1143 Statistical Modeling Jobs - Page 16

Role And Responsibilities : - Work with stakeholders throughout the organization to identify opportunities for leveraging company data to drive business solutions. - Mine and analyze data from company databases to drive optimization and improvement of business strategies. - Assess the effectiveness and accuracy of data sources and data gathering techniques. - Develop custom data models and algorithms to apply to data sets. - Use predictive modelling to increase and optimize business outcomes. - Work individually or with extended teams to operationalize models & algorithms into structured software, programs or operational processes - Coordinate with different functional teams to implement models and monitor outcomes. - Develop processes and tools to monitor and analyze model performance and data accuracy. - Provide recommendations to business users based upon data/ model outcomes, and implement recommendations including changes in operational processes, technology or data management - Primary area of focus: PSCM/ VMI business; secondary area of focus: ICS KPI s - Business improvements pre & post (either operational program, algorithm, model or resultant software). Improvements measured in time and/or dollar savings - Satisfaction score of business users (of either operational program, algorithm, model or resultant software). Qualifications And Education Requirements - Graduate BSc/BTech in applied sciences with year 2 statistics courses. - Relevant Internship (at least 2 months) OR Relevant Certifications of Preferred Skills. Preferred Skills - Strong problem-solving skills with an emphasis on business development. - Experience the following coding languages : - R or python (Data Cleaning, Statistical and Modelling packages) , SQL, VBA and DAX (PowerBI) - Knowledge of working with and creating data architectures. - Knowledge of a variety of machine learning techniques (clustering, decision tree learning, artificial neural networks, etc.) and their real-world advantages/drawbacks. - Knowledge of advanced statistical techniques and concepts (regression, properties of distributions, statistical tests, and proper usage, etc.) and experience with applications. - Excellent written and verbal communication skills for coordinating across teams. - A drive to learn and master new technologies and technique Compliance Requirements : - GET has a Business Ethics Policy which provides guidance to all employees in their day-to-day roles as well as helping you and the business comply with the law at all times. The incumbent must read, understand and comply with, at all times, the policy along with all other corresponding policies, procedures and directives. QHSE Responsibilities - Demonstrate a personal commitment to Quality, Health, Safety and the Environment. - Apply GET, and where appropriate Client Company s, Quality, Health, Safety & Environment Policies and Safety Management Systems. - Promote a culture of continuous improvement, and lead by example to ensure company goals are achieved and exceeded. Skills - Analytical skills - Negotiation - Convincing skills Key Competencies - Never give up attitude - Flexible - Eye to detail Experience: Minimum 8 Years Of Experience

Design, develop, and maintain scalable, efficient, and reliable systems to support GenAI and machine learning-based applications and use cases Lead the development of data pipelines, architectures, and tools to support data-intensive projects, ensuring high performance, security, and compliance Collaborate with other stakeholders to integrate AI and ML models into production-ready systems Work closely with non-backend expert counterparts, such as data scientists and ML engineers, to ensure seamless integration of AI and ML models into backend systems Ensure high-quality code, following best practices, and adhering to industry standards and company guidelines Hard Requirements: Senior backend engineer with a proven track record of owning the backend portion of projects Experience collaborating with product, project, and domain team members Strong understanding of data pipelines, architectures, and tools Proficiency in Python (ability to read, write and debug Python code with minimal guidance) Mandatory Skills: Machine Learning: experience with machine learning frameworks, such as scikit-learn, TensorFlow, or PyTorch Python: proficiency in Python programming, with experience working with libraries and frameworks, such as NumPy, pandas, and Flask Natural Language Processing: experience with NLP techniques, such as text processing, sentiment analysis, and topic modeling Deep Learning: experience with deep learning frameworks, such as TensorFlow, or PyTorch Data Science: experience working with data science tools Backend: experience with backend development, including design, development, and deployment of scalable and modular systems Artificial Intelligence: experience with AI concepts, including computer vision, robotics, and expert systems Pattern Recognition: experience with pattern recognition techniques, such as clustering, classification, and regression Statistical Modeling: experience with statistical modeling, including hypothesis testing, confidence intervals.

Join Innodatas global Data Science team as an LLM Research Data Scientist and drive innovation in Multimodal Large Language Models and Agentic Workflows. In this position, you’ll contribute across the full LLM lifecycle, from data collection and post-training to evaluation and benchmarking. Collaborate closely with our data engineering teams to translate data into client-facing insights. Enjoy the freedom to publish scientific work and contribute to open-source initiatives. Key Responsibilities Analyze existing workflows and data pipelines to extract insights, identify areas of improvement, and propose recommendations. Collaborate with internal teams and clients to operationalize findings. Specialize in one of the following focus areas: oData: Collection, curation, and synthetic data creation oModeling: Multimodal post-training and agentic workflow creation oEvaluation: LLM and Agent benchmarking and performance analysis What We Look For Strong communication and collaboration skills across technical and non-technical audiences Ability to work autonomously, self-motivated, ambitious Client-facing mindset: active listening, clear articulation of findings and recommendations Willingness to help upskill teammates in data science and generative AI fundamentals Qualifications Master’s degree in Data Science, Computer Science or a related field 10+ years of experience in data science and client-facing roles High proficiency with AI tools (e.g., Copilots, GenAI platforms) and applying them to complex real-world use cases Expert-level Python skills, with deep familiarity with LLM frameworks for data manipulation, post training and evaluation

Overview Accelerate PepsiCo business growth by supporting the North America DX Sector Leads with Category analysis, Space and assortment strategy recommendations to drive growth Responsible for delivering assortment and space analysis, category performance reviews, and addressing ad-hoc customer requests, based on internal and external data sources Provide analytics to support key strategic customer engagements and to support category assortment and space interventions Responsibilities Supports in the creation and driving of winning execution strategies in-store with customers. Identifies sales opportunities and optimization tactics to drive category demand, space and assortment Space Management- Optimizing shelf space allocation for products. Assortment Planning- Developing tailored product assortments for retail locations. Qualifications An experienced Insight or Analytics professional with experience in a leading consumer goods company with 10+ years EducationMBA, Masters or bachelors in engineering/economics, statistics, marketing. LanguageEnglish Fluent High degree of familiarity with CPG and Food & Beverage industry data sources, including Nielsen/IRi (POS and HH panel), Kantar Worldpanel, etc. Deep understanding of CPG industry business performance outputs and causal measures, their relationships, and how to address business questions in a robust way that translates to simple outputs Proficient with Power Point and advance Excel skills. Willingness to learn new tools and capabilities. Strong collaboratorInterested and motivated by working with others. Actively creates and participates in opportunities to co-create solutions across markets; will be willing and able to embrace Responsive Ways of Working Can easily see how insights/research learning can improve businesses impact and frames up presentation efforts and opportunities to inform business decisions Proven analytics, shopper research experience, or consumer insights experience applying statistics to CPG industry business problems Problem solvingA bility to approach complex problems methodically and develop effective solutions. Operational experience from business servicing sector and/or consulting experience would be a plus Essential Become an indispensable partner for Sector Commercial by showing great thought leadership with ability to recognize and take actions to improve delivery of work. Not always being asked. Navigating conflict in a collaborative way to provide a solution that works for GBS & Sector. Ability to work in diverse teams Solution-oriented approach to problem solving Possess ability to analyze & benchmark competitive scenarios Depth and breadth of syndicated data analytics and statistical modeling Ability to work collaboratively and proactively with multi-functional teams Complete understanding of internal & external data sources that could contribute to analytics roles across service centers Strong analytical thinking with proven ability to connect data & insight from category consumption, brands drivers, macro & micro trends, and future forces of consumer change and deliver clear implications for the business.

Job Title:Artificial Intelligence EngineerExperience8-12 YearsLocation:Bangalore : Algorithm Development**Design and implement algorithms, neural networks, and other machine learning techniques to simulate human intelligence processes. Model Creation**Develop and validate algorithms, neural networks, and other machine learning models. Generative AI**Specialize in generative AI, which involves creating AI systems that autonomously generate content such as text, images, and music. Machine Learning**Leverage your expertise in machine learning to train models on large datasets and optimize them for creative content generation. Natural Language Processing (NLP)**Apply NLP techniques for text generation projects, including text parsing, sentiment analysis, and the use of transformer models like GPT. Data Management**Handle data pre-processing, augmentation, and synthetic data generation. Qualifications To excel in this role, you should possess the following skills: Hard Skills1. **Advanced Programming**Proficiency in programming languages such as Python, along with AI-centric libraries like TensorFlow, PyTorch, and Keras.2. **Generative Models**Expertise in generative models, including Generative Adversarial Networks (GANs) and Variational Autoencoders (VAEs).3. **NLP**Familiarity with NLP techniques for text generation.4. **Data Management**Knowledge of data pre-processing, augmentation, and synthetic data generation.Soft Skills1. **Creativity**Ability to think creatively and solve complex, creative challenges using AI.2. **Collaboration**Work effectively with researchers, engineers, and other team members.3. **Continuous Learning**Stay updated with evolving AI technologies and applications.Qualifications- Bachelor's or Master's degree in Computer Science, Artificial Intelligence, or related fields.- Proven experience in machine learning, generative AI,

An R Shiny web developerbuilds interactive data visualization and analysis tools using the R programming language and the Shiny framework.They design, develop, and deploy dashboards and applications that allow users to explore and manipulate data dynamically.This role often involves data manipulation, UI/UX design, and ensuring the application runs efficiently. Here's a more detailed breakdown of an R Shiny web developer's responsibilities: Responsibilities: Building and Maintaining Shiny Applications: Designing, developing, and maintaining interactive dashboards and applications using R and Shiny. Implementing user interfaces (UI) and server-side logic. Ensuring applications are visually appealing and user-friendly. Updating existing applications based on changes in functionality or requirements. Debugging and testing applications to ensure they function correctly. Data Handling and Manipulation: Analyzing datasets, both structured and unstructured, to identify relationships and prepare data for loading into databases. Creating and managing data pipelines and ETL (Extract, Transform, Load) processes. Data Visualization and Reporting: Developing visualizations, reports, and dashboards using R Shiny. Creating data pipelines that integrate various data sources to create comprehensive visualizations. Collaboration and Communication: Working closely with other developers, data scientists, and subject matter experts. Communicating technical information clearly and concisely. Proposing solutions to technical challenges and application improvements. Mandatory Competencies Data Science and Machine Learning - Data Science and Machine Learning - R Shiny User Interface - Other User Interfaces - JavaScript Beh - Communication and collaboration UX - UX - Photoshop

Responsibilities: *Teach statistics subjects * Teach statistical principles using software tools * Publish academic papers related to statistics

GreenCell Mobility is seeking a strategic and analytical Senior Manager - Pricing and Competition Benchmarking Analyst to develop and implement competitive pricing strategies. This role is critical for optimizing revenue, ensuring alignment with dynamic market conditions in the electric bus and shared mobility sector, and achieving key business objectives. The incumbent will be responsible for continuous monitoring of competitors, analyzing market trends, and providing actionable insights to drive informed pricing decisions and maintain GreenCell Mobility's competitive positioning. Key Responsibilities: Competitive Benchmarking: Conduct regular, in-depth analysis of competitor pricing, promotions, and service offerings within the electric bus and broader mobility sector. Identify strategic gaps and opportunities in existing fare structures to ensure GreenCell Mobility maintains a strong competitive edge. Continuously monitor new market entrants and emerging trends in the bus industry, including dynamic and subscription-based pricing models relevant to electric mobility. Market Analysis: Evaluate evolving market conditions, customer travel preferences, and regional demand fluctuations to directly influence and refine pricing strategies. Analyze the impact of significant events such as festivals, regulatory changes, and local economic conditions on pricing models. Revenue Optimization: Utilize advanced analytical tools and methodologies to meticulously analyze occupancy rates and revenue per trip for various routes and services. Implement and manage dynamic pricing strategies to effectively maximize revenue during peak demand periods and high-demand routes. Proactively identify and mitigate risks associated with underperforming routes through strategic pricing adjustments. Data-Driven Insights: Develop and maintain comprehensive dashboards and reports to track pricing performance, monitor competitor trends, and analyze market share. Translate complex data into clear, actionable insights and recommendations for senior management. Collaboration and Stakeholder Engagement: Work closely and collaboratively with operations, sales, and other internal stakeholders to ensure pricing strategies are fully aligned with customer acquisition, retention, and operational efficiency goals. Coordinate effectively with finance teams to evaluate the detailed impacts of pricing decisions on overall revenue and profitability. Compliance and Standardization: Ensure strict adherence to all relevant industry regulations and internal pricing policies. Maintain consistent and standardized fare structures across all distribution channels and partners, including Online Travel Agencies (OTAs), GreenCell Mobility's own platforms, and Offline ticket counters. Preferred Candidate Profile: Proven experience in competitive pricing strategy development and analysis within the transportation, mobility-as-a-service (MaaS), or a related dynamic industry. Strong analytical skills with proficiency in data analysis, statistical modeling, and financial forecasting. Expertise in market research, competitive intelligence gathering, and benchmarking methodologies. Familiarity with dynamic pricing models, subscription-based services, and revenue management principles. Advanced proficiency in data visualization tools (e.g., Tableau, Power BI) and advanced Excel. Excellent communication, presentation, and interpersonal skills, with the ability to articulate complex insights to diverse audiences. Ability to work collaboratively in a cross-functional environment and influence decision-making. A strong understanding of the bus and electric mobility sector is highly preferred. Demonstrated ability to manage multiple priorities and work effectively in a fast-paced, evolving market.

Roles and Responsibilities Characterization of plasma proteins by various physicochemical methods Responsible for stability sample analysis by different methods and its data management Analytical Method Qualification and Analytical Technology transfer Method Development & Troubleshooting Instruments Handling/ Techniques: SDS-Page , HPLC , GC, IEF and Western blot, ELISA Reference standard qualification, instrument & micropipette calibration Responsible for document preparation/review of LPs, MOA, MQP, MQR,TTD and documentation of related activities Desired Candidate Profile Candidate should have experience in biopharma/ biotech industry

As an Economic Analyst for North America (NAM) at the Mastercard Economics Institute (MEI), you will play a crucial role in contributing to economic research and data analytics for the U.S. and Canada. Reporting directly to the VP, Lead Economist for North America, you will be responsible for engaging in client and stakeholder interactions, collaborating with external partners, and generating actionable insights to support impactful economic storylines and visuals. Your role will involve synthesizing analyses into clear recommendations, assisting in the creation of reports and client presentations, and enhancing existing products while also contributing to the development of new solutions. You will be expected to proactively seek new knowledge, structure project work efficiently, and actively participate in thought leadership activities to continuously improve the quality and productivity of economic research initiatives. To excel in this role, you must hold a Bachelor's degree in Economics, Statistics, or Mathematics, with a strong background in statistical modeling, quantitative analysis, and data engineering, particularly in economic research. Proficiency in SQL and Hadoop is essential, along with expertise in statistical packages such as R, Python, and Tableau. Knowledge of JavaScript for data visualization is advantageous, and experience in financial services would be beneficial. In addition to technical skills, excellent communication and strong writing abilities are required for effective collaboration and presentation of insights. You should be willing to learn new statistical applications or software as needed and demonstrate proficiency in key econometric and statistical techniques to support the Institute's mission to provide valuable economic insights for customers, partners, and policymakers.,

GreenCell Mobility is seeking a strategic and analytical Senior Manager - Pricing and Competition Benchmarking Analyst to develop and implement competitive pricing strategies. This role is critical for optimizing revenue, ensuring alignment with dynamic market conditions in the electric bus and shared mobility sector, and achieving key business objectives. The incumbent will be responsible for continuous monitoring of competitors, analyzing market trends, and providing actionable insights to drive informed pricing decisions and maintain GreenCell Mobility's competitive positioning. Key Responsibilities: Competitive Benchmarking: Conduct regular, in-depth analysis of competitor pricing, promotions, and service offerings within the electric bus and broader mobility sector. Identify strategic gaps and opportunities in existing fare structures to ensure GreenCell Mobility maintains a strong competitive edge. Continuously monitor new market entrants and emerging trends in the bus industry, including dynamic and subscription-based pricing models relevant to electric mobility. Market Analysis: Evaluate evolving market conditions, customer travel preferences, and regional demand fluctuations to directly influence and refine pricing strategies. Analyze the impact of significant events such as festivals, regulatory changes, and local economic conditions on pricing models. Revenue Optimization: Utilize advanced analytical tools and methodologies to meticulously analyze occupancy rates and revenue per trip for various routes and services. Implement and manage dynamic pricing strategies to effectively maximize revenue during peak demand periods and high-demand routes. Proactively identify and mitigate risks associated with underperforming routes through strategic pricing adjustments. Data-Driven Insights: Develop and maintain comprehensive dashboards and reports to track pricing performance, monitor competitor trends, and analyze market share. Translate complex data into clear, actionable insights and recommendations for senior management. Collaboration and Stakeholder Engagement: Work closely and collaboratively with operations, sales, and other internal stakeholders to ensure pricing strategies are fully aligned with customer acquisition, retention, and operational efficiency goals. Coordinate effectively with finance teams to evaluate the detailed impacts of pricing decisions on overall revenue and profitability. Compliance and Standardization: Ensure strict adherence to all relevant industry regulations and internal pricing policies. Maintain consistent and standardized fare structures across all distribution channels and partners, including Online Travel Agencies (OTAs), GreenCell Mobility's own platforms, and Offline ticket counters. Preferred Candidate Profile: Proven experience in competitive pricing strategy development and analysis within the transportation, mobility-as-a-service (MaaS), or a related dynamic industry. Strong analytical skills with proficiency in data analysis, statistical modeling, and financial forecasting. Expertise in market research, competitive intelligence gathering, and benchmarking methodologies. Familiarity with dynamic pricing models, subscription-based services, and revenue management principles. Advanced proficiency in data visualization tools (e.g., Tableau, Power BI) and advanced Excel. Excellent communication, presentation, and interpersonal skills, with the ability to articulate complex insights to diverse audiences. Ability to work collaboratively in a cross-functional environment and influence decision-making. A strong understanding of the bus and electric mobility sector is highly preferred. Demonstrated ability to manage multiple priorities and work effectively in a fast-paced, evolving market.

You are an experienced Senior Quantitative Analyst (Model Developer/Validator) with a strong background in credit risk modeling, particularly focusing on Internal Credit Risk Rating modeling. Your expertise will be crucial in leading the development and validation of sophisticated credit risk models for retail and wholesale portfolios. Your responsibilities will include developing and validating credit risk models such as PD, EAD, LGD, with a special emphasis on Expert judgement-based PD models for Corporate, Specialised Lending, and Financial Institutions. You will also be responsible for data preparation and preprocessing using tools like SAS, Python, R, and SQL. Collaborating with various stakeholders to analyze and interpret complex model results and insights will be a key aspect of your role. In addition, you will develop technical documentation for regulatory compliance, test plans, validation reports, and business requirements documents. You will drive continuous model improvement by identifying optimization opportunities, implementing advanced modeling techniques, and enhancing model performance. Mentoring and providing technical guidance to junior team members will be part of your responsibilities to encourage a culture of knowledge sharing and professional development. To be successful in this role, you should have 5-10 years of hands-on experience in credit risk model development and validation, along with proven expertise in modeling across retail and wholesale credit portfolios. Advanced proficiency in SAS, Python, R, and SQL is essential, as well as a deep understanding of IFRS9 and CECL regulatory frameworks. Strong analytical and problem-solving skills, along with excellent written and verbal communication abilities, are also required. Preferred qualifications include an advanced degree in Statistics, Mathematics, Economics, or a related field, professional certifications in risk management or financial modeling, experience with IRB modeling, machine learning/advanced statistical modeling techniques, and knowledge of Basel regulatory guidance. Your technical skills should encompass model development (PD, LGD, EAD, Qualitative PD Models), programming (SAS, Python, R, SQL), regulatory knowledge (IRB, IFRS9, CECL), statistical modeling, data preprocessing, and machine learning techniques.,

As a Senior Analytics Consultant in the banking sector, you will leverage your expertise in areas such as credit risk modeling, fraud detection, and marketing analytics to lead client-facing engagements. With over 5 years of experience, you will play a key role in designing and implementing advanced models, translating data insights into strategic recommendations, and ensuring compliance with regulatory standards. Your responsibilities will include leading and managing analytics projects focusing on credit risk, fraud analytics, and marketing analytics for banking clients. You will collaborate with clients to define business problems, develop analytic frameworks, build and validate statistical and machine learning models, and present complex analytical findings in a clear and business-friendly manner. Additionally, you will guide junior team members, contribute to knowledge sharing, and uphold regulatory standards in risk and fraud modeling. To excel in this role, you are required to have a Bachelor's or Master's degree in Statistics, Economics, Mathematics, Computer Science, or a related quantitative discipline. Your hands-on experience in banking analytics, proficiency in SQL and analytical programming languages such as Python, R, or SAS, strong understanding of statistical modeling techniques, and excellent communication skills will be essential. Preferred qualifications include prior consulting experience, familiarity with cloud-based analytics platforms, and exposure to regulatory model validation frameworks. Join us for high-impact projects with top banking institutions, a collaborative team culture, clear paths for career growth, and competitive compensation.,

The Specialized Analytics Senior Analyst is a seasoned professional role that requires in-depth disciplinary knowledge and expertise. You will contribute to the development of new techniques and process improvements within your area of function. Your role will involve integrating subject matter and industry expertise to ensure the smooth operation of processes. You must have a comprehensive understanding of how different areas integrate within the sub-function and how they contribute to the overall objectives of the function and business. You will be responsible for evaluating moderately complex issues with potential impacts, requiring you to weigh various alternatives and balance conflicting situations using multiple sources of information. Strong analytical skills are essential to filter, prioritize, and validate complex material from diverse sources. Excellent communication and diplomacy skills are also required as you will often assume informal or formal leadership roles within teams, coaching and training new recruits. Your influence will have a significant impact on project size and geography by providing advice, counsel, and facilitating services in your area of specialization. The performance of all teams in the area will directly depend on your performance. Responsibilities: - Work with large and complex data sets to evaluate, recommend, and support the implementation of business strategies - Identify and compile data sets using tools like SQL and Access to predict, improve, and measure the success of key business outcomes - Document data requirements, data collection/processing/cleaning, and exploratory data analysis, potentially utilizing statistical models/algorithms and data visualization techniques - Specialize in marketing, risk, digital, and AML fields - Appropriately assess risk in business decisions to safeguard Citigroup, its clients, and assets by driving compliance with laws and regulations Qualifications: - 8-12 years of experience - Proficient in retrieving and manipulating data - Advanced analytic ability and problem-solving skills to address business questions with data-driven solutions - Ability to build partnerships with cross-functional teams - Experience in a quantitative field, preferably in the Financial/Credit Card industry - Willingness to learn with a can-do attitude - Excellent communication and interpersonal skills, detail-oriented, flexible, and adaptive to a matrix work environment Education: - Bachelors/University degree or equivalent experience This job description provides an overview of the work performed, and additional duties may be assigned as required.,

The role of Asset Predictive Analytics (APA) support for industrial clients involves utilizing data analysis and machine learning techniques to predict potential failures and optimize maintenance strategies for mechanical equipment. As the ideal candidate, you will have a strong understanding of mechanical systems, data analysis, and predictive modeling to enhance equipment reliability and minimize downtime. Your responsibilities will include implementing Asset Predictive Analytics (APA) for major rotating and static equipment, such as compressors, pumps, turbines, motors, blowers, fans, heaters, distillation columns, transformers, and heat exchangers. You will be involved in data collection and analysis, developing and implementing predictive models, and optimizing maintenance schedules based on predictive insights to prevent unplanned downtime. To qualify for this role, you should hold a B.E/B.Tech degree in Mechanical or Chemical Engineering, along with a minimum of 5-7 years of experience in APA within industrial sectors, preferably oil & gas. Proficiency in AVEVA Predictive Analytics or similar solutions, as well as knowledge of reliability principles, tools, and methodologies, is essential. You should also possess strong skills in data analysis, statistical modeling, programming languages like Python or R, and experience in developing predictive models using machine learning algorithms. In addition, you must demonstrate the ability to communicate technical information effectively to both technical and non-technical audiences, engage with stakeholders at a senior level, and work collaboratively with maintenance teams. Your competency should include strong interpersonal skills, a self-aware and self-developmental approach, and a systematic work ethic with attention to detail. The role may involve travel as per business needs. Clients in Energy, Oil & Gas, Refining, Petrochemicals, Chemicals, Mining, Supply Chain, Utilities, Power, and Manufacturing industries will be your primary focus.Embrace change, develop innovative solutions, and challenge the status quo to excel in this dynamic role.,

As a Data Science Associate Director at Accenture Strategy & Consulting's Global Network Data & AI practice in the Resources team, your role will involve collaborating with clients and stakeholders to drive business growth and identify new opportunities. You will be responsible for solution architecting, designing, building, deploying, delivering, and monitoring advanced analytics models to address various client problems. Your strategic mindset will play a crucial role in translating engineering and business problems into analytics challenges to deliver actionable insights and operational enhancements. Your responsibilities will include interfacing with clients and account teams, collaborating with internal Accenture teams to drive sales, identifying new use cases with cross-functional teams, and providing innovation and thought leadership in key capability areas. Additionally, you will manage and mentor a high-performing team of data analysts working on large-scale datasets, cloud platforms, IoT, and similar data sets. To excel in this role, you should possess excellent communication and interpersonal skills, a strategic mindset, and a solid foundation in Statistical Modeling, Machine Learning algorithms, and Experimental design. Your 15+ years of experience in Data Science with a focus on cloud services will be valuable, along with expertise in programming languages such as Python, PySpark, SQL, or Scala. Experience in Utilities, Energy, Chemical, and Natural Resources sectors is preferred. Implementing MLOps practices, understanding data integration, modeling, warehousing concepts, and possessing strong analytical and problem-solving skills are essential for this position. A Bachelor's/Masters's degree in Mathematics, Statistics, Computer Science, Computer Engineering, or a related field is required. Relevant certifications in Azure Data Services or cloud data engineering are highly desirable. Your ability to work effectively with cross-functional teams, stakeholders, and provide analytically-informed insights at scale will be key to achieving high performance and driving business growth in this role.,

The Data Science Analyst role at Citi, located in Gurgaon, is a developing professional position within the GWFO team. As a Data Science Analyst, you will utilize specialized knowledge in machine learning, statistical modeling, and data analysis to evaluate processes and data, identifying opportunities for leveraging advanced analytics to enhance business outcomes. You will play a key role in automating processes, generating actionable insights, and developing innovative AI solutions to contribute to the organization's success. Collaboration with cross-functional stakeholders is a fundamental aspect of this role. In this position, your responsibilities will include gathering and processing operational data from various stakeholders, applying machine learning techniques to identify data patterns and trends, developing and implementing machine learning models for predictive analytics, and designing Generative AI solutions to enhance customer experience. You will also experiment with agentic AI frameworks, develop tools to evaluate AI solutions" performance, and translate data into consumer insights to drive targeting and segmentation strategies. Effective communication of findings to business partners and senior leaders is essential for success in this role. The ideal candidate should possess 5+ years of relevant experience in data science or a related field, advanced process management skills, a curious mindset for learning new skill sets, and strong programming skills in Python. Proficiency in relevant data science libraries, experience with statistical modeling techniques, and familiarity with data visualization tools are required. Additionally, strong logical reasoning capabilities, willingness to learn new skills, and good communication and presentation skills are essential for this position. A Bachelor's/University degree or equivalent experience in a quantitative field is necessary, with a Master's degree being preferred. Working at Citi offers more than just a job it provides the opportunity to join a global family of dedicated individuals, grow your career, contribute to your community, and make a meaningful impact. If you require a reasonable accommodation due to a disability to access our search tools or apply for a career opportunity, please review the Accessibility at Citi information. For more details, you can refer to Citis EEO Policy Statement and the Know Your Rights poster.,

You are a skilled Quantitative Researcher who will be joining our team to develop advanced algorithmic trading strategies for cryptocurrency markets. Leveraging your deep quantitative skills, market insights, and statistical modeling, you will be responsible for researching, designing, and testing trading strategies that capture alpha in digital asset markets. Your key responsibilities will include researching and developing quantitative trading strategies for crypto markets across spot, perpetual futures, and derivatives. You will analyze market microstructure, order flow, and liquidity to identify trading opportunities. Additionally, you will design and implement statistical and machine learning models for signal generation, risk forecasting, and anomaly detection. It will be essential for you to perform extensive backtesting, simulation, and performance analysis using historical and live data. Furthermore, optimizing strategies for execution costs, slippage, latency, and market impact will be part of your responsibilities. Collaboration with developers to translate research into production-grade algorithmic trading systems is also a key aspect of the role. Monitoring live strategies and conducting post-trade analysis to refine and improve models, staying updated on market trends, blockchain analytics, protocol updates, and evolving market structure, and contributing to research documentation, strategy reports, and knowledge sharing within the team are also part of your duties. The required skills and qualifications for this role include a strong background in quantitative research, statistical modeling, or applied mathematics, solid programming skills in Python, R, or similar languages for data analysis and prototyping, experience with time series analysis, signal processing, and statistical inference, ability to work with large datasets, proficiency in data cleaning, feature engineering, and data visualization, understanding of trading concepts such as PnL attribution, Sharpe ratio, drawdown, and risk management, interest in cryptocurrency markets and familiarity with crypto-specific market dynamics, excellent problem-solving and critical-thinking skills, and ability to communicate complex quantitative ideas clearly to technical and non-technical stakeholders. Preferred qualifications for this role include prior experience in algorithmic trading or systematic strategy development (crypto or traditional markets), knowledge of crypto market microstructure, DeFi protocols, and blockchain data analytics, familiarity with exchange APIs, order types, and execution logic, experience with backtesting frameworks and simulation environments, machine learning experience applied to financial markets (e.g. feature selection, ensemble models, reinforcement learning), and an academic background in quantitative disciplines (e.g. Mathematics, Statistics, Physics, Computer Science, Engineering, Finance).,

You are an experienced Lead Data Scientist with a minimum of 8 years of professional experience, including at least 6 years in a data science role. Your expertise lies in statistical modeling, machine learning, deep learning, and GenAI. Proficiency in Python is a must, along with hands-on experience in optimizing code for performance. You excel in data preprocessing, feature engineering, data visualization, hyperparameter tuning, and have a solid understanding of database concepts, especially while working with large datasets. You have experience deploying and scaling machine learning models in a production environment, along with familiarity with machine learning operations (MLOps) and related tools. Your knowledge extends to Generative AI concepts and LLM finetuning, supported by excellent communication and collaboration skills. Your responsibilities as a Lead Data Scientist include guiding and mentoring a high-performance team on the latest technology landscape, patterns, and design standards. You provide strategic direction and technical leadership for AI initiatives, leading the design and architecture of complex AI systems. Your role involves developing and deploying machine learning/deep learning models to address key business challenges, applying various techniques in statistical modeling, data preprocessing, feature engineering, and more. You are proficient in areas such as computer vision, predictive analytics, natural language processing, time series analysis, and recommendation systems. Furthermore, you design and optimize data pipelines for model training and deployment, utilizing model serving frameworks and APIs for integration with other systems. Your qualifications include a Bachelor's or Master's degree in a quantitative field such as statistics, mathematics, computer science, or a related area. Your primary skills encompass Python, Data Science concepts, Pandas, NumPy, Matplotlib, Artificial Intelligence, Statistical Modeling, Machine Learning, Natural Language Processing (NLP), Deep Learning, Model Serving Frameworks, MLOps, Computer Vision, Predictive Analytics, Time Series Analysis, Anomaly Detection, Recommendation Systems, Generative AI, and proficiency in Cloud Computing Platforms. Your secondary skills involve expertise in designing scalable and efficient model architectures, the ability to assess and forecast financial requirements of data science projects, and strong communication skills for conveying technical concepts to stakeholders. As a Lead Data Scientist, you stay updated with the latest advancements in data science and machine learning, particularly in generative AI, to evaluate their potential applications and serve as a primary point of contact for client managers.,

The Spec Analytics Intmd Analyst is a developing professional role. You will be dealing with most problems independently and have some latitude to solve complex problems. It is essential to integrate in-depth specialty area knowledge with a solid understanding of industry standards and practices. You should have a good understanding of how the team and area integrate with others in accomplishing the objectives of the sub function/job family. Applying analytical thinking and knowledge of data analysis tools and methodologies is crucial. Attention to detail is required when making judgments and recommendations based on the analysis of factual information. You will typically deal with variable issues with potentially broader business impact and apply professional judgment when interpreting data and results. Breaking down information in a systematic and communicable manner will be one of your responsibilities. Developed communication and diplomacy skills are required in order to exchange potentially complex/sensitive information. There will be a moderate but direct impact through close contact with the business's core activities. The quality and timeliness of the service provided by you will affect the effectiveness of your own team and other closely related teams. Responsibilities: - Work with large and complex data sets (both internal and external data) to evaluate, recommend, and support the implementation of business strategies - Identify and compile data sets using a variety of tools (e.g., SQL, Access) to help predict, improve, and measure the success of key business outcomes - Document data requirements, data collection/processing/cleaning, and exploratory data analysis, which may include utilizing statistical models/algorithms and data visualization techniques - Specialization in marketing, risk, digital, and AML fields is possible - Assess risk appropriately when making business decisions, demonstrating particular consideration for the firm's reputation and safeguarding Citigroup, its clients, and assets by driving compliance with applicable laws, rules, and regulations, adhering to policy, applying sound ethical judgment regarding personal behavior, conduct, and business practices, and escalating, managing, and reporting control issues with transparency Qualifications: - 5-7 years of relevant experience - Ability to retrieve and manipulate data - Possess analytic ability and problem-solving skills - Working experience in a quantitative field - Willingness to learn and a can-do attitude - Excellent communication and interpersonal skills, be organized, detail-oriented, flexible, and adaptive to a matrix work environment - Ability to build partnerships with cross-functional leaders Education: - Bachelor's/University degree or equivalent experience This job description provides a high-level review of the types of work performed. Other job-related duties may be assigned as required. If you are a person with a disability and need a reasonable accommodation to use our search tools and/or apply for a career opportunity, review Accessibility at Citi. View Citis EEO Policy Statement and the Know Your Rights poster.,

Critical Skills to Possess: Advanced working knowledge and experience with relational and non-relational databases. Advanced working knowledge and experience with API data providers Experience building and optimizing Big Data pipelines, architectures, and datasets. Strong analytic skills related to working with structured and unstructured datasets. Hands-on experience in Azure Databricks utilizing Spark to develop ETL pipelines. Strong proficiency in data analysis, manipulation, and statistical modeling using tools like Spark, Python, Scala, SQL, or similar languages. Strong experience in Azure Data Lake Storage Gen2, Azure Data Factory, Databricks, Event Hub, Azure Synapse. Familiarity with several of the following technologies: Event Hub, Docker, Azure Kubernetes Service, Azure DWH, API Azure, Azure Function, Power BI, Azure Cognitive Services. Azure DevOps experience to deploy the data pipelines through CI/CD. Preferred Qualifications: BS degree in Computer Science or Engineering or equivalent experience Roles and Responsibilities Roles and Responsibilities: You are detailed reviewing and analyzing structured, semi-structured and unstructured data sources for quality, completeness, and business value. You design, architect, implement and test rapid prototypes that demonstrate value of the data and present them to diverse audiences. You participate in early state design and feature definition activities. Responsible for implementing robust data pipeline using Microsoft, Databricks Stack Responsible for creating reusable and scalable data pipelines. You are a Team-Player, collaborating with team members across multiple engineering teams to support the integration of proven prototypes into core intelligence products. You have strong communication skills to effectively convey complex data insights to non-technical stakeholders.

Responsibilities : Lead AI Strategy: Oversee AI/ML projects from development to deployment, ensuring alignment with business goals. Model Development & Fine-tuning: Lead the fine-tuning of LLMs and advanced NLP models to meet enterprise needs. Team Leadership: Manage and mentor data science teams, fostering growth and innovation. Cross-functional Collaboration: Work with engineers, product teams, and leadership to drive AI initiatives. Optimization & Deployment: Ensure efficient workflows, containerization (Docker), and scalable model deployment. Client Engagement: Provide strategic insights and translate AI capabilities into business solutions. Good to Have: Cloud Platform Expertise: Experience working with AWS, Azure, or GCP on large-scale AI/ML projects. Enterprise Solutions: Familiarity with enterprise Knowledge Management Systems and their integration with AI-driven tools. Advanced MLOps: Deep understanding of MLOps principles and tools to ensure efficient model deployment and monitoring. Problem-Solving: Ability to break down complex problems into manageable components and design effective solutions. Innovation: A passion for experimenting with cutting-edge AI/ML technologies and applying them to real-world business problems. Required Skills: Technical Skills: Proficiency in Python, with strong expertise in libraries such as PyTorch, Pandas, and NumPy. Extensive experience in fine-tuning large language models (LLMs) and applying advanced NLP techniques. Strong background in handling both structured and unstructured data, with hands-on experience working on complex data transformations. Proficiency in MLOps tools, including Docker, Kubernetes, and cloud platforms (AWS, Azure, or GCP). In-depth knowledge of model optimization, deployment pipelines, and scalable production environments. Ability to design and implement AI/ML workflows that balance speed and quality in a fast-paced environment. Leadership Skills: Proven ability to lead and manage teams of data scientists, driving results through mentorship and strategic guidance. Strong project management skills, with experience handling multiple AI projects simultaneously and ensuring timely delivery. Exceptional communication skills to work with cross-functional teams and explain complex AI concepts to non-technical stakeholders.

Please Note- Its 6 days WFO from Client location in Kolkata Role & responsibilities Data Science & AI Specialist in Kolkata requires strong programming skills in Python and experience with AI/ML libraries (e.g., Scikit-learn, TensorFlow, PyTorch, XGBoost). Proficiency in Jupyter and Databricks, along with experience in time-series modeling, advanced regression, anomaly detection, and optimization algorithms , is necessary. An understanding of energy systems, including renewables, grid infrastructure, and smart meters, is advantageous. Candidates should be familiar with cloud platforms (AWS, Azure, GCP) and MLOps tools for model deployment and monitoring, as well as data visualization tools (Power BI) and version control (Git). The ideal candidate will have a bachelors or master’s degree in relevant fields and 2+ years of experience in AI and data science projects , preferably in the energy domain Kindly note that resource must travel to Kolkata Sector 5 client office daily ( No work from home ) and 6 Days a week working

As a Fortune 50 company with more than 400,000 team members worldwide, Target is an iconic brand and one of America's leading retailers. Joining Target means promoting a culture of mutual care and respect and striving to make the most meaningful and positive impact. Becoming a Target team member means joining a community that values different voices and lifts each other up. Here, we believe your unique perspective is important, and you'll build relationships by being authentic and respectful. Overview about TII At Target, we have a timeless purpose and a proven strategy. And that hasnt happened by accident. Some of the best minds from different backgrounds come together at Target to redefine retail in an inclusive learning environment that values people and delivers world-class outcomes. That winning formula is especially apparent in Bengaluru, where Target in India operates as a fully integrated part of Targets global team and has more than 4,000 team members supporting the companys global strategy and operations. Pyramid Overview A role with Target Data Science & Engineering means the chance to help develop and manage state of the art predictive algorithms that use data at scale to automate and optimize decisions at scale. Whether you join our Statistics, Optimization or Machine Learning teams, youll be challenged to harness Targets impressive data breadth to build the algorithms that power solutions our partners in Marketing, Supply Chain Optimization, Network Security and Personalization rely on. Team Overview Target Data Sciences is offering an exciting opportunity to solve state of the art problems in e-commerce search . Targets Search Technology team is rapidly growing and creating a massive business impact by building cutting edge search systems. We use NLP, deep learning, classical machine learning and LLMs to build the best in class systems. As we build the future of e-commerce search, we are looking for driven and passionate individuals with deep expertise in building ML and engineering systems for Search . If you are that person, you can expect to be involved in: Designing, building and and integrating systems for solving problems across query and content understanding, ranking and relevance and external search Influencing roadmaps and driving its execution with a team of talented scientists and engineers Developing a multi-year vision for search on Target.com Preferred domain experience Creating tech led solutions in e-commerce search and recommendations About You: 4-year degree in quantitative disciplines (Science, Technology, Engineering, Mathematics) or equivalent experience 3+ years of professional experience or equivalent industry experience Good knowledge and experience developing deep learning, NLP, classical ML and LLM based solutions Strong analytical thinking skills . Ability to creatively solve business problems, innovating new approaches, where required Strong hands-on programming skills in Python , SQL and Spark Passion for solving interesting and relevant real-world problems using a data science approach Excellent communication skills . Able to communicate with both technical and non-technical audiences. Self-driven and results oriented Strong team player with ability to collaborate effectively across geographies/time zones Know More here: Life at Target - https://india.target.com/ Benefits - https://india.target.com/life-at-target/workplace/benefits Culture- https://india.target.com/life-at-target/belonging

As a Fortune 50 company with more than 400,000 team members worldwide, Target is an iconic brand and one of America's leading retailers. Joining Target means promoting a culture of mutual care and respect and striving to make the most meaningful and positive impact. Becoming a Target team member means joining a community that values different voices and lifts each other up. Here, we believe your unique perspective is important, and you'll build relationships by being authentic and respectful. Overview about TII At Target, we have a timeless purpose and a proven strategy. And that hasnt happened by accident. Some of the best minds from different backgrounds come together at Target to redefine retail in an inclusive learning environment that values people and delivers world-class outcomes. That winning formula is especially apparent in Bengaluru, where Target in India operates as a fully integrated part of Targets global team and has more than 4,000 team members supporting the companys global strategy and operations. Pyramid overview A role with Target Data Science & Engineering means the chance to help develop and manage state of the art predictive algorithms that use data at scale to automate and optimize decisions at scale. Whether you join our Statistics, Optimization or Machine Learning teams, youll be challenged to harness Targets impressive data breadth to build the algorithms that power solutions our partners in in Marketing, Supply Chain Optimization, Network Security and Personalization rely on Every Scientist on Targets Data Sciences team can expect modeling and data science, software/product development of highly performant code for Model Performance, and to elevate Targets culture and apply retail domain knowledge. Position Overview: As a Senior Data Scientist, you will be involved in end-to-end development of Ad-Tech products and capabilities that fulfil strategic priorities and power growth of Roundel, Targets Retail media business. You will leverage understanding of data and algorithms to build prototypes and run experiments to evaluate them against given specifications. As you follow agile processes, you will implement and deploy a scalable data science solution by using MLOps best practices across model development life cycle. You will collaborate with product and business partners to seek feedback on effectiveness of solution and identify future opportunities for enhancements. You will work with your peers to create a well-maintainable & tested codebase with relevant documentation. The exciting part of retail and mediaIts always changing! Core responsibilities of this job are described within this job description. Job duties may change at any time due to business needs. About You: 4-year degree in Quantitative disciplines (Science, Technology, Engineering, Mathematics) or equivalent experience 3+ years of professional experience or equivalent industry experience Good knowledge and experience developing optimization, simulation and statistical models Strong analytical thinking skills. Ability to creatively solve business problems, innovating new approaches, where required Strong hands-on programming skills in Python, SQL, Spark, Hadoop/Hive . Good working knowledge of mathematical and statistical concepts, MILP, algorithms and computational complexity Passion for solving interesting and relevant real-world problems using a data science approach Experience in implementing advanced statistical techniques like r egression, clustering, PCA, forecasting (time series) etc. Able to produce reasonable documents/narrative suggesting actionable insights Excellent communication skills. Ability to clearly tell data driven stories through appropriate visualizations, graphs and narratives Self-driven and results oriented; able to meet tight timelines Strong team player with ability to collaborate effectively across geographies/time zones Know More here: Life at Target - https://india.target.com/ Benefits - https://india.target.com/life-at-target/workplace/benefits Culture- https://india.target.com/life-at-target/belonging