244 Arima Jobs - Page 9

AlgoTutor is looking for a confident and engaging HFT Trainer to deliver in-person training sessions at one of our partner colleges in Jalandhar. If you’re passionate about guiding students in cracking HFT companies by guiding them on HFT curriculum — we want to hear from you! Location: On-site/Online , College Campus in Bengaluru Duration: 28 days Daily Hours: 6 hours/day Start Date: 16th Jun Key Responsibilities: Conduct sessions on below curriculum Week 1: Foundations of HFT Day 1 : Introduction to HFT, market microstructure, setup environment, data parsing. Day 2 : Low-latency C++ programming, multithreading, latency profiling. Day 3 : Data structures (arrays, hash maps), limit order book implementation. Day 4 : Networking (TCP/UDP, FIX protocol), low-latency message handling. Day 5 : Tick data processing, moving averages, real-time metrics. Day 6 : HFT system architecture, event-driven systems, trading loop. Day 7 : Weekly review, build a market data simulator project. Week 2: Trading Strategies & Optimization Day 8 : Statistical arbitrage, mean reversion, basic strategy coding. Day 9 : Market making strategies, order logic, inventory management. Day 10 : Time series analysis (MA, ARIMA), predictive modeling. Day 11 : Advanced low-latency techniques, multithreaded optimization. Day 12 : Execution algorithms (VWAP, TWAP), large order handling. Day 13 : Real-time risk management, stop-loss, risk detection. Day 14 : Weekly review, build a market-making bot. Week 3: Advanced Strategies & Infrastructure Day 15 : Pairs trading, cointegration, ADF test, backtesting. Day 16 : Latency arbitrage, strategy simulation, ethics. Day 17 : ML for HFT, feature engineering, order flow prediction. Day 18 : Infrastructure: co-location, FPGAs, network optimization. Day 19 : Order book dynamics, spoofing detection, high-volume trading. Day 20 : Portfolio optimization (Sharpe, Kelly), multi-asset strategies. Day 21 : Weekly review, build a latency arbitrage system. Week 4: Real-World Deployment Day 22 : Regulations (MiFID II, SEC), compliance checks. Day 23 : Backtesting framework, avoiding bias, strategy validation. Day 24 : Live trading simulation using real-time feeds. Day 25 : System monitoring, logging, failure detection. Day 26 : Capstone Project (Part 1): design and implement core logic. Day 27 : Capstone Project (Part 2): risk, compliance, testing, prep. Day 28 : Final presentations, wrap-up, certification, career advice. Requirements: Strong command over HFT Concepts Prior experience in classroom/online training Passionate about teaching Why Work With Us? Impact hundreds of students by enhancing their communication and confidence Be part of a mission-driven EdTech company shaping future professionals Opportunity for long-term collaboration on future training programs Apply Now and Grow with AlgoTutor! Show more Show less

Quantitative Researcher - High Frequency Trading Are you a self-proclaimed 'numbers person' with a love for high frequency trading, and staring at screens for hours on end? Do you enjoy the thrill of fast-paced, high-frequency trading? Then we've got the job for you! We're looking for a Quantitative Researcher to join our team and help us generate profits through complex financial modeling and lightning-fast algorithmic trading. You'll spend your days analyzing vast amounts of data, poring over charts and graphs, and occasionally taking breaks to go outside and squint at the sun. If you're the type of person who gets excited about 'tick data' and can recite the entire formula for calculating a 'moving average,' then we want to hear from you. Bonus points if you know how to 'cross-validate' like a pro and have a secret love for 'ARIMA models.' Qualifications A strong background in mathematics, statistics, or a related field Proficiency in Python, with experience using libraries such as NumPy, Pandas, and Scikit-Learn Familiarity with high-frequency trading strategies and market microstructure The ability to stare at screens for extended periods of time without going blind A passion for solving complex problems and generating profits through clever trading strategies A willingness to occasionally leave the office and breathe fresh air (optional) We offer competitive compensation packages, comprehensive benefits, and a company culture that values individuality Show more Show less

We’re currently looking for specialist Freelance Statisticians. What you will do: Provide support with simple and/or complex statistical analysis and interpretation based on the information and data shared by the author Analyse complex datasets and provide actionable insights to address research objectives. Generate comprehensive statistical outputs, including detailed inferences and analysis results. Present findings in a clear, structured format suitable for incorporation into research papers with minimal revisions. Apply advanced statistical techniques such as regression analysis, survival analysis, mixed-effects modelling, or machine learning as needed. Multiple Linear Regression Cox Proportional Hazards Model Principal Component Analysis (PCA) Structural Equation Modeling (SEM) Mixed-Effects Models Regularized Regression (LASSO, Ridge) Time Series Analysis (ARIMA Models) Propensity Score Matching Bayesian Hierarchical Modeling Prepare visualizations (charts, graphs, and tables) to effectively communicate findings. Summarize statistical findings in a way that is understandable to both technical and non-technical audiences. Review of methods used for the analysis to check appropriateness for answering research questions Rerunning the analysis to validate the results and confirm reproducibility Critical feedback on the statistical methods, analysis and results, with actionable recommendations for improvement (including additional tests/analysis/highlighting of results that can be used for the Discussion/Conclusions sections) Clean and/or organize data/variables, rework the analysis based on new data or additional tests, and enhance standard figures and tables to create Illustrations What you need: A Masters or PhD in one or more specialized subject areas in physical sciences, engineering, materials sciences, healthcare, life sciences, medicine, and surgery with minimum 3 years of experience in statistical analysis domain Knowledge of statistical analysis methodologies and experimental design, Randomized Control Trials (RCTs), and statistical applications in pharmacology, epidemiology, and safety evaluations Well versed with basic and advanced statistical and data processing software like SPSS, SAS, R, Minitab, STATA, JMP, Matlab, Statistica, and Prism Well versed with MS Office tools, specifically Outlook, Word, Excel, and PowerPoint Minimum 2-3 publications in reputed journals in the relevant subject area. (Preferred) Excellent communication skills in English (written/verbal). May also include one to one consultation calls with clients. Why this is a great opportunity for those searching for freelance opportunities: Flexibility to determine your work hours Work from anywhere Note: There is no mandatory time commitment. There is a fair amount of flexibility with working your schedule around the time required for each assignment. Show more Show less

At PwC, our people in data and analytics focus on leveraging data to drive insights and make informed business decisions. They utilise advanced analytics techniques to help clients optimise their operations and achieve their strategic goals. In data analysis at PwC, you will focus on utilising advanced analytical techniques to extract insights from large datasets and drive data-driven decision-making. You will leverage skills in data manipulation, visualisation, and statistical modelling to support clients in solving complex business problems. Years of Experience: Candidates with 4+ years of hands on experience Position: Senior Associate Industry: Supply Chain/Forecasting/Financial Analytics Required Skills: Successful candidates will have demonstrated the following skills and characteristics: Must Have Strong supply chain domain knowledge (inventory planning, demand forecasting, logistics) 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) Experience using at least one major cloud platform (AWS, Azure, GCP), such as: AWS: Experience with AWS SageMaker, Redshift, Glue, Lambda, QuickSight Azure: Experience with Azure ML Studio, Synapse Analytics, Data Factory, Power BI GCP: Experience with BigQuery, Vertex AI, Dataflow, Cloud Composer, Looker Experience developing, deploying, and monitoring ML models on cloud infrastructure Expertise in Python, SQL, data orchestration, and cloud-native data tools Hands-on experience with cloud-native data lakes and lakehouses (e.g., Delta Lake, BigLake) Familiarity with infrastructure-as-code (Terraform/CDK) for cloud provisioning Knowledge of visualization tools (PowerBI, Tableau, Looker) integrated with cloud backends Strong command of statistical modeling, testing, and inference Advanced capabilities in data wrangling, transformation, and feature engineering Familiarity with MLOps, containerization (Docker, Kubernetes), and orchestration tools (e.g., Airflow) 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 Professional And Educational Background BE / B.Tech / MCA / M.Sc / M.E / M.Tech /Master’s Degree /MBA from reputed institute Show more Show less

We are seeking a candidate with strong working experience in both Data Scientist . The ideal candidate must have utilized Azure services related to data, data engineering, and machine learning. PAN India. Machine Learning 7+ years of relevant experience Experience in handling ETRM projects. Good understanding of Power Trading concepts Must have good experience in implementing machine learning models such as Prophet, ARIMA, SARIMA, XGBoost, ElasticNet, Ridge, Lasso, Random Forest, and Linear Regression on time-series data. Proficient in using Python ML packages such as scikit-learn, sktime, and darts. Must have strong expertise in key techniques for time series feature engineering, including lag features, rolling window statistics, Fourier transforms, and handling seasonality. Proven ability to tune the performance of existing deployed forecasting models. Must have experience with Azure Machine Learning Python SDK v1/v2 to: Manage data, models, and environments Build/debug AML pipelines to stitch together multiple tasks (feature engineering, training, registering models, etc.) and production workflows using Azure ML pipelines Schedule Azure ML jobs Deploy registered models to create endpoints. Good to have experience with K-Means clustering.

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. 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. Additional Skills: Project Management: Experience managing data analytics projects from inception to completion, ensuring deadlines and objectives are met. Cloud Platforms: Experience with cloud platforms (AWS, GCP, Azure) for deploying AI models, handling large datasets, and performing distributed computing. Business Acumen: A strong understanding of business KPIs and the ability to align AI and analytics projects with client business goals. Show more Show less

Job Description ABOUT ADVANCE AUTO PARTS Founded in Roanoke, VA in 1932, Advance Auto Parts is a leading automotive aftermarket retail parts provider that serves both professional installer and do-it-yourself Customers. As of July 13, 2019, Advance operated 4,912 stores and 150 Worldpac branches in the United States, Canada, Puerto Rico, and the U.S. Virgin Islands. The Company also serves 1,250 independently owned CARQUEST branded stores across these locations in addition to Mexico, the Bahamas, Turks, and Caicos and the British Virgin Islands. The company has a workforce of over 70,000 knowledgeable and experienced Team Members who are proud to provide outstanding service to their Customers, Communities, and each other every day. ABOUT AAP GLOBAL CAPABILITY CENTER We are continually innovating and seeking to elevate the Customer experience at each of our stores. For an organization of our size and reach, today, it has become more critical than ever, to identify synergies and build shared capabilities. The AAP Global Capability Center, located in Hyderabad, is a step in this strategic direction that enables us to access a larger talent pool, unlock operational efficiencies and increase levels of collaboration. ABOUT PRICING TEAM The Pricing team is growing its presence in India to help expand our technical, brand, and analytical capabilities across the enterprise. This is a fantastic opportunity to join a team of highly specialized and focused individuals dedicated to driving our brand marketing and eCommerce outcomes in a collaborative environment. Join the Pricing team and start reimagining the future of automotive retail. Disrupt the way consumers buy Auto Parts and join a fast-growing eCommerce team to take on the industry’s biggest challenges. The focus here is on our customers -- how we make them happy, earn their trust, and create loyalty. We want to expand our best in class data science capability to predict consumer behavior and ensure we are getting the right return on our investments. Ultimately, the Pricing team is responsible for rapidly developing and deploying solutions that will drive the customer experience and, ultimately, enhance our bottom line as an organization. Job Description Looking for a Data Scientist with strong problem-solving skills and knowledge in Math, Statistics, and data science to join our Pricing Analytics CoE team. Applicants should have strong fundamental understanding and experience in Data Wrangling, Statistical Analysis, Predictive Modeling using Machine Learning (Regression and Classification), Cluster & Segmentation, Time Series Forecasting (ARIMA, SARIMAX) etc. with advanced level proficiency in programming language of Python and SQL Roles And Responsibilities As a self-starter, understand the Business dynamics and identify potential business problems that can be solved through Analysis and Advanced methodologies Involve in discussions with stakeholders to develop the data science use cases in retail, pricing and promotions that would impact the strategic pricing decisions. Apply statistical techniques to test various hypotheses, develop predictive models using data science Apply business knowledge for the Interpretation of test results and present the actionable insights to stakeholders for strategic pricing decisions. For identified use cases, develop proof of concepts and then scale the solutions for larger consumption of the outcomes by all the stakeholders. Identify potential data-driven solutions to improve customer and channel experience through personalization and predicting or influencing consumer behavior prediction (eg : next purchase, attrition, spend and ROI optimization etc.) Forecasting of demand drivers using Structural Time Series and Naïve Bayes approach Build intelligent systems to capture and model the vast amount of behavior data to enrich the content understanding with behavioral information for promotional strategies Cross-collaborate with data science practices and leverage learnings Requirements Candidates should have: BE/BTEch or Masters in Mathematics/Computer Science, MBA from a reputed institution with good academic record. 2-4 years of hands on experience in business consulting and advance analytics Must be strong in Python/R, SQL, and exposure to Machine Learning techniques is desirable Exposure to cloud technologies (e.g. AWS, Bitbucket), visualization tools (e.g. PowerBI) will be desirable Excellent understanding of complex system architecture, components and requirements Knowledge in supervised and unsupervised is a must Experience in Retail/Auto/Finance/Auto industry will be added advantage. Strong applied knowledge of machine learning covering the landscape of classification, regression and with in-depth interpretation of outcomes. California Residents Click Below For Privacy Notice: https://jobs.advanceautoparts.com/us/en/disclosures We are an Equal Opportunity Employer and do not discriminate against any employee or applicant for employment because of race, color, sex, age national origin, religion, sexual orientation, gender identity, status as a veteran and basis of disability or any other federal, state or local protected class. Show more Show less

• Develop, validate, and implement advanced statistical models, including mixed effects models, structural equation modelling, generalized additive models (GAMs), Bayesian modelling , and hierarchical models to address complex business challenges. • Analyze large datasets using statistical techniques to extract actionable insights and trends. • Collaborate with stakeholders to understand business needs and translate them into analytical solutions. • Present findings and recommendations clearly to both technical and non-technical audiences. • Stay current with industry trends, statistical methodologies, and best practices in data analysis. • Document methodologies and results, ensuring transparency and reproducibility of models. • Conduct exploratory data analysis to inform model development and improve accuracy. • Participate in continuous improvement initiatives to enhance modelling processes and tools. Qualifications: • Masters degree or above in Statistical Sciences. • Proven experience in statistical modeling, data analysis, and predictive analytics. • Very strong proficiency in statistical software (e.g., R, Python, SAS, SPSS) and data visualization tools (e.g., Tableau, Power BI). • Strong understanding of advanced statistical techniques, including regression analysis, time series forecasting, mixed effects models, structural equation modeling, generalized linear models (GLMs), machine learning algorithms (e.g., decision trees, random forests, support vector machines), and Bayesian inference. • Excellent problem-solving skills and attention to detail. • Strong communication skills, with the ability to convey complex statistical concepts to diverse audiences. • Experience with data management and database systems (e.g., SQL) is a plus. What we Offer • Competitive salary • Medical Benefits/Accident Cover • Flexi Office Working Hours • Fast paced start up

Company Qualcomm India Private Limited Job Area Information Technology Group, Information Technology Group > IT Management General Summary Experience in engaging with business and technical stakeholders, understanding complex problem statements, and proposing value-driven Data Science & ML solutions Functional & technical leadership in developing data science roadmap and guiding the team with end-to-end delivery (design, development, maintenance, and optimization) of advanced analytical solutions with focus on process standardization and best practices Proactive in reaching out to wide variety of stakeholders for increasing the awareness of Data Science, ML and GenAI capabilities and identifying business value driven opportunities Analyze the market and industry trends in the technology and proactively look for opportunities in bringing the best solutions 'Strong analytical skills with the ability to gather information from several sources and identify fundamental patterns/trends in data Conduct research, design statistical studies and develop solutions Develop Story Telling dashboards on analytics to assist business in decision making Implement deep learning models for structured and unstructured data sets Perform Time Series Analysis and Forecast (ARIMA, Exponential Smoothing, VAR etc.) Implementation experience with identifying, prototyping, developing and delivering GenAI solutions using Industry standard RAG models and frameworks Ability to develop capabilities in Text Analytics ranging from Basic to Advanced (Topic Modelling, NLP) Experience with AWS suite of Data Science and ML tools Develops predictive models using Machine Learning algorithms (SVM, Random Forest, Neural Network, Decision Tree, Logistic Regression, K-mean Clustering, Catboost etc.) 'Experience With Other Cloud Platforms (GCP And Azure) Understanding of Data Platforms and Data Engineering Exposure to ChatBot solutions and Automation technologies Minimum Qualifications 7+ years of IT-related work experience with a Bachelor's degree. OR 9+ years of IT-related work experience without a Bachelor’s degree. 4+ years in a leadership role in projects/programs. Applicants : Qualcomm is an equal opportunity employer. If you are an individual with a disability and need an accommodation during the application/hiring process, rest assured that Qualcomm is committed to providing an accessible process. You may e-mail disability-accomodations@qualcomm.com or call Qualcomm's toll-free number found here. Upon request, Qualcomm will provide reasonable accommodations to support individuals with disabilities to be able participate in the hiring process. Qualcomm is also committed to making our workplace accessible for individuals with disabilities. (Keep in mind that this email address is used to provide reasonable accommodations for individuals with disabilities. We will not respond here to requests for updates on applications or resume inquiries). Qualcomm expects its employees to abide by all applicable policies and procedures, including but not limited to security and other requirements regarding protection of Company confidential information and other confidential and/or proprietary information, to the extent those requirements are permissible under applicable law. To all Staffing and Recruiting Agencies : Our Careers Site is only for individuals seeking a job at Qualcomm. Staffing and recruiting agencies and individuals being represented by an agency are not authorized to use this site or to submit profiles, applications or resumes, and any such submissions will be considered unsolicited. Qualcomm does not accept unsolicited resumes or applications from agencies. Please do not forward resumes to our jobs alias, Qualcomm employees or any other company location. Qualcomm is not responsible for any fees related to unsolicited resumes/applications. If you would like more information about this role, please contact Qualcomm Careers. 3067263 Show more Show less

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