafana to monitor model performance in production? Work Location: In person Application Deadline: 05/06/2025 Expected Start Date: 05/06/2025

Our Purpose Mastercard powers economies and empowers people in 200+ countries and territories worldwide. Together with our customers, we’re helping build a sustainable economy where everyone can prosper. We support a wide range of digital payments choices, making transactions secure, simple, smart and accessible. Our technology and innovation, partnerships and networks combine to deliver a unique set of products and services that help people, businesses and governments realize their greatest potential. Title And Summary Manager- Data Science Who is Mastercard? Mastercard is a global technology company in the payments industry. Our mission is to connect and power an inclusive, digital economy that benefits everyone, everywhere by making transactions safe, simple, smart, and accessible. Using secure data and networks, partnerships, and passion, our innovations and solutions help individuals, financial institutions, governments, and businesses realize their greatest potential. Our decency quotient, or DQ, drives our culture and everything we do inside and outside of our company. With connections across more than 210 countries and territories, we are building a sustainable world that unlocks priceless possibilities for all. Our Team As consumer preference for digital payments continues to grow, ensuring a seamless and secure consumer experience is top of mind. Optimization Solutions team focuses on tracking of digital performance across all products and regions, understanding the factors influencing performance and the broader industry landscape. This includes delivering data-driven insights and business recommendations, engaging directly with key external stakeholders on implementing optimization solutions (new and existing), and partnering across the organization to drive alignment and ensure action is taken. Are you excited about Data Assets and the value they bring to an organization? Are you an evangelist for data-driven decision-making? Are you motivated to be part of a team that builds large-scale Analytical Capabilities supporting end users across 6 continents? Do you want to be the go-to resource for data science & analytics in the company? The Role Work closely with global optimization solutions team to architect, develop, and maintain advanced reporting and data visualization capabilities on large volumes of data to support data insights and analytical needs across products, markets, and services The candidate for this position will focus on Building solutions using Machine Learning and creating actionable insights to support product optimization and sales enablement. Prototype new algorithms, experiment, evaluate and deliver actionable insights. Drive the evolution of products with an impact focused on data science and engineering. Designing machine learning systems and self-running artificial intelligence (AI) software to automate predictive models. Perform data ingestion, aggregation, and processing on high volume and high dimensionality data to drive and enable data unification and produce relevant insights. Continuously innovate and determine new approaches, tools, techniques & technologies to solve business problems and generate business insights & recommendations. Apply knowledge of metrics, measurements, and benchmarking to complex and demanding solutions. Role Ensure that all AI solutions follow industry standards for data management and privacy, covering aspects like data collection, use, storage, access, retention, output, reporting, and quality at Mastercard. Take a practical approach to AI, simplifying complex technical requirements to align with stakeholders' needs. Collaborate with global stakeholders to gather necessary information and define business problems. Think creatively to link AI methodologies with real business challenges. Identify common use case patterns to promote scalable AI through reusable models and a microservice approach. Build AI/ML solutions using the latest advancements from industry and academia. Use both open and proprietary technologies to address business problems. Work effectively across teams and geographies, leveraging broader team expertise to achieve AI goals. Partner with technical teams to deploy solutions in production environments. Foster a culture of learning and continuous improvement in AI capabilities. All About You 8+ years in Data Science, with a focus on AI strategy, execution, and solution development from the ground up. A passion for AI, demonstrated through participation in competitions such as Kaggle. Preferred experience or familiarity with cybersecurity, fraud, and risk solutions, including: Deep learning algorithms, open-source tools, and statistical environments (Python, R, SQL). Big data platforms like Hadoop, Hive, Spark, and GPU clusters for deep learning. Classical machine learning techniques such as Logistic Regression, Decision Trees, K-Means, PCA, and Time Series models (ARIMA/ARMA). Deep learning techniques including Random Forest, GBM, Neural Networks (CNNs, LSTMs), and optimization techniques (Adam, Adagrad, etc.). Frameworks like TensorFlow, Keras, PyTorch, and XGBoost for production systems. Experience or exposure to collaboration tools like Confluence, Bitbucket, ALM, etc. Knowledge of the payments industry and experience with SAFe (Scaled Agile Framework) is a plus. Effectiveness Ability to manage assumptions and validate them with key stakeholders under tight deadlines, while keeping development on track. Strong problem-solving skills, with the ability to break down complex issues and apply the right AI techniques to solve them. Deep attention to detail, ensuring high confidence in developed solutions. Strong understanding of technical system architecture and interdependencies, anticipating challenges and proactively solving them. Core Capabilities Excellent written and verbal communication skills. Strong project management experience. Background in Computer Science. Corporate Security Responsibility All activities involving access to Mastercard assets, information, and networks comes with an inherent risk to the organization and, therefore, it is expected that every person working for, or on behalf of, Mastercard is responsible for information security and must: Abide by Mastercard’s security policies and practices; Ensure the confidentiality and integrity of the information being accessed; Report any suspected information security violation or breach, and Complete all periodic mandatory security trainings in accordance with Mastercard’s guidelines. R-245889 Show more Show less

Flexing It is a freelance consulting marketplace that connects freelancers and independent consultants with organisations seeking independent talent. Flexing It has partnered with Our client, A leading global FMCG firm is seeking a detail-oriented and analytical Statistical Forecasting Analyst. The ideal candidate will be responsible for developing, maintaining, and improving statistical models to forecast demand, sales, or other key business metrics. This role requires strong analytical skills, proficiency in statistical software, and the ability to translate complex data into actionable insights that support strategic decision-making. Key responsibilities: ● Develop and maintain statistical models for short-term and long-term forecasting. ● Analyze historical data and identify trends, seasonality, and outliers to enhance forecast accuracy. ● Collaborate with cross-functional teams (e.g., sales, marketing, finance, supply chain) to understand forecasting requirements and business drivers. ● Perform scenario analysis and sensitivity testing to evaluate forecast robustness. ● Utilize software tools and programming languages (e.g., Python, R, SQL, Excel, SAS) for data manipulation and model development. ● Communicate forecasting results and insights through clear visualizations, dashboards, and presentations. ● Continuously refine forecasting processes and recommend improvements to enhance accuracy and efficiency. ● Monitor forecast performance using key metrics (e.g., MAPE, RMSE) and adjust models accordingly. ● Support demand planning or financial planning functions with accurate forecast inputs Skills required: ● Bachelor’s or Master’s degree in Statistics, Mathematics, Data Science, Economics, or a related quantitative field. ● 3+ years of experience in statistical modeling, forecasting, or related analytics roles. ● Strong knowledge of time series analysis and forecasting methodologies (e.g., ARIMA, exponential smoothing, regression, machine learning approaches). ● Proficiency in statistical and data analysis tools such as Python, R, SQL, Excel, or SAS. ● Experience with data visualization tools like Power BI, Tableau, or similar. ● Strong problem-solving, critical thinking, and communication skills. ● Ability to work independently and collaboratively in a fast-paced environment Show more Show less

Company:- ABDOS Lamitubes Pvt. Ltd. (https://abdoslamitubes.com/) Position: - Safety Officer - EHS Experience: - 1 to 5+ Years Qualification: - Diploma/ B. Tech (Certificate Course of Industrial Safety from Govt. recognized) Salary:- Upto - 4.80 LPA Location:- Amingaon, Guwahati. Responsibilities: - Prepare and facilitate training on environment, health, and safety (EHS) measures imparted company. Should have experience on Hazardous waste management and statutory compliance of storage or Disposal of waste. Should have experience of consent management and hazardous disposal documentation. Should be aware about pollution control Board and liaisoning. EHS Documentation including SOPs, change controls, deviations, CAPA, validations, Data capturing etc. Expertise in GMP implementations, good practices in the organization, Environment Impact, and climate change Risk assessment & analysis, GHG emissions analysis, To organize safety committee meetings, drills and actively participate in the activities carried out regarding the safety in the concerned area. Significant solutions and implementing Environment, health safety management systems for maintaining sound environmental and safety conditions and development, repair, and modification of the plant. Role: - Planning and preparing EHS Calendar of all activities to be carried out during the year. Records related to EHS and MIS Compliance. Ensuring complete adherence to policies and sops related to EHS. EHS Awareness. Plant Development, Repairing and Modification. NOTE :- Manufacturing industry experience required only. Interested candidates can apply at neha.srivastava@abdoslmitubes.com or Whatsapp 8851314500 (Neha)