214 Linear Regression Jobs - Page 2

Salary : 40 to 55 LPA Exp: 8 to 12 years Location :Gurugram Hybrid Notice: Immediate to 30 days..!! Roles & responsibilities: 7+ years exp on Python , ML and model development Interact with the client to understand their requirements and communicate / brainstorm solutions, model Development: Design, build, and implement credit risk model. Contribute to how analytical approach is structured for specification of analysis Contribute insights from conclusions of analysis that integrate with initial hypothesis and business objective. Independently address complex problems 8+ years exp on ML/Python (predictive modelling) . Design, implement, test, deploy and maintain innovative data and machine learning solutions to accelerate our business. Create experiments and prototype implementations of new learning algorithms and prediction techniques Collaborate with product managers, and stockholders to design and implement software solutions for science problems Use machine learning best practices to ensure a high standard of quality for all of the team deliverables Has experience working on unstructured data ( text ): Text cleaning, TFIDF, text vectorization Hands-on experience with IFRS 9 models and regulations. Data Analysis: Analyze large datasets to identify trends and risk factors, ensuring data quality and integrity. Statistical Analysis: Utilize advanced statistical methods to build robust models, leveraging expertise in R programming. Collaboration: Work closely with data scientists, business analysts, and other stakeholders to align models with business needs. Continuous Improvement: Stay updated with the latest methodologies and tools in credit risk modeling and R programming.

Salary : 20 to 35 LPA Exp: 3 to 8 years Location :/Gurugram/Bangalore/Hyderabad Notice: Immediate to 30 days..!! Roles & responsibilities: 3+ years exp on Python , ML and Banking model development Interact with the client to understand their requirements and communicate / brainstorm solutions, model Development: Design, build, and implement credit risk model. Contribute to how analytical approach is structured for specification of analysis Contribute insights from conclusions of analysis that integrate with initial hypothesis and business objective. Independently address complex problems 3+ years exp on ML/Python (predictive modelling) . Design, implement, test, deploy and maintain innovative data and machine learning solutions to accelerate our business. Create experiments and prototype implementations of new learning algorithms and prediction techniques Collaborate with product managers, and stockholders to design and implement software solutions for science problems Use machine learning best practices to ensure a high standard of quality for all of the team deliverables Has experience working on unstructured data ( text ): Text cleaning, TFIDF, text vectorization Hands-on experience with IFRS 9 models and regulations. Data Analysis: Analyze large datasets to identify trends and risk factors, ensuring data quality and integrity. Statistical Analysis: Utilize advanced statistical methods to build robust models, leveraging expertise in R programming. Collaboration: Work closely with data scientists, business analysts, and other stakeholders to align models with business needs. Continuous Improvement: Stay updated with the latest methodologies and tools in credit risk modeling and R programming.

Salary : 25 to 40 LPA Exp: 4 to 8 years Location :/Gurugram/Bangalore/Hyderabad Notice: Immediate to 30 days..!! Roles & responsibilities: 3+ years exp on Python , ML and Banking model development Interact with the client to understand their requirements and communicate / brainstorm solutions, model Development: Design, build, and implement credit risk model. Contribute to how analytical approach is structured for specification of analysis Contribute insights from conclusions of analysis that integrate with initial hypothesis and business objective. Independently address complex problems 3+ years exp on ML/Python (predictive modelling) . Design, implement, test, deploy and maintain innovative data and machine learning solutions to accelerate our business. Create experiments and prototype implementations of new learning algorithms and prediction techniques Collaborate with product managers, and stockholders to design and implement software solutions for science problems Use machine learning best practices to ensure a high standard of quality for all of the team deliverables Has experience working on unstructured data ( text ): Text cleaning, TFIDF, text vectorization Hands-on experience with IFRS 9 models and regulations. Data Analysis: Analyze large datasets to identify trends and risk factors, ensuring data quality and integrity. Statistical Analysis: Utilize advanced statistical methods to build robust models, leveraging expertise in R programming. Collaboration: Work closely with data scientists, business analysts, and other stakeholders to align models with business needs. Continuous Improvement: Stay updated with the latest methodologies and tools in credit risk modeling and R programming.

Practical in applying geometric concepts, with strong Python & SQL skills. Creative problem-solver, innovator, able to build agent-driven solutions. Senior dev with TDD, AWS knowledge preferred over Ph.D.

The selected individuals will be responsible for conducting training sessions for professionals and corporates on various Analytical tools and techniques, with a focus on BI tools such as SAS, R, SPSS, Python, Tableau, and VBA. Their main duties will involve developing relevant content and materials for the program and other technologies as directed by the organization. Successful candidates will have the opportunity to grow into key positions within the organization and may explore roles in training, content development, and research based on their interests and potential. Candidates for this role should hold a MA/MSc/ MPhil/ Phd (pursuing) degree in Economics, Statistics, Mathematics, or B-Tech, with 0-2 years of work experience in a similar industry. Key prerequisites for the role include an understanding of BI tools, a working knowledge of Advanced Excel (VBA Macros), a strong grasp of Analytical concepts, and proficiency in basic Statistical Concepts such as Descriptive Statistics, Probability, Hypothesis testing, Factor Analysis, Cluster Analysis, Linear Regression, Logistic Regression, and Time series Modeling. Other essential skills and qualities include excellent Presentation, Team Handling, and People Skills. Preference will be given to candidates with consistent academic records and those with leadership experience in extracurricular activities. Candidates with a Masters in Statistics or Economics, knowledge of Econometrics, and proficiency in Base SAS, Advanced SAS, R-Programming, SPSS, Excel, VBA, and Tableau will be preferred. Additionally, familiarity with various analytical concepts such as Linear Regression, Logistic Regression, Time Series, Cluster Analysis, Factor Analysis, Analysis of Variance, Sentiment Analysis, Market Basket Analysis, CHAID- Decision Tree, Text Mining, Survival Analysis, Credit Risk, and Customer Analytics will be advantageous for this role.,

Data Science Machine Learning Specialist Location Thiruvananthapuram Experience 4 to 5 yrs 4 5 years of hands-on experience in data science projects, preferably across different domains. Strong statistical expertise, including hypothesis testing, linear and non-linear regression, classification techniques, and probability distributions. Proven ability to translate complex business problems into data science use cases with practical impact. Experienced in building and validating machine learning models, including classification, regression, and survival analysis. Proficiency in Python, including libraries like Pandas, NumPy, Scikit-learn, Matplotlib, and Seaborn, as well as SQL for data querying and analysis. Experience handling both structured and unstructured datasets, with expertise in exploratory data analysis (EDA) and data cleaning. Strong communication skills, with the ability to explain technical concepts clearly to non-technical stakeholders. Familiarity with version control tools such as Git/GitHub and collaborative development workflows. A deployment mindset, with an understanding of how to build data products that are usable, scalable, and maintainable.

About OJ Commerce: OJ Commerce (OJC), a rapidly expanding and profitable online retailer, is headquartered in Florida, USA, with a fully-functional office in Chennai, India. We deliver exceptional value to our customers by harnessing cutting-edge technology, fostering innovation, and establishing strategic brand partnerships to enable a seamless, enjoyable shopping experience featuring high-quality products at unbeatable prices. Our advanced, data-driven system streamlines operations with minimal human intervention. Our extensive product portfolio encompasses over a million SKUs and more than 2,500 brands across eight primary categories. With a robust presence on major platforms such as Amazon, Walmart, Wayfair, Home Depot, and eBay, we directly serve consumers in the United States. As we continue to forge new partner relationships, our flagship website, www.ojcommerce.com, has rapidly emerged as a top-performing e-commerce channel, catering to millions of customers annually. Responsibilities: • 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

You will be joining Dark Matter Technologies, a company leading the tech-driven revolution in loan origination with cutting-edge AI and origination technology solutions. As a Senior Data Scientist, your role will involve building machine learning models, using various algorithms for regression, prediction, and deep learning. You will be responsible for identifying data sources, analyzing data, writing machine code in Python (or Azure ML), and creating models. The job location is in Hyderabad and Bhubaneswar. Your responsibilities will include selecting features, building, and optimizing classifiers using machine learning techniques, conducting hypothesis testing, and developing predictive models. You will collaborate with cross-functional teams to integrate AI models into business solutions, conduct research to improve AI models and algorithms, and stay updated with the latest AI/ML technologies and trends. Additionally, you will implement and deploy AI models using cloud AI services while ensuring the quality and scalability of AI solutions. To qualify for this role, you should have at least 10 years of experience in Predictive Analytics and Data Mining, with hands-on experience in various areas such as linear regression, classification techniques, logistic regression, unsupervised learning techniques, feature reduction methods, and optimization methods. You must be proficient in working with R/Python, T-SQL, and graph-based models, with hands-on development experience in Python. Understanding of Azure Machine Learning and other Azure AI tools is essential, along with proficiency in data modeling, design, SQL development, and deploying machine learning models for key use cases. Preferred skills include exposure to machine learning libraries like Scikit-learn, TensorFlow, or PyTorch, leveraging Azure Machine Learning for managing data pipelines, experiments, and deployments, and implementing end-to-end AI solutions using Azure AI services. Certification in Microsoft Azure AI relative to Azure Machine Learning, expert database knowledge in SQL, and proficiency in Azure Data Services are also advantageous. You should possess strong problem-solving skills, the ability to work independently and as part of a team, excellent communication skills to convey complex technical concepts to non-technical stakeholders, and a solid understanding of statistical analysis and machine learning algorithms. Your role will involve working with large-scale datasets, ensuring efficiency and scalability in data processing, collaborating with stakeholders to design data science solutions, and presenting analytical findings and business insights to project managers and senior leadership. Keeping abreast of new statistical and machine learning techniques is crucial to improve predictive performance.,

We are a collaborative, tight knit group of contributors. While we re headquartered in the Chicago area in Oak Brook, our software lab is located in Pune, India. We have decades of experience working with remote teams. We re looking to expand our Developer positions in Pune, India. You ll find our technology managers a joy to work with; people with excellent technical skills, always willing to mentor, roll up their sleeves and get deep into technical issues. Our management possesses rare technical insight coupled with a remarkable business vision. You ll be working as a key member of our technical team in what will be an amazing opportunity for you. Your work environment: We are a group of talented and dedicated individuals and though we are a software company, we have a no insane hours rule. We are not clock watchers. If you need to take off for a couple of hours to visit the doctor or dentist go ahead. We look at what you re accomplishing not how many hours you spend in the office. We conduct meetings on a daily basis with our Chicago office so some overlapping hours are necessary. Our work is performed using the latest technology and tools. We re constantly innovating and improving our delivery capability by building our own components and tools as well as licensing new tech that we ve tried and works in our environment. We are an open, collaborative work environment and suggestions are not just welcome, they are appreciated. You ll find our product roadmap is exciting and full of opportunity. We believe in compensating our core team with higher than prevailing market wage. Your skills: You keep up with technology changes and trends. You are a top notch Developer whose code not only solves complex issues but is written in such a way that the rest of your team is able to understand. This means that you re not shy about documenting your code and you understand the need for coding standards and why everyone should use them.

Salary : 25 to 40 LPA Exp: 4 to 8 years Location :/Gurugram/Bangalore/Hyderabad Notice: Immediate to 30 days..!! Roles & responsibilities: 3+ years exp on Python , ML and Banking model development Interact with the client to understand their requirements and communicate / brainstorm solutions, model Development: Design, build, and implement credit risk model. Contribute to how analytical approach is structured for specification of analysis Contribute insights from conclusions of analysis that integrate with initial hypothesis and business objective. Independently address complex problems 3+ years exp on ML/Python (predictive modelling) . Design, implement, test, deploy and maintain innovative data and machine learning solutions to accelerate our business. Create experiments and prototype implementations of new learning algorithms and prediction techniques Collaborate with product managers, and stockholders to design and implement software solutions for science problems Use machine learning best practices to ensure a high standard of quality for all of the team deliverables Has experience working on unstructured data ( text ): Text cleaning, TFIDF, text vectorization Hands-on experience with IFRS 9 models and regulations. Data Analysis: Analyze large datasets to identify trends and risk factors, ensuring data quality and integrity. Statistical Analysis: Utilize advanced statistical methods to build robust models, leveraging expertise in R programming. Collaboration: Work closely with data scientists, business analysts, and other stakeholders to align models with business needs. Continuous Improvement: Stay updated with the latest methodologies and tools in credit risk modeling and R programming.

Salary : 20 to 35 LPA Exp: 3 to 8 years Location :/Gurugram/Bangalore/Hyderabad Notice: Immediate to 30 days..!! Roles & responsibilities: 3+ years exp on Python , ML and Banking model development Interact with the client to understand their requirements and communicate / brainstorm solutions, model Development: Design, build, and implement credit risk model. Contribute to how analytical approach is structured for specification of analysis Contribute insights from conclusions of analysis that integrate with initial hypothesis and business objective. Independently address complex problems 3+ years exp on ML/Python (predictive modelling) . Design, implement, test, deploy and maintain innovative data and machine learning solutions to accelerate our business. Create experiments and prototype implementations of new learning algorithms and prediction techniques Collaborate with product managers, and stockholders to design and implement software solutions for science problems Use machine learning best practices to ensure a high standard of quality for all of the team deliverables Has experience working on unstructured data ( text ): Text cleaning, TFIDF, text vectorization Hands-on experience with IFRS 9 models and regulations. Data Analysis: Analyze large datasets to identify trends and risk factors, ensuring data quality and integrity. Statistical Analysis: Utilize advanced statistical methods to build robust models, leveraging expertise in R programming. Collaboration: Work closely with data scientists, business analysts, and other stakeholders to align models with business needs. Continuous Improvement: Stay updated with the latest methodologies and tools in credit risk modeling and R programming.

About Northern Trust Northern Trust is a globally recognized, award-winning financial institution that has been in continuous operation since 1889. We take pride in providing 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 over 130 years of financial experience and more than 22,000 partners, we serve sophisticated clients using leading technology and exceptional service. The Model Risk Management Group (MRMG) is a centralized function within the bank focusing on model risk management. We are currently looking for a Senior Consultant, Risk Analytics to join our team. The primary responsibility of this role is to lead the discovery and diagnostic of model-related risks, including input data, assumptions, conceptual soundness, methodology, outcomes analysis, benchmarking, monitoring, and model implementation. As a Senior Consultant, Risk Analytics, you will: - Validate models developed in Python, R, and occasionally SAS, challenging the conceptual soundness of regression and machine learning models, and ensuring the use of appropriate and high-quality data. - Demonstrate advanced proficiency in financial models used in portfolio analysis, asset management, Value at Risk, Monte Carlo, CAPM, Factors. - Possess a solid understanding of risks posed by AI/ML models and stress testing, CCAR, CECL, etc. - Solve complex quantitative problems, analyze solutions independently, and utilize expertise in machine learning algorithms and statistics. - Review and evaluate bank-wide quantitative models, ensuring regulatory compliance and internal risk management needs are met. - Establish and maintain relationships with key stakeholders such as model developers, owners, and users. Qualifications for this role include: - 8-10 years of modeling or quantitative analysis experience, preferably in risk management. - A degree in a STEM field, mathematics, actuarial science, engineering, or related discipline (Advanced degree preferred). - Strong interpersonal, verbal, and written communication skills. - Programming experience in Python required, experience in SAS and R desired. - Mastery of analytical tools such as Excel, Word, and PowerPoint. - Deep understanding of linear regression and logistic regression. - Experience with Machine Learning models desired. - Familiarity with cloud and big data technologies desired. At Northern Trust, you will have the opportunity to work in a flexible and collaborative culture that encourages movement within the organization. We are committed to assisting the communities we serve and value inclusivity and flexibility in the workplace. If you are interested in joining one of the world's most admired and sustainable companies, apply today and let us know how your interests and experience align with our mission. #MadeForGreater Northern Trust is committed to providing reasonable accommodations for individuals with disabilities. If you require accommodation during the employment process, please contact our HR Service Center at MyHRHelp@ntrs.com. We look forward to welcoming you to our team and working together to achieve greater success. Apply now and discuss your flexible working requirements to help us create a more inclusive workplace.,

About Northern Trust: Northern Trust is a globally recognized, award-winning financial institution that has been in continuous operation since 1889. With over 22,000 partners and more than 130 years of financial experience, Northern Trust takes pride in providing innovative financial services and guidance to the world's most successful individuals, families, and institutions while upholding enduring principles of service, expertise, and integrity. The Model Risk Management Group (MRMG) is a centralized function within the Bank that has experienced rapid growth in response to increasing global regulatory focus on model risk. We are currently seeking a Consultant, Risk Analytics to join our team. In this role, your primary responsibility will be to support the model validation function, acting as a lead contributor in identifying and diagnosing model-related risks across various aspects including input data, assumption, methodology, and outcomes analysis. Key Responsibilities: - Validate models primarily developed in Python or SAS, with a focus on challenging the conceptual soundness of machine learning models and ensuring the quality of input data. - Demonstrate advanced proficiency in financial models related to portfolio analysis, asset management, Value at Risk, Monte Carlo simulations, CAPM, and factors. - Exhibit a solid understanding of risks associated with AI/ML models, such as Fairness, Privacy, Transparency, and Explainability. - Engage in stress testing, CCAR, CECL, and other relevant areas. - Solve complex quantitative problems, analyze possible solutions, and develop a deep understanding of various algorithms and machine learning techniques. - Review and assess bank-wide quantitative models including those used for CECL, CCAR/DFAST stress testing, credit risk projections, operational risk, AML, and other machine learning models. - Ensure model development, monitoring, and validation approaches align with regulatory expectations and internal risk management needs. - Evaluate model specifications, assumptions, testing completeness, and performance metrics, while documenting observations and recommending remediation actions. - Maintain strong relationships with key stakeholders like model developers, owners, and users. Qualifications: - 6 to 8 years of modeling or quantitative analysis experience in a relevant discipline. - A degree in STEM field, mathematics, actuarial science, engineering, or statistics (Advanced degree preferred). - Strong interpersonal, verbal, and written communication skills. - Proficiency in Python, with experience in SAS and R desired. - Mastery of analytical tools like Excel, Word, and PowerPoint. - Deep understanding of linear and logistic regression, along with experience in Machine Learning models. - Familiarity with cloud and big data technologies is a plus. Joining Northern Trust offers a chance to be part of a flexible and collaborative work culture where innovation is encouraged, and career growth is supported. As a company committed to serving communities, Northern Trust values inclusivity and flexibility in the workplace. Apply today to explore opportunities with one of the world's most esteemed and sustainable companies. #MadeForGreater Northern Trust is dedicated to providing reasonable accommodations to individuals with disabilities. If you require accommodation during the employment process, please contact MyHRHelp@ntrs.com. We look forward to learning more about your interests and experiences and discussing how you can contribute to our team. Share your flexible working requirements with us, and together, we can achieve greater success.,

You will be owning the design and implementation of processes to extract, transform and load data from disparate sources into a form that is consumable by analytics processes, for large or more sophisticated projects, using advanced technical capabilities You will take accountability to produce a suite of data models with relatively high complexity, demonstrating a strong understanding of data modelling standards to ensure high quality Working with other departments across the business to help define and deliver business value, as well as interfacing and presenting with program teams, management and partners to deliver large, sophisticated projects Your key responsibilities include Evaluating and resolving issues regarding data quality reviews, cleansing, data integration and migration, demonstrating sophisticated data engineering skills Analyzing the latest industry trends and latest technologies Developing strong working relationships with peers across engineering, collaborating to develop leading data engineering solutions Batch Processing - Capability to design an efficient way of processing high volumes of data where a group of transactions is collected over a period of time Data Integration (Sourcing, Storage and Migration) - Capability to design and implement models, capabilities and solutions to handle data within the enterprise (structured and unstructured, data archiving principles, data warehousing, data sourcing, etc.). This includes the data models, storage requirements and migration of data from one system to another Data Quality, Profiling and Cleansing - Capability to review (profile) a data set to establish its quality against a defined set of parameters and to highlight data where corrective action (cleansing) is required to remediate the data Stream Systems - Capability to discover, integrate, and ingest all available data from the machines that produce it, as fast as its produced, in any format, and at any quality

At EY, you'll have the chance to build a career as unique as you are, with the global scale, support, inclusive culture, and technology to become the best version of yourself. We are counting on your unique voice and perspective to help EY become even better. Join us to build an exceptional experience for yourself and contribute to creating a better working world for all. As a Manager - AI/GenAI in the Data and Analytics team at EY, you will be part of a multi-disciplinary technology team delivering client projects and solutions across various domains like Data Mining & Management, Visualization, Business Analytics, Automation, Statistical Insights, and AI/GenAI. Your responsibilities will include developing and delivering industry-specific solutions using Artificial Intelligence, Machine Learning, deep learning, Generative AI, text analytics, and Python Programming. These solutions will be utilized to implement EY SaT mergers and acquisition methodologies across different sectors such as Financial Services, Consumer, Product & Retail, Healthcare & Wellness, Manufacturing, Supply Chain, Telecom, Real Estate, etc. Your key responsibilities will involve: - Developing, reviewing, and implementing solutions applying AI, Machine Learning, Deep Learning, and creating APIs using Python. - Leading the development and implementation of Generative AI applications using both open source (Llama, BERT, Dolly, etc.) and closed source (Open AI GPT models, MS Azure Cognitive Services, Google's Palm, Cohere, etc.) Large Language Models (LLMs). - Working with advanced models like GPT-3.5, GPT 4, Llama, BERT for natural language processing and creative content generation. - Designing and optimizing solutions using Vector databases for efficient storage and retrieval of contextual data for LLMs. - Identifying opportunities for analytics applications based on business understanding within different sectors. - Managing projects of various sizes, ensuring smooth service delivery, studying resource needs, and communicating effectively with cross-functional teams. To qualify for this role, you must have: - Experience in guiding teams on AI/Data Science projects and presenting results to clients. - Proficiency in implementing solutions in Azure Cloud Framework and excellent presentation skills. - 9-14 years of relevant work experience in developing and implementing AI and Machine Learning models, with deployment experience in Azure preferred. - Expertise in statistical techniques, deep learning, machine learning algorithms, NLG, LLM, and DL Techniques. - Strong programming skills in Python, experience with SDLC, and the ability to mentor team members. - Excellent communication skills, strategic thinking abilities, and a client-centric approach. Ideally, you should also possess: - Strategic thinking skills with a result-oriented mindset. - Ability to build rapport with clients and stakeholders. - Willingness to travel and work at various client sites and practice office locations. At EY, we look for individuals with commercial acumen, technical expertise, and a willingness to learn in a fast-paced environment. You will have the opportunity to work with a diverse team of professionals globally, across various industries, and be part of a market-leading, multi-disciplinary team. In addition, you will be part of the EY Global Delivery Services (GDS) network, offering fulfilling career opportunities and the chance to collaborate with teams from all EY service lines and geographies. Join us at EY and be part of building a better working world, where you will have access to continuous learning, transformative leadership, and a diverse and inclusive culture. EY teams around the world provide trust through assurance and help clients grow, transform, and operate by asking better questions to find new answers for the complex issues facing our world today.,

Collect, clean, and analyze large datasets from multiple sources. Build and deploy machine learning and statistical models to solve business challenges. Perform exploratory data analysis (EDA) to identify trends, patterns, and insights.

What Data Science contributes to Cardinal Health The Data & Analytics Function oversees the analytics lifecycle in order to identify, analyze and present relevant insights that drive business decisions and anticipate opportunities to achieve a competitive advantage. This function manages analytic data platforms, the access, design and implementation of reporting/business intelligence solutions, and the application of advanced quantitative modeling. Data Science applies base, scientific methodologies from various disciplines, techniques and tools that extract knowledge and insight from data to solve complex business problems on large data sets, integrating multiple systems. Qualifications 2-4 years of experience, preferred Bachelor's degree in related field, or equivalent work experience, preferred Technical support and enhancements for GenAI pipelines with RAG Assist with prompt engineering to improve performance Monitor system performance, logs, retrieval quality and prompt-effectiveness Provide on-call support during incidents What is expected of you and others at this level Applies working knowledge in the application of concepts, principles and technical capabilities to perform varied tasks Works on projects of moderate scope and complexity Identifies possible solutions to a variety of technical problems and takes action to resolve. Apply judgment within defined parameters Receives general guidance and may receive more detailed instruction on new projects Work reviewed for sound reasoning and accuracy

3 - 5 years of analytics experience in Retail/CPG industry covering at least 2 of the below mentioned areas: Customer (insights/trends) Campaigns/CRM Loyalty Marketing To define, develop & support analytical solutions, along with extracting insights from data for improving business decisions of various retail functions (Ex. Marketing, Merchandising, Retail etc.) The recruit will be directly working with the on-shore Analytics team and with key business stakeholders of retail functions in each business unit to understand their business problems around merchandising and help deliver data-driven decision making. Analyze data o evaluate existing decisions framework and apply analytical techniques to discover meaningful patterns. Develop and support sophisticated & innovative analytical solutions that generate actionable insights by utilizing diverse information. Provide high-end consulting to functional teams to help them sharpen their business strategy. Keep abreast of industry trends and emerging methodologies to continuously improve skill set. Contribute to knowledge sharing and improve team productivity through training/documentation of best practices. Exposure to Azure Databricks (Good to have) Experience in Power BI (Good to have) Desired Skills and Experience: Bachelors or masters degree in any quantitative discipline (B.Tech/M.Tech in Computer Science/IT preferred) Candidates from Economics, Statistics/Data Science or Operations Research background from reputable institutions would also be preferred Ability to handle large datasets and expertise in analytical tools such as SAS, SQL, R, Python, Spark etc. Expertise in analytical techniques such as Linear Regression, Logistic Regression, Cluster analysis, Market Basket Analysis, Product Bundling, Cross/Upsell Analysis etc. Strong MS office skills and data visualization competence Excellent verbal and written presentation skills Should be able to articulate thoughts and ideas properly (structured approach should be there for problem solving) Attention to detail and ability to work in high pressure environment. Strong Drive and passion to deliver business impact through retail analytics. Strong business acumen and ability to translate data insights into meaningful business recommendations. Open to Travel (up to 20%) on need basis

Position: Data Science Trainer Salary : As per company standards Experience : 1yr- 5yrs WORK FROM OFFICE MANDATORY (Full time, permanent) Notice Period : immediate Location :Shivaji Nagar, Chinchwad Job Description : Candidates must have the ability to take both theory and practical sessions. Should have excellent knowledge on Python Data Science technologies. Should be able to teach Machine learning, deep learning, artificial Intelligence, SQL, Django Able to resolve students' queries. We expect good communication and presentation skills. Able to explain complex subjects in a clear and interesting way. Dynamic personality. Should be flexible to conduct Weekend Batches as well as Weekday Batches. Responsibilities and Duties - Devise technical training programs according to organizational requirements. Produce training schedules and classroom agenda. Determine course content according to objectives. Prepare training material (presentations, worksheets etc.) Execute training sessions Keep and report data on completed courses, absences, issues etc. Observe and evaluate results of training programs. Determine overall effectiveness of programs and make improvements. (Note: No part time , No work from home) Interested candidates can drop their CV on gkhandale@sevenmentor.com OR Contact on 7387385189

Project Role : Responsible AI Engineer Project Role Description : Assess AI systems for adherence to predefined thresholds and benchmarks related to responsible, ethical and sustainable practices. Design and implement technology mitigation strategies for systems to ensure ethical and responsible standards are achieved. Must have skills : Responsible AI Good to have skills : NAMinimum 15 year(s) of experience is required Educational Qualification : 15 years full time education Summary :As a Responsible AI Engineer, you will assess AI systems for adherence to predefined thresholds and benchmarks related to responsible, ethical, and sustainable practices. Design and implement technology mitigation strategies for systems to ensure ethical and responsible standards are achieved. Roles & Responsibilities:- Expected to be a SME with deep knowledge and experience.- Should have Influencing and Advisory skills.- Responsible for team decisions.- Engage with multiple teams and contribute on key decisions.- Expected to provide solutions to problems that apply across multiple teams.- Develop and implement responsible AI frameworks.- Conduct audits and assessments of AI systems for ethical compliance.- Collaborate with cross-functional teams to ensure responsible AI practices are integrated. Professional & Technical Skills: - Must To Have Skills: Proficiency in Responsible AI.- Strong understanding of statistical analysis and machine learning algorithms.- Experience with data visualization tools such as Tableau or Power BI.- Hands-on implementing various machine learning algorithms such as linear regression, logistic regression, decision trees, and clustering algorithms.- Solid grasp of data munging techniques, including data cleaning, transformation, and normalization to ensure data quality and integrity. Additional Information:- The candidate should have a minimum of 15 years of experience in Responsible AI.- This position is based at our Bengaluru office.- A 15 years full-time education is required. Qualification 15 years full time education

Management Level :07- I&F Decision Sci Practitioner Manager Location :Mumbai Must-have skills :Risk Analytics, Model Development, Validation, and Auditing, Performance Evaluation, Monitoring, Governance, Statistical Techniques:Linear Regression, Logistic Regression, GLM, GBM, XGBoost, CatBoost, Neural Networks, Programming Languages:SAS, R, Python, Spark, Scala, Tools:Tableau, QlikView, PowerBI, SAS VA, Regulatory Knowledge:Basel/CCAR/DFAST/CECL/IFRS9, Risk Reporting and Dashboard Solutions Good to have skills :Advanced Data Science Techniques, AML, Operational Risk Modelling, Cloud Platform Experience (AWS/Azure/GCP), Machine Learning Interpretability and Bias Algorithms Job Summary We are seeking a highly skilled I&F Decision Sci Practitioner Manager to join the Accenture Strategy & Consulting team in the Global Network Data & AI practice. You will be responsible for leading risk model development, validation, and auditing activities, ensuring performance evaluation, monitoring, governance, and documentation. This role also provides opportunities to work with top financial clients globally, utilizing cutting-edge technologies to drive business capabilities and foster innovation. Roles & Responsibilities: Engagement Execution Lead the team in the development, validation, governance, strategy, transformation, implementation, and end-to-end delivery of risk solutions for clients. Manage workstreams for large and small projects, overseeing the quality of deliverables for junior team members. Develop and frame Proof of Concept for key clients where applicable. Practice Enablement Mentor, guide, and counsel analysts and consultants. Support the development of the practice by driving innovations and initiatives. Support efforts of sales team to identify and win potential opportunities by assisting with RFPs, RFI. Assist in designing POVs, GTM collateral. Professional & Technical Skills: 7-12 years of relevant Risk Analytics experience at one or more Financial Services firms or Professional Services / Risk Advisory with significant exposure to Credit Risk :PD/LGD/EAD Models, CCAR/DFAST Loss Forecasting, Revenue Forecasting Models, IFRS9/CECL Loss Forecasting across Retail and Commercial portfolios. Credit Acquisition/Behavior :Modeling, Credit Policies, Limit Management, Acquisition Frauds, Collections Agent Matching/Channel Allocations across Retail and Commercial portfolios. Regulatory Capital and Economic Capital Models Liquidity Risk :Liquidity Models, Stress Testing Models, Basel Liquidity Reporting Standards Anti-Money Laundering (AML) :AML Scenarios/Alerts, Network Analysis Operational Risk :AMA Modeling, Operational Risk Reporting Modeling Techniques :Linear Regression, Logistic Regression, GLM, GBM, XGBoost, CatBoost, Neural Networks, Time Series (ARMA/ARIMA), ML Interpretability and Bias Algorithms Programming Languages & Tools :SAS, R, Python, Spark, Scala, Tableau, QlikView, PowerBI, SAS VA Strong understanding of Risk functions and their application in client discussions and project implementation. Additional Information: Masters Degree in a quantitative discipline (mathematics, statistics, economics, financial engineering, operations research) or MBA from top-tier universities Industry Certifications :FRM, PRM, CFA preferred Excellent Communication and Interpersonal Skills About Our Company | Accenture Qualification Experience :Minimum 7-12 years of relevant Risk Analytics experience, Exposure to Financial Services firms or Professional Services/Risk Advisory Educational Qualification :Masters degree in a quantitative discipline (mathematics, statistics, economics, financial engineering, operations research) or MBA from top-tier universities, Industry certifications such as FRM, PRM, CFA preferred

Python RWe are seeking a skilled Data Scientist proficient in Python and R to join our team The ideal candidate will have extensive experience developing machine learning and statistical models for regression, classification, and time series problems Additionally, they will have a strong understanding of software engineering principles and the ability to write clear, well structured, and testable code Key Responsibilities: Develop machine learning and statistical models for various business needs, including regression, classification, and time series analysis Implement models using Python and relevant libraries such as scikit learn, pandas, and numpy Apply machine learning techniques such as Linear Regression, Random Forest, Classification, and Ensemble methods Convert R code to Python and ensure seamless integration between the two languages Utilize R for data manipulation and analysis using tidyverse, dplyr, and data table Optimize and enhance existing R code for performance and scalability Collaborate with cross functional teams to understand business requirements and deliver data driven solutions Follow best practices in software engineering to produce clean, manageable, and testable code Stay updated with the latest industry trends and advancements in data science and machine learning Required Skills and Qualifications: Bachelor s or Master s degree in Computer Science, Statistics, Data Science, or a related field 6+ years of IT experience with a min of 3+ years in Data Science (AI/ML) Proven experience as a Data Scientist or similar role with hands on experience in Python and R Strong knowledge of machine learning algorithms and statistical modeling techniques Proficiency in Python libraries such as scikit learn, pandas, numpy, and matplotlib Expertise in R programming, particularly with tidyverse, dplyr, tidymodels, and data table Experience with relational databases and SQL Ability to convert R code to Python efficiently Familiarity with software engineering principles and best practices Strong problem solving skills and attention to detail Excellent communication and collaboration skills Ability to manage multiple projects and meet deadlines

Salary : 30 to 45 LPA Exp: 6 to 10 years Location :Hyderabad (Hybrid) Notice: Immediate to 30 days..!! Roles & responsibilities: 5+ years exp on Python , ML and Banking model development Interact with the client to understand their requirements and communicate / brainstorm solutions, model Development: Design, build, and implement credit risk model. Contribute to how analytical approach is structured for specification of analysis Contribute insights from conclusions of analysis that integrate with initial hypothesis and business objective. Independently address complex problems 5+ years exp on ML/Python (predictive modelling) . Design, implement, test, deploy and maintain innovative data and machine learning solutions to accelerate our business. Create experiments and prototype implementations of new learning algorithms and prediction techniques Collaborate with product managers, and stockholders to design and implement software solutions for science problems Use machine learning best practices to ensure a high standard of quality for all of the team deliverables Has experience working on unstructured data ( text ): Text cleaning, TFIDF, text vectorization Hands-on experience with IFRS 9 models and regulations. Data Analysis: Analyze large datasets to identify trends and risk factors, ensuring data quality and integrity. Statistical Analysis: Utilize advanced statistical methods to build robust models, leveraging expertise in R programming. Collaboration: Work closely with data scientists, business analysts, and other stakeholders to align models with business needs. Continuous Improvement: Stay updated with the latest methodologies and tools in credit risk modeling and R programming.

Salary : 20 to 35 LPA Exp: 3 to 8 years Location :/Gurugram/Bangalore/Hyderabad Notice: Immediate to 30 days..!! Roles & responsibilities: 3+ years exp on Python , ML and Banking model development Interact with the client to understand their requirements and communicate / brainstorm solutions, model Development: Design, build, and implement credit risk model. Contribute to how analytical approach is structured for specification of analysis Contribute insights from conclusions of analysis that integrate with initial hypothesis and business objective. Independently address complex problems 3+ years exp on ML/Python (predictive modelling) . Design, implement, test, deploy and maintain innovative data and machine learning solutions to accelerate our business. Create experiments and prototype implementations of new learning algorithms and prediction techniques Collaborate with product managers, and stockholders to design and implement software solutions for science problems Use machine learning best practices to ensure a high standard of quality for all of the team deliverables Has experience working on unstructured data ( text ): Text cleaning, TFIDF, text vectorization Hands-on experience with IFRS 9 models and regulations. Data Analysis: Analyze large datasets to identify trends and risk factors, ensuring data quality and integrity. Statistical Analysis: Utilize advanced statistical methods to build robust models, leveraging expertise in R programming. Collaboration: Work closely with data scientists, business analysts, and other stakeholders to align models with business needs. Continuous Improvement: Stay updated with the latest methodologies and tools in credit risk modeling and R programming.

About the role: This is a unique opportunity to join our fast-growing Data Science team. In the role of Data Scientist, you will execute large scale, high impact data modeling projects with responsibility for designing, developing, validating, socializing, operationalizing, and maintaining data-driven analytics that provide business insights to increase operational efficiency and customer value. What you will do: Deliver modeling and analytical insights to inform strategic and operational initiatives Conduct all phases of the model development process. Including: Understanding business issues, proposing technical solutions, data wrangling, data cleaning, data analysis, feature engineering, model selection, model development, model validation, model operationalization, presentation of results and insights, model implementation, model documentation Convert top-down business initiative requirements into actionable data analytics projects as well as conceiving and proposing a bottom-up analytics innovations Communicate technical solutions and results to business stakeholders Partner with business stakeholders, IT and lead the design and delivery ML solutions Inject the most applicable technology, including Machine Learning, Artificial Intelligence, Natural Language Processing and Statistical Modeling Continuously innovate with state of art techniques to improve the model What you will need: For Data Scientist 3-6 years & for Associate Data Scientist 1-3 years of experience in solving real life business problems using ML & Data Science Bachelor's degree is required. Master's degree preferred. Technical degrees with a concentration in statistics, data science, computer science or related field preferred In-depth knowledge of statistical methods & principles and its usage in the model building & data analysis Experience in applying descriptive, predictive, prescriptive models & data visualization to solve real life business problems Understanding of NLP concepts and its application is preferred Expertise in Python, SQL, Spark Experience with multiple modeling techniques such as: Time Series, Random Forests, Clustering, Neural Networks, Generalized Linear Models, Optimization, DOE, Dimensionality Reduction MLOps experience is preferred (implementing models/algorithms into production systems) Ability to work in a fast-paced environment and deliver against milestones Excellent communication skills in technical and business domains Proven ability to influence key stakeholders and leaders What you will get: Competitive salary, generous paid time off policy, charity match program, Group Medical Insurance, Parental Leave, Employee Assistance Program (EAP) and more! Collaborative, team-oriented culture that embraces diversity Professional development and unlimited growth opportunities