56 Arima Jobs

We are seeking a data scientist with strong technical expertise in machine learning and statistical analysis to develop and deploy impactful data solutions. The role involves designing and implementing predictive models (e.g., regression, classification, NLP, time series), collaborating with stakeholders to solve business problems, and driving strategic decisions through experimentation and data-driven insights Job Description: Key responsibilities: 1. Modeling & Machine Learning Design and implement robust machine learning solutions (e.g., regression, classification, NLP, time series, recommendation systems). Evaluate and tune models using appropriate metrics (AUC, RMSE, precision/recall, etc.). Work on feature engineering, model interpretability, and performance optimization. 2. Data-Driven Business Strategy Partner with stakeholders to identify key opportunities where data science can drive business value. Translate business problems into data science projects with clearly defined deliverables and success metrics. Provide actionable recommendations based on data analysis and model outputs. 3. Analytics and Experimentation Conduct deep-dive exploratory analysis to uncover trends and insights. Apply statistical methods to test hypotheses, forecast trends, and measure campaign effectiveness Design and analyze A/B tests and other experiments to support product and marketing decisions. Automate data pipelines and dashboards for ongoing monitoring of model and business performance. Technical Skills: Languages: Proficient in Python, MySQL. Libraries/Frameworks: scikit-learn, Pandas, NumPy, Time series, ARIMA, Bayesian model, Market Mix model, Regression, XGBoost, LightGBM, TensorFlow, PyTorch. Statistical Method: Proficient in statistical techniques such as hypothesis testing, regression analysis, time-series analysis Databases : PostgreSQL, BigQuery, MySQL. Visualization: Plotly, Seaborn, Matplotlib. Deployment: Experience in Gitlab, CI/CD pipelines(Good to have). Cloud Platforms: Familiarity with AWS, GCP, or Azure services(Good to have). Location: Chennai Brand: Paragon Time Type: Full time Contract Type: Permanent

We are seeking a data scientist with strong technical expertise in machine learning and statistical analysis to develop and deploy impactful data solutions. The role involves designing and implementing predictive models (e.g., regression, classification, NLP, time series), collaborating with stakeholders to solve business problems, and driving strategic decisions through experimentation and data-driven insights Job Description: Key responsibilities: Modeling & Machine Learning Design and implement robust machine learning solutions (e.g., regression, classification, NLP, time series, recommendation systems). Evaluate and tune models using appropriate metrics (AUC, RMSE, precision/recall, etc.). Work on feature engineering, model interpretability, and performance optimization. Data-Driven Business Strategy Partner with stakeholders to identify key opportunities where data science can drive business value. Translate business problems into data science projects with clearly defined deliverables and success metrics. Provide actionable recommendations based on data analysis and model outputs. Analytics and Experimentation Conduct deep-dive exploratory analysis to uncover trends and insights. Apply statistical methods to test hypotheses, forecast trends, and measure campaign effectiveness Design and analyze A/B tests and other experiments to support product and marketing decisions. Automate data pipelines and dashboards for ongoing monitoring of model and business performance. Technical Skills: Languages: Proficient in Python, MySQL. Libraries/Frameworks: scikit-learn, Pandas, NumPy, Time series, ARIMA, Bayesian model, Market Mix model, Regression, XGBoost, LightGBM, TensorFlow, PyTorch. Statistical Method: Proficient in statistical techniques such as hypothesis testing, regression analysis, time-series analysis Databases : PostgreSQL, BigQuery, MySQL. Visualization: Plotly, Seaborn, Matplotlib. Deployment: Experience in Gitlab, CI/CD pipelines(Good to have). Cloud Platforms: Familiarity with AWS, GCP, or Azure services(Good to have). Location: Chennai Brand: Paragon Time Type: Full time Contract Type: Permanent Show more Show less

About Northern Trust Northern Trust, a Fortune 500 company, is a globally recognized, award-winning financial institution that has been in continuous operation since 1889. Northern Trust is proud to provide innovative financial services and guidance to the world’s most successful individuals, families, and institutions by remaining true to our enduring principles of service, expertise, and integrity. With more than 130 years of financial experience and over 22,000 partners, we serve the world’s most sophisticated clients using leading technology and exceptional service. Job Summary Job Function: Model Development Associate Consultant/Consultant, is a key member of the Risk Analytics and Data Service Team and Responsible for acting as an individual contributor in the development and maintenance of high quality risk analytics. Resolves complex issues in Credit Risk/ PPNR modelling and measuring risk, enhancement in Credit Risk/ PPNR methodologies or other aspects of risk measurement. Job title: Associate Consultant/Consultant Location: Bangalore Experience: 4-8 years of relevant experience Major Duties Responsible for Development of CCAR models (PD/EAD/LGD) , CECL models (PD/EAD/LGD) and Basel models (PD/EAD/LGD). Also for PPNR model development for Non-Interest Income, Net Interest Income, Expense, Deposit, Balance models. Ensures regular production of analytical work.. Collaborates with regulators, Audit Services, and other independent reviewers. Evaluates existing framework in relation to corporate objectives and industry leading practices. Assesses development needs and manages process to achieve desired future state. Supports stress testing, capital quantification and/or internal capital allocation methodologies. Ensures that modelling approaches meet both internal corporate needs and regulatory requirements related to prevailing regulatory guidance. Provides technical/theoretical inputs to resolve risk issues and enhance overall risk framework. Works with other risk or business unit teams to ensure that risk management policies/processes and quantitative modelling approaches are consistent. Operates independently; has knowledge of banking balance sheets and income statements. Conducts analysis, independently ensuring accuracy and completeness. Responsible for interaction with different committees and/or senior management. Qualification Master in Statistics/ Economics/Mathematics/advanced degree in quant area Or B.tech. From tier 1 college with MBA in related field Skills Required Strong BASEL, CCAR and DFAST, SR-11/7 understanding. Strong regulatory understanding 2+ years of hands on model building experience in Credit Risk / PPNR Strong conceptual and technical knowledge of risk concepts and quantitative modelling techniques including familiarity with statistical concepts used in stress testing Strong in quantitative skills – experience in model validation a plus Experience in R, SAS, Matlab, advanced Excel techniques and VBA programming. SAS is preferred Strong Experience in building linear regression models, Nonlinear regression, time series modeling (ARIMA, AR, VAR, MA ) and stochastic process Strong organizational and interpersonal skills Excellent verbal and written communication skills (English) Experience of working in a multi-cultural and global environment Related Industry qualification (e.g., CFA, FRM) a plus Working With Us As a Northern Trust partner, greater achievements await. You will be part of a flexible and collaborative work culture in an organization where financial strength and stability is an asset that emboldens us to explore new ideas. Movement within the organization is encouraged, senior leaders are accessible, and you can take pride in working for a company committed to assisting the communities we serve! Join a workplace with a greater purpose. We’d love to learn more about how your interests and experience could be a fit with one of the world’s most admired and sustainable companies! Build your career with us and apply today. Reasonable accommodation Northern Trust is committed to working with and providing reasonable accommodations to individuals with disabilities. If you need a reasonable accommodation for any part of the employment process, please email our HR Service Center at MyHRHelp@ntrs.com. We hope you’re excited about the role and the opportunity to work with us. We value an inclusive workplace and understand flexibility means different things to different people. Apply today and talk to us about your flexible working requirements and together we can achieve greater. For further information, and to apply, please visit our website via the “Apply” button below. Show more Show less

Job Description: Data Scientist - Forecasting We are seeking a highly analytical and experienced Data Scientist to join our Workforce Planning or Analytics team. The ideal candidate will focus on long-term forecasting for contact center operations, leveraging machine learning models and advanced analytics to drive data-informed decisions using Python, SQL and Power BI. You will play a critical role in projecting future contact volumes, resource requirements, and operational trends, directly supporting strategic planning and optimization efforts across the business. Key Responsibilities Analytics & Insights: Analyze historical trends and seasonality to make informed decisions. Apply machine learning and statistical techniques (e.g., ARIMA, Prophet, XGBoost, LSTM, etc.) to improve forecast accuracy over months and years. Conduct in-depth analysis using Excel or Python to identify key drivers of change in volume. Generate Forecast: Generate monthly forecasts for multiple lobs using machine learning models. Monitor and adjust forecasts based on trends, seasonality, and business updates. Forecast assessment: Evaluate forecast accuracy every month and present key findings. Monitor forecast performance, diagnose deviations, and continuously improve model performance using feedback loops and model validation. Stakeholder Collaboration: Present analytical findings and strategic recommendations to stakeholders, especially around critical days or events. Collaborate with cross-functional teams to understand business requirements and deliver analytical solutions Required Skills & Expertise Technical Skills: Proficiency in Excel, SQL and Python for advanced data analysis, data extraction and data manipulation Hands-on experience with data visualization tools (e.g., Tableau, Power BI) is a plus. Analytical Acumen: Advanced knowledge of Time Series forecasting techniques or Contact Center demand volume forecasting. Ability to work with large datasets and extract meaningful insights to generate forecasts Ability to work on ad-hoc requests to support business needs and derive actionable insights Problem-Solving & Communication: Strong problem-solving skills, with the ability to translate complex analytical findings into clear and actionable recommendations. Excellent communication and data storytelling skills; able to influence stakeholders using evidence-based insights Candidate Profile Educational Background: Bachelor’s/Master’s degree in Analytics, Data Science, Economics, Statistics, Engineering, or a related field. Professional Experience: At least 3-5 years of experience in the data analytics with good experience of Time Series Forecasting. Show more Show less

Dreaming big is in our DNA. It’s who we are as a company. It’s our culture. It’s our heritage. And more than ever, it’s our future. A future where we’re always looking forward. Always serving up new ways to meet life’s moments. A future where we keep dreaming bigger. We look for people with passion, talent, and curiosity, and provide them with the teammates, resources and opportunities to unleash their full potential. The power we create together – when we combine your strengths with ours – is unstoppable. Are you ready to join a team that dreams as big as you do? , AB InBev GCC was incorporated in 2014 as a strategic partner for Anheuser-Busch InBev. The center leverages the power of data and analytics to drive growth for critical business functions such as operations, finance, people, and technology. The teams are transforming Operations through Tech and Analytics. Do You Dream Big? We Need You. Job Description Job Title: Analyst – Junior Data Scientist Location: Bangalore Reporting to: Manager Analytics Purpose of the role Key Tasks & Accountabilities Execute coding skills to develop ML/time-series models. Focus on developing end-to-end analytical solution and present them to business partners/stakeholders. Should have consultative mindset to come up with solutions that can be easily understood and interpreted by business users. Research on the newer technologies and algorithms, to provide better solutions to the current problems. Interact and manage expectations of multiple stakeholders, building compelling narratives and help drive value for businesses by helping them strengthen brands on ground. Qualifications, Experience & Skills Level Of Educational Attainment Required Degree in business analytics / data science / statistics / economics and / or degree in Engineering, Mathematics or Computer Science Previous Work Experience Bachelor’s degree with minimum 2 years of Data Science experience Hands-on experience in implementation of various machine learning algorithms (e.g. SVM, Random Forests, Gradient Boosting, Log-Log regression, XGBoost, Lasso, Ridge, Clustering techniques) and time-series algorithms (e.g. ARIMA, ARIMAX, UCM, Holt-Winters and others) Strong programming skills with working knowledge of SQL, Python. Excellent problem-solving and analytical mindset Strong communication and interpersonal skills Strong story boarding skills And above all of this, an undying love for beer! We dream big to create future with more cheers Show more Show less

Job Title: Data Scientist Location: Navi Mumbai Experience: 3-6 Years Duration: Fulltime Job Summary: We are looking for a highly skilled Data Scientist with deep expertise in time series forecasting, particularly in demand forecasting and customer lifecycle analytics (CLV). The ideal candidate will be proficient in Python or PySpark, have hands-on experience with tools like Prophet and ARIMA, and be comfortable working in Databricks environments. Familiarity with classic ML models and optimization techniques is a plus. Key Responsibilities • Develop, deploy, and maintain time series forecasting models (Prophet, ARIMA, etc.) for demand forecasting and customer behavior modeling. • Design and implement Customer Lifetime Value (CLV) models to drive customer retention and engagement strategies. • Process and analyze large datasets using PySpark or Python (Pandas). • Partner with cross-functional teams to identify business needs and translate them into data science solutions. • Leverage classic ML techniques (classification, regression) and boosting algorithms (e.g., XGBoost, LightGBM) to support broader analytics use cases. • Use Databricks for collaborative development, data pipelines, and model orchestration. • Apply optimization techniques where relevant to improve forecast accuracy and business decision-making. • Present actionable insights and communicate model results effectively to technical and non-technical stakeholders. Required Qualifications • Strong experience in Time Series Forecasting, with hands-on knowledge of Prophet, ARIMA, or equivalent – Mandatory. • Proven track record in Demand Forecasting – Highly Preferred. • Experience in modeling Customer Lifecycle Value (CLV) or similar customer analytics use cases – Highly Preferred. • Proficiency in Python (Pandas) or PySpark – Mandatory. • Experience with Databricks – Mandatory. • Solid foundation in statistics, predictive modeling, and machine learning Show more Show less

Description GlobalLogic seeking a highly analytical and detail-oriented MIS / Workforce Management (WFM) Team Manager to join our team. In this role, you will support operations through accurate reporting, data-driven insights, and efficient workforce planning. Requirements Minimum of 5 years of experience in MIS and/or Workforce Management. Strong background in handling invoicing within service-based environments. Advanced proficiency in Microsoft Excel, including formulas, pivot tables, and macros. Familiarity with Amazon Connect, Monte Carlo simulations, and forecasting models such as SARIMA/ARIMA. Understanding of billing models, specifically BE6. Experience with data visualization tools (e.g., Power BI, Tableau) is a plus. Exceptional attention to detail, with a strong analytical and problem-solving mindset. Excellent communication skills and proven ability to manage stakeholder expectations. Job responsibilities Lead the development and execution of MIS and WFM strategies to enhance operational reporting, forecasting, and efficiency. Design and maintain dashboards and reports using Excel, Power BI, or similar tools to provide actionable insights. Track key workforce metrics such as staffing levels, schedule adherence, and occupancy rates, and provide data-backed recommendations for optimization. Collaborate with internal stakeholders to collect invoice-related data, ensure billing accuracy, and manage timely invoice generation. Reconcile timesheets and billable hours with contract requirements and service level agreements What we offer Culture of caring. At GlobalLogic, we prioritize a culture of caring. Across every region and department, at every level, we consistently put people first. From day one, you’ll experience an inclusive culture of acceptance and belonging, where you’ll have the chance to build meaningful connections with collaborative teammates, supportive managers, and compassionate leaders. Learning and development. We are committed to your continuous learning and development. You’ll learn and grow daily in an environment with many opportunities to try new things, sharpen your skills, and advance your career at GlobalLogic. With our Career Navigator tool as just one example, GlobalLogic offers a rich array of programs, training curricula, and hands-on opportunities to grow personally and professionally. Interesting & meaningful work. GlobalLogic is known for engineering impact for and with clients around the world. As part of our team, you’ll have the chance to work on projects that matter. Each is a unique opportunity to engage your curiosity and creative problem-solving skills as you help clients reimagine what’s possible and bring new solutions to market. In the process, you’ll have the privilege of working on some of the most cutting-edge and impactful solutions shaping the world today. Balance and flexibility. We believe in the importance of balance and flexibility. With many functional career areas, roles, and work arrangements, you can explore ways of achieving the perfect balance between your work and life. Your life extends beyond the office, and we always do our best to help you integrate and balance the best of work and life, having fun along the way! High-trust organization. We are a high-trust organization where integrity is key. By joining GlobalLogic, you’re placing your trust in a safe, reliable, and ethical global company. Integrity and trust are a cornerstone of our value proposition to our employees and clients. You will find truthfulness, candor, and integrity in everything we do. About GlobalLogic GlobalLogic, a Hitachi Group Company, is a trusted digital engineering partner to the world’s largest and most forward-thinking companies. Since 2000, we’ve been at the forefront of the digital revolution – helping create some of the most innovative and widely used digital products and experiences. Today we continue to collaborate with clients in transforming businesses and redefining industries through intelligent products, platforms, and services. Show more Show less

Title : Senior Manager -Data Science, Machine Learning and GenAI Technical Leader 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 solutionsFunctional & 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 practicesProactive in reaching out to wide variety of stakeholders for increasing the awareness of Data Science, ML and GenAI capabilities and identifying business value driven opportunitiesAnalyze 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 dataConduct research, design statistical studies and develop solutionsDevelop Story Telling dashboards on analytics to assist business in decision makingImplement deep learning models for structured and unstructured data setsPerform 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 frameworksAbility to develop capabilities in Text Analytics ranging from Basic to Advanced (Topic Modelling, NLP)Experience with AWS suite of Data Science and ML toolsDevelops 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 EngineeringExposure 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 Bachelors degree. 4+ years in a leadership role in projects/programs.

Job Description: Forecasting Specialist with Expertise in Inventory Management We are looking for a Forecasting Specialist with a strong background in inventory management and data-driven demand forecasting . This role is focused on optimizing inventory levels and enhancing supply chain efficiency through advanced forecasting models and analytical tools. The ideal candidate will bring expertise in statistical forecasting, data analysis, and technical systems to improve retail inventory operations. Responsibilities Statistical Demand Forecasting : Utilize advanced statistical techniques (e.g., ARIMA , exponential smoothing , seasonal decomposition , regression models ) to create accurate demand forecasts and inventory plans. Inventory Optimization : Apply mathematical models like EOQ (Economic Order Quantity) , Safety Stock Calculation , and Replenishment Algorithms to optimize inventory levels and minimize holding costs. Data Analysis & Reporting : Extract and analyze large datasets from various sources, utilizing SQL and advanced analytics tools to forecast trends, detect anomalies, and ensure inventory alignment with demand. Forecasting Model Development : Continuously develop, refine, and evaluate statistical models to improve forecasting accuracy and adapt to changing consumer behavior. System Integration : Work with ERP systems (e.g., SAP , Oracle ) and integrate them with forecasting platforms (e.g., Demand Works , Forecast Pro ) to streamline inventory management processes and ensure real-time data synchronization. Automation and Scripting : Write Python or R scripts to automate data extraction, cleaning, analysis, and forecasting tasks. Data Visualization & Communication : Leverage tools like Power BI , Tableau , or Google Data Studio to build dashboards that present inventory insights and forecasting accuracy to stakeholders in an actionable format. Continuous Improvement : Apply machine learning techniques (e.g., regression models , decision trees , ensemble methods ) to enhance forecasting models and adapt to new retail trends. Key Technical Skills Statistical Tools & Forecasting : Expertise in R or Python for statistical analysis and time series forecasting. In-depth knowledge of forecasting techniques (ARIMA, Holt-Winters, Exponential Smoothing). Understanding of advanced regression and machine learning algorithms applied to demand prediction and trend analysis. SQL & Database Management Proficiency in writing complex SQL queries to extract and manipulate data from inventory and sales databases (MySQL, PostgreSQL, etc.). Experience working with relational databases and cloud-based solutions for inventory data management. Inventory Optimization Algorithms Advanced understanding of inventory models such as ABC Classification , Just-In-Time (JIT) , Reorder Point (ROP) , Safety Stock Optimization , and Vendor-Managed Inventory (VMI) . Ability to apply algorithms to dynamically adjust reorder quantities based on fluctuating demand. Data Visualization & Business Intelligence Expertise in data visualization tools like Power BI to present key performance metrics and inventory analytics to non-technical stakeholders. Ability to create interactive dashboards that display key inventory KPIs (e.g., stock levels, turnover rates, and demand forecasts). Automation & Scripting Proficient in Python (pandas, NumPy) or R for scripting and automating inventory analysis and forecasting processes. Experience with Jupyter Notebooks or RStudio for developing reproducible analysis workflows. Additional Skills Machine Learning (ML) : Knowledge of machine learning algorithms (e.g., XGBoost , Random Forests , Neural Networks ) for improving predictive accuracy in demand forecasting. Desired Qualifications Bachelor's degree in Statistics , Computer Science , Supply Chain Management , or a related field. Proven experience in a similar technical forecasting or inventory management role, preferably in a retail or e-commerce setting. Strong problem-solving skills and a keen attention to detail in data quality and accuracy. This is a high-impact, technical role where you will leverage your expertise in statistical forecasting , data analysis , and inventory optimization to drive significant improvements in retail inventory management systems. If you are passionate about using advanced data science techniques to solve complex supply chain problems, we encourage you to apply. Show more Show less

About The Role We are seeking a highly skilled and hands-on Senior Data Scientist with 7+ years of experience to lead the design and implementation of robust machine learning pipelines and drive data-driven decision making across the organization. This role requires a strategic thinker who can bridge the gap between complex data science concepts and practical business solutions, while ensuring model integrity, explainability, and compliance in production environments. As a Senior Data Scientist, you will have end-to-end ownership of the model life cycle, from data ingestion and feature engineering to model deployment, monitoring, and governance. Youll work closely with AI engineers, product teams, and stakeholders to deliver high-impact solutions that drive business value. Key Responsibilities Machine Learning & Predictive Modeling : Design and build sophisticated predictive models using Scikit-learn, XG Boost, LightGBM, and CatBoost for various use cases. Develop advanced forecasting models using Prophet, ARIMA, and neural forecasting techniques for time series analysis. Implement anomaly detection systems and risk scoring models for fraud detection and security applications Create recommendation systems and personalization algorithms using collaborative filtering and deep learning approaches AI Integration & Pipeline Development Collaborate with AI engineers to integrate traditional ML components into LangChain and LLM-driven intelligent systems Design hybrid architectures that combine classical ML with generative AI for enhanced business solutions Develop evaluation frameworks for comparing traditional ML and LLM based approaches Implement retrieval systems that enhance LLM performance with domain specific knowledge Model Lifecycle Management Automate comprehensive model lifecycle processes including training, validation, deployment, and rollback procedures Implement continuous training pipelines using MLFlow, Kubeflow, and Weights & Biases Design and maintain model monitoring systems for drift detection, performance degradation, and data quality issues Establish model governance frameworks ensuring reproducibility and auditability Data Validation & Quality Assurance Lead the development of pre-model and post-model validation frameworks using DeepChecks, Great Expectations, and custom validation rules Implement fairness and bias detection systems using Fairlearn and custom algorithmic auditing tools Design comprehensive data quality monitoring and alerting systems Conduct statistical testing and hypothesis validation for model performance claims Compliance & Security Ensure PII protection and DPDP compliance through secure data preprocessing and anonymization techniques Implement synthetic data generation pipelines using Gretel.ai and other privacy-preserving technologies Design policy-driven access controls and data governance frameworks using Apache Griffin and DataHub Conduct privacy impact assessments and implement differential privacy techniques where applicable Model Explainability & Auditing Develop comprehensive model explainability frameworks using SHAP, LIME, and custom interpretation tools Conduct reasoning-based walkthroughs and accuracy audits for deployed models Perform bias analysis and fairness assessments across different demographic groups Design and implement A/B testing frameworks for model performance evaluation Data Engineering & Pipeline Architecture Design and implement scalable ETL/ELT pipelines using Apache Spark, Flink, and modern data processing frameworks Leverage Redis for intelligent caching strategies and real-time feature serving Implement streaming data processing using Apache Kafka, RabbitMQ, and event-driven architectures Optimize data pipeline performance and ensure data consistency across distributed systems (ref:hirist.tech) Show more Show less

Job Title: Data Scientist Electric Load Forecasting Location: Mumbai / Pune Job Type: Full-time Experience: 3-5 years About the Role: We are seeking a highly motivated Data Scientist – Forecasting 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: 3-5 years 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 .

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