92 Regression Analysis Jobs - Page 4

Sanas is revolutionizing the way we communicate with the world s first real-time algorithm, designed to modulate accents, eliminate background noises, and magnify speech clarity. Pioneered by seasoned startup founders with a proven track record of creating and steering multiple unicorn companies, our groundbreaking GDP-shifting technology sets a gold standard. Sanas is a 200-strong team, established in 2020. In this short span, we ve successfully secured over $100 million in funding. Our innovation have been supported by the industry s leading investors, including Insight Partners, Google Ventures, Quadrille Capital, General Catalyst, Quiet Capital, and other influential investors. Our reputation is further solidified by collaborations with numerous Fortune 100 companies. With Sanas, you re not just adopting a product; you re investing in the future of communication. This position requires a deep understanding of machine learning model behavior, strong attention to detail, and a passion for building high-quality AI systems. We are seeking a Model QA Engineer with hands-on experience in evaluating real-time speech and language models. In this role, you ll act as the first line of defense for ensuring the performance, stability, and reliability of our deployed AI systems. You ll work closely with Machine Learning Researchers, Data Analysts, and Product Managers to detect regressions, surface edge cases, and deliver actionable insights that help shape future models. Key Responsibilities: Conduct end-to-end evaluation of ML models through structured listening tests, regression analysis, and failure case identification Analyze customer call recordings to replicate issues and validate model behavior across different environments and configurations Participate in internal dogfooding, model AB testing, and cross-version comparisons with clear documentation of findings Collaborate with research teams to debug, interpret and report model output anomalies Curate diverse, representative datasets for recurring QA evaluations and benchmarks Maintain quality and consistency in evaluation documentation, ensuring traceability and reproducibility of results Track ongoing model performance and provide timely reports highlighting areas of improvement or risk Assist in QA automation efforts to streamline model evaluation workflows over time Must have qualifications: 2+ years of experience in a QA, Model QA, Speech Evaluation, or ML testing role Familiarity with speech/audio quality concepts (e.g., fidelity, intelligibility, latency, robustness) Experience working with audio listening tools (Audacity, Praat) and evaluation metrics (PESQ, STOI, MOS etc.) Excellent communication skills and the ability to write structured, actionable feedback for technical teams Proven ability to identify subtle performance issues in AI model outputs Comfortable working with large datasets (CSV, JSON) and using tools like Excel, Google Sheets or Python for analysis Highly detail-oriented with a proactive and investigative mindset Preferred qualifications: Background in linguistics, phonetics, audio engineering, or speech science Experience working in cross-functional ML product teams Exposure to ASR, TTS, or real-time audio systemsFamiliarity with tools like Git, Jira, Notion, or Confluence Understanding of ML model deployment cycles and CI/CD pipelines Prior experience with annotation platforms or feedback loop systems for ML models Joining us means contributing to the world s first real-time speech understanding platform revolutionizing Contact Centers and Enterprises alike. Our technology empowers agents, transforms customer experiences, and drives measurable growth. But this is just the beginning. Youll be part of a team exploring the vast potential of an increasingly sonic future

Description As a Business Analysis Associate I within the Operations Performance Management team, you will play a pivotal role in generating analytical insights that significantly influence the financial performance of the Collections organization across Card, Overdraft, and Auto lines of business. You will develop comprehensive data expertise to support cross-line performance monitoring and analysis, forge strong partnerships with key stakeholders, and utilize your understanding of data to craft compelling business narratives that drive decisions and strategic direction. Job Responsibilities Support daily operations and tasks related to specific functional areas or business partners. Create business review decks, weekly updates, and ad-hoc communications for presentation to senior leaders and team members. Ensure projects are completed within established timelines. Participate in cross-functional teams to drive initiatives. Assemble data, build reports/dashboards, and provide innovative solutions for business partners. Identify risks and opportunities, proposing solutions to unlock value. Required Qualifications, Capabilities, and Skills Over 5 years of professional experience in business and relevant MIS/Technology roles. Strong understanding of business operations and procedures, with the ability to connect them to business fundamentals. Proficiency in sourcing data from multiple locations, integrating them, and providing actionable information for reporting or analysis. Eagerness to learn and adapt to new technologies. Open-mindedness to diverse perspectives. Ability to anticipate and resolve customer and general issues with urgency. Expertise in using advanced statistical tools, such as regression analysis and interpreting correlation coefficients. Ability to interpret business trends, propose solutions to improve them, and identify gaps with recommendations. Knowledge to incorporate other business areas in analysis and solutions, such as inventory, strategy, and contact management. Experience in reporting and data analysis development, with the ability to meet strict deadlines. Strong proficiency in SAS, Alteryx, SQL, and advanced Excel. Preferred Qualifications, Capabilities, and Skills Prior experience in Collections Operations is preferred. Bachelors degree or equivalent is required.

Our Data Analysts use data to build the best customer experiences and love helping to make better business decisions, by using diverse sets of data. We re looking for brilliant minds who find meaning in structured and unstructured data, with business domain expertise to translate commercial goals into data-based deliverables to solve the world s most complex challenges. About our Digital Channels Data Analytics (DCDA) team They support our corporate clients, by creating a more equitable, sustainable, and prosperous future for clients and global communities through technology, data and digital. They re responsible for being an expert in digital products and services and partner with our sales and coverage teams. About Corporate Investment Banking (CIB) For more than 170 years we ve support clients with their transaction banking, financial markets, corporate finance and borrowing needs and provide solutions to nearly 20, 000 clients in the world s fastest-growing economies and most active trade corridors. Key Responsibilities Data analysis and visualisation including: Support the development and execution of our data analytics strategy and roadmap. Develop and deploy analytical models to produce analytical solutions and provide insights that support business decisions, including coalition data viewer and expand data viewer. Translate business challenges into statistical problems and data analysis. Use data analysis techniques including trend analysis, regression analysis and the Monte Carlo simulation. Use analytical tools including Azure, Python and SQL to analyse datasets to gain key actionable insights to resolve business problems. Present key findings, insights and business recommendations to stakeholders using data storyboarding and visualisation techniques. Promote analytics-driven decision-making processes across our business to drive awareness of data led decision making and business opportunities. Build and automate data visualisation dashboards using tools such as Tableau and Power BI to enable stakeholder self-service. Partner with stakeholders to identify and optimise analytical tools including Dataiku, Python and Azure. Skills and Experience Statistical analysis. Agile project management. Big data management and analytics. Data monetisation. Financial mathematics. Business acumen entry. Emerging technologies. Client experience, behaviours and preferences. Financial services regulatory experience. Data governance and management. About Standard Chartered Were an international bank, nimble enough to act, big enough for impact. For more than 170 years, weve worked to make a positive difference for our clients, communities, and each other. We question the status quo, love a challenge and enjoy finding new opportunities to grow and do better than before. If youre looking for a career with purpose and you want to work for a bank making a difference, we want to hear from you. You can count on us to celebrate your unique talents and we cant wait to see the talents you can bring us. Our purpose, to drive commerce and prosperity through our unique diversity, together with our brand promise, to be here for good are achieved by how we each live our valued behaviours. When you work with us, youll see how we value difference and advocate inclusion. Together we: Do the right thing and are assertive, challenge one another, and live with integrity, while putting the client at the heart of what we do Never settle, continuously striving to improve and innovate, keeping things simple and learning from doing well, and not so well Are better together, we can be ourselves, be inclusive, see more good in others, and work collectively to build for the long term What we offer In line with our Fair Pay Charter, we offer a competitive salary and benefits to support your mental, physical, financial and social wellbeing. Core bank funding for retirement savings, medical and life insurance, with flexible and voluntary benefits available in some locations. Time-off including annual leave, parental/maternity (20 weeks), sabbatical (12 months maximum) and volunteering leave (3 days), along with minimum global standards for annual and public holiday, which is combined to 30 days minimum. Flexible working options based around home and office locations, with flexible working patterns. Proactive wellbeing support through Unmind, a market-leading digital wellbeing platform, development courses for resilience and other human skills, global Employee Assistance Programme, sick leave, mental health first-aiders and all sorts of self-help toolkits A continuous learning culture to support your growth, with opportunities to reskill and upskill and access to physical, virtual and digital learning. Being part of an inclusive and values driven organisation, one that embraces and celebrates our unique diversity, across our teams, business functions and geographies - everyone feels respected and can realise their full potential. Recruitment Assessments Some of our roles use assessments to help us understand how suitable you are for the role youve applied to. If you are invited to take an assessment, this is great news. It means your application has progressed to an important stage of our recruitment process. Visit our careers website www. sc. com/careers www. sc. com/careers 26932

Designation:- Test Engineer Experience Range :- 1-3 Years Must have Primary Skill :- Life Insurance , test case planning and execution , regression analysis , defect testing , bug fixing and good English communication skills. Only candidates from Hyderabad are required. Job Description:- 1. 1-3years of work experience in Life insurance and Life Asia. 2.Ensure successful test case execution maintaining the organizations quality standards. 3.Maintain workplace discipline and adhere to organization standards. 4.Execute the test cases as per test plan. 5.Record defects in Defect Management Tool. 6. Retesting of defects fixed.

We are seeking an experienced Advanced Analytics Manager to join our dynamic team. This role focuses on leveraging advanced analytics techniques, including machine learning algorithms, Generative AI (GenAI), and large language models (LLMs), to drive data-driven decision-making within the retail/CPG domain. The ideal candidate will possess a strong quantitative background, a passion for transforming complex data into actionable insights, an extensive experience into leading mid-to-large sized teams, and the ability to create, assess and implement RFPs, POCs, approaches and framework Job Description: Key Responsibilities: Develop, implement, and maintain advanced analytical models using machine learning algorithms and GenAI applications Utilize various advanced analytics techniques to uncover trends, patterns, and insights from large and complex datasets. Collaborate with cross-functional teams to identify business needs and deliver data-driven solutions. Create visually compelling dashboards and reports to present findings to stakeholders. Continuously evaluate and improve existing analytics methodologies and models to enhance accuracy and performance. Stay abreast of industry trends and advancements in analytics and machine learning to drive innovation within the team. Mentor junior team members and contribute to knowledge sharing within the organization. Basic Qualifications: Bachelor s or Master s degree in Data Science, Business Analytics, Mathematics, Statistics, or a related field. 8+ years of experience in advanced analytics, data science, machine learning, Generative AI or a related field. Strong experience with quantitative modeling, predictive analytics, text analytics, and forecasting methodologies Proficiency in SQL (or Google BigQuery), Python, visualization tools like Tableau/PowerBI Familiarity with the Retail/CPG/Tech industry and experience with product, transaction, and customer-level data. Excellent communication skills, both verbal and written, with the ability to convey complex concepts to non-technical stakeholders. Strong analytical and problem-solving skills, with an inquisitive mindset. Desired Skills: Proficient in the following advanced analytics techniques: Descriptive Analytics: Statistical analysis, data visualization. Predictive Analytics: Regression analysis, time series forecasting, classification techniques, market mix modeling Prescriptive Analytics: Optimization, simulation modeling. Text Analytics: Natural Language Processing (NLP), sentiment analysis. Extensive knowledge of machine learning techniques, including: Supervised Learning: Linear regression, logistic regression, decision trees, support vector machines, random forests, gradient boosting machines among others Unsupervised Learning: K-means clustering, hierarchical clustering, principal component analysis (PCA), anomaly detection among others Reinforcement Learning: Q-learning, deep Q-networks, etc. Experience with Generative AI and large language models (LLMs) for text generation, summarization, and conversational agents. Researching, loading and application of the best LLMs (GPT, Gemini, LLAMA, etc.) for various objectives Hyper parameter tuning Prompt Engineering Embedding & Vectorization Fine tuning Proficiency in data visualization tools such as Tableau or Power BI. Strong skills in data management, structuring, and harmonization to support analytical needs. What We Offer: Opportunities for professional development and career growth. A collaborative and innovative work environment. If you are passionate about data analytics and want to make a significant impact in the retail/CPG industry, we encourage you to apply! Location: Bengaluru Brand: Merkle Time Type: Full time Contract Type: Permanent

We are seeking an experienced Advanced Analytics Manager to join our dynamic team. This role focuses on leveraging advanced analytics techniques, including machine learning algorithms, Generative AI (GenAI), and large language models (LLMs), to drive data-driven decision-making within the retail/CPG domain. The ideal candidate will possess a strong quantitative background, a passion for transforming complex data into actionable insights, an extensive experience into leading mid-to-large sized teams, and the ability to create, assess and implement RFPs, POCs, approaches and framework Job Description: Key Responsibilities: Develop, implement, and maintain advanced analytical models using machine learning algorithms and GenAI applications Utilize various advanced analytics techniques to uncover trends, patterns, and insights from large and complex datasets. Collaborate with cross-functional teams to identify business needs and deliver data-driven solutions. Create visually compelling dashboards and reports to present findings to stakeholders. Continuously evaluate and improve existing analytics methodologies and models to enhance accuracy and performance. Stay abreast of industry trends and advancements in analytics and machine learning to drive innovation within the team. Mentor junior team members and contribute to knowledge sharing within the organization. Basic Qualifications: Bachelor s or Master s degree in Data Science, Business Analytics, Mathematics, Statistics, or a related field. 8+ years of experience in advanced analytics, data science, machine learning, Generative AI or a related field. Strong experience with quantitative modeling, predictive analytics, text analytics, and forecasting methodologies Proficiency in SQL (or Google BigQuery), Python, visualization tools like Tableau/PowerBI Familiarity with the Retail/CPG/Tech industry and experience with product, transaction, and customer-level data. Excellent communication skills, both verbal and written, with the ability to convey complex concepts to non-technical stakeholders. Strong analytical and problem-solving skills, with an inquisitive mindset. Desired Skills: Proficient in the following advanced analytics techniques: Descriptive Analytics: Statistical analysis, data visualization. Predictive Analytics: Regression analysis, time series forecasting, classification techniques, market mix modeling Prescriptive Analytics: Optimization, simulation modeling. Text Analytics: Natural Language Processing (NLP), sentiment analysis. Extensive knowledge of machine learning techniques, including: Supervised Learning: Linear regression, logistic regression, decision trees, support vector machines, random forests, gradient boosting machines among others Unsupervised Learning: K-means clustering, hierarchical clustering, principal component analysis (PCA), anomaly detection among others Reinforcement Learning: Q-learning, deep Q-networks, etc. Experience with Generative AI and large language models (LLMs) for text generation, summarization, and conversational agents. Researching, loading and application of the best LLMs (GPT, Gemini, LLAMA, etc.) for various objectives Hyper parameter tuning Prompt Engineering Embedding & Vectorization Fine tuning Proficiency in data visualization tools such as Tableau or Power BI. Strong skills in data management, structuring, and harmonization to support analytical needs. What We Offer: Opportunities for professional development and career growth. A collaborative and innovative work environment. If you are passionate about data analytics and want to make a significant impact in the retail/CPG industry, we encourage you to apply! Location: Bengaluru Brand: Merkle Time Type: Full time Contract Type: Permanent

We are seeking an experienced Advanced Analytics Manager to join our dynamic team. This role focuses on leveraging advanced analytics techniques, including machine learning algorithms, Generative AI (GenAI), and large language models (LLMs), to drive data-driven decision-making within the retail/CPG domain. The ideal candidate will possess a strong quantitative background, a passion for transforming complex data into actionable insights, an extensive experience into leading mid-to-large sized teams, and the ability to create, assess and implement RFPs, POCs, approaches and framework Job Description: Key Responsibilities: Develop, implement, and maintain advanced analytical models using machine learning algorithms and GenAI applications Utilize various advanced analytics techniques to uncover trends, patterns, and insights from large and complex datasets. Collaborate with cross-functional teams to identify business needs and deliver data-driven solutions. Create visually compelling dashboards and reports to present findings to stakeholders. Continuously evaluate and improve existing analytics methodologies and models to enhance accuracy and performance. Stay abreast of industry trends and advancements in analytics and machine learning to drive innovation within the team. Mentor junior team members and contribute to knowledge sharing within the organization. Basic Qualifications: Bachelor s or Master s degree in Data Science, Business Analytics, Mathematics, Statistics, or a related field. 8+ years of experience in advanced analytics, data science, machine learning, Generative AI or a related field. Strong experience with quantitative modeling, predictive analytics, text analytics, and forecasting methodologies Proficiency in SQL (or Google BigQuery), Python, visualization tools like Tableau/PowerBI Familiarity with the Retail/CPG/Tech industry and experience with product, transaction, and customer-level data. Excellent communication skills, both verbal and written, with the ability to convey complex concepts to non-technical stakeholders. Strong analytical and problem-solving skills, with an inquisitive mindset. Desired Skills: Proficient in the following advanced analytics techniques: Descriptive Analytics: Statistical analysis, data visualization. Predictive Analytics: Regression analysis, time series forecasting, classification techniques, market mix modeling Prescriptive Analytics: Optimization, simulation modeling. Text Analytics: Natural Language Processing (NLP), sentiment analysis. Extensive knowledge of machine learning techniques, including: Supervised Learning: Linear regression, logistic regression, decision trees, support vector machines, random forests, gradient boosting machines among others Unsupervised Learning: K-means clustering, hierarchical clustering, principal component analysis (PCA), anomaly detection among others Reinforcement Learning: Q-learning, deep Q-networks, etc. Experience with Generative AI and large language models (LLMs) for text generation, summarization, and conversational agents. Researching, loading and application of the best LLMs (GPT, Gemini, LLAMA, etc.) for various objectives Hyper parameter tuning Prompt Engineering Embedding Vectorization Fine tuning Proficiency in data visualization tools such as Tableau or Power BI. Strong skills in data management, structuring, and harmonization to support analytical needs. What We Offer: Opportunities for professional development and career growth. A collaborative and innovative work environment. If you are passionate about data analytics and want to make a significant impact in the retail/CPG industry, we encourage you to apply! Location: Bengaluru Brand: Merkle Time Type: Full time Contract Type: Permanent

About the Role The Data Science department plays a pivotal role in our company, generating value to client by developing algorithms and analytical production-grade solutions. We leverage advanced techniques and algorithms to provide maximum value from data in all shapes and sizes (such as classification models, NLP, anomaly detection, graph theory, deep learning, and more). As a Data Scientist, you will assume the classic data-science role of an end-to-end project development and implementation practitioner. Being part of the team requires a mix of hard quantitative and analytical skills, solid background in statistical modeling and machine learning, a technical data-savvy nature, along with a passion for problem-solving and a desire to drive data-driven decision-making. What Youll Be Doing Data Exploration and Preprocessing: Collect, clean, and transform large, complex data sets from various sources to ensure data quality and integrity for analysis Statistical Analysis and Modeling: Apply statistical methods and mathematical models to identify patterns, trends, and relationships in data sets, and develop predictive models Machine Learning: Develop and implement machine learning algorithms, such as classification, regression, clustering, and deep learning, to solve business problems and improve processes Feature Engineering: Extract relevant features from structured and unstructured data sources, and design and engineer new features to enhance model performance Model Development and Evaluation: Build, train, and optimize machine learning models using state-of-the-art techniques, and evaluate model performance using appropriate metrics Data Visualization: Present complex analysis results in a clear and concise manner using data visualization techniques, and communicate insights to stakeholders effectively Collaborative Problem-Solving: Collaborate with cross-functional teams, including product managers, data engineers, software developers, and business stakeholders to identify data-driven solutions and implement them in production environments Research and Innovation: Stay up to date with the latest advancements in data science, machine learning, and related fields, and proactively explore new approaches to enhance the companys analytical capabilities Qualifications B.Sc (M.Sc is a plus) in Computer Science, Mathematics, Statistics, or a related field 3+ years of proven experience designing and implementing machine learning algorithms and successfully deploying them to production. Strong understanding and practical experience with various machine learning algorithms. Proficiency in Python, Experience with SQL and data manipulation tools (e.g., Pandas, NumPy) to extract, clean, and transform data for analysis Solid foundation in statistical concepts and techniques, including hypothesis testing, regression analysis, time series analysis, and experimental design Strong analytical and critical thinking skills to approach business problems, formulate hypotheses, and translate them into actionable solutions Proficiency in data visualization libraries, to create meaningful visual representations of complex data Excellent written and verbal communication skills to present complex findings and technical concepts to both technical and non-technical stakeholders Demonstrated ability to work effectively in cross-functional teams, collaborate with colleagues, and contribute to a positive work environment Advantages: Experience in the fraud domain Experience with Airflow, CircleCI, PySpark, Docker and K8S Senior Data Scientist About the Role The Data Science department plays a pivotal role in our company, generating value to client by developing algorithms and analytical production-grade solutions. We leverage advanced techniques and algorithms to provide maximum value from data in all shapes and sizes (such as classification models, NLP, anomaly detection, graph theory, deep learning, and more). As a Data Scientist, you will assume the classic data-science role of an end-to-end project development and implementation practitioner. Being part of the team requires a mix of hard quantitative and analytical skills, solid background in statistical modeling and machine learning, a technical data-savvy nature, along with a passion for problem-solving and a desire to drive data-driven decision-making. What Youll Be Doing Data Exploration and Preprocessing: Collect, clean, and transform large, complex data sets from various sources to ensure data quality and integrity for analysis Statistical Analysis and Modeling: Apply statistical methods and mathematical models to identify patterns, trends, and relationships in data sets, and develop predictive models Machine Learning: Develop and implement machine learning algorithms, such as classification, regression, clustering, and deep learning, to solve business problems and improve processes Feature Engineering: Extract relevant features from structured and unstructured data sources, and design and engineer new features to enhance model performance Model Development and Evaluation: Build, train, and optimize machine learning models using state-of-the-art techniques, and evaluate model performance using appropriate metrics Data Visualization: Present complex analysis results in a clear and concise manner using data visualization techniques, and communicate insights to stakeholders effectively Collaborative Problem-Solving: Collaborate with cross-functional teams, including product managers, data engineers, software developers, and business stakeholders to identify data-driven solutions and implement them in production environments Research and Innovation: Stay up to date with the latest advancements in data science, machine learning, and related fields, and proactively explore new approaches to enhance the companys analytical capabilities Qualifications B.Sc (M.Sc is a plus) in Computer Science, Mathematics, Statistics, or a related field 5+ years of proven experience designing and implementing machine learning algorithms and successfully deploying them to production. Strong understanding and practical experience with various machine learning algorithms. Proficiency in Python, Experience with SQL and data manipulation tools (e.g., Pandas, NumPy) to extract, clean, and transform data for analysis Solid foundation in statistical concepts and techniques, including hypothesis testing, regression analysis, time series analysis, and experimental design Strong analytical and critical thinking skills to approach business problems, formulate hypotheses, and translate them into actionable solutions Proficiency in data visualization libraries, to create meaningful visual representations of complex data Excellent written and verbal communication skills to present complex findings and technical concepts to both technical and non-technical stakeholders Demonstrated ability to work effectively in cross-functional teams, collaborate with colleagues, and contribute to a positive work environment Advantages: Experience in the fraud domain Experience with Airflow, CircleCI, PySpark, Docker and K8S Data Scientist- Autonomous About Us Empowers businesses to unleash ecommerce growth by taking risk off the table. Many of the world s biggest brands and publicly traded companies selling online rely on us for guaranteed protection against chargebacks, to fight fraud and policy abuse at scale, and to improve customer retention. Developed and managed by the largest team of ecommerce risk analysts, data scientists and researchers, AI-powered fraud and risk intelligence platform analyzes the individual behind each interaction to provide real-time decisions and robust identity-based insights. We are proud to work with incredible companies in virtually all industries including Wayfair, Acer, Gucci, Lorna Jane, GoPro, and many more We thrive in a collaborative work setting, alongside great people, to build and enhance products that matter. Abundant opportunities to create and contribute provide us with a sense of purpose that extends beyond ourselves, leaving a lasting impact. These sentiments capture why we choose every day. About the Role The Research and Data Science department plays a pivotal role in our company, generating value to client by developing algorithms and analytical production-grade solutions. We leverage advanced techniques and algorithms to provide maximum value from data in all shapes and sizes (such as classification models, NLP, anomaly detection, graph theory, deep learning, and more). As a Data Scientist, you will assume the classic data-science role of an end-to-end project development and implementation practitioner. Being part of the team requires a mix of hard quantitative and analytical skills, solid background in statistical modeling and machine learning, a technical data-savvy nature, along with a passion for problem-solving and a desire to drive data-driven decision-making. What Youll Be Doing Data Exploration and Preprocessing: Collect, clean, and transform large, complex data sets from various sources to ensure data quality and integrity for analysis Statistical Analysis and Modeling: Apply statistical methods and mathematical models to identify patterns, trends, and relationships in data sets, and develop predictive models Machine Learning: Develop and implement machine learning algorithms, such as classification, regression, clustering, and deep learning, to solve business problems and improve processes Feature Engineering: Extract relevant features from structured and unstructured data sources, and design and engineer new features to enhance model performance Model Development and Evaluation: Build, train, and optimize machine learning models using state-of-the-art techniques, and evaluate model performance using appropriate metrics Data Visualization: Present complex analysis results in a clear and concise manner using data visualization techniques, and communicate insights to stakeholders effectively Collaborative Problem-Solving: Collaborate with cross-functional teams, including product managers, data engineers, software developers, and business stakeholders to identify data-driven solutions and implement them in production environments Research and Innovation: Stay up to date with the latest advancements in data science, machine learning, and related fields, and proactively explore new approaches to enhance the companys analytical capabilities Qualifications B.Sc (M.Sc is a plus) in Statistics, Computer Science, Mathematics, or a related field 3+ years of proven experience designing and implementing machine learning algorithms and techniques in production grade Strong understanding and practical experience with various machine learning algorithms, such as linear regression, logistic regression, decision trees, similarity search, neural networks, and deep learning Proficiency in programming languages such as Python or R for data manipulation, statistical analysis, and machine learning model development Experience with SQL and data manipulation tools (e.g., Pandas, NumPy) to extract, clean, and transform data for analysis Solid foundation in statistical concepts and techniques, including hypothesis testing, regression analysis, time series analysis, and experimental design Strong analytical and critical thinking skills to approach business problems, formulate hypotheses, and translate them into actionable solutions Proficient in data visualization libraries (e.g., Matplotlib, Seaborn, ggplot) to create meaningful visual representations of complex data Excellent written and verbal communication skills to present complex findings and technical concepts to both technical and non-technical stakeholders Demonstrated ability to work effectively in cross-functional teams, collaborate with colleagues, and contribute to a positive work environmentAdvantages: Experience in the fraud domain Experience with Airflow, CircleCI, PySpark, Docker and K8S EXPERIENCE 6-8 Years SKILLS Primary Skill: Data Science Sub Skill(s): Data Science Additional Skill(s): AI/ML Development, Data Science

Our Data Analysts use data to build the best customer experiences and love helping to make better business decisions, by using diverse sets of data. We re looking for brilliant minds who find meaning in structured and unstructured data, with business domain expertise to translate commercial goals into data-based deliverables to solve the world s most complex challenges. About our Digital Channels & Data Analytics (DCDA) team They support our corporate clients, by creating a more equitable, sustainable, and prosperous future for clients and global communities through technology, data and digital. They re responsible for being an expert in digital products and services and partner with our sales and coverage teams. About Corporate & Investment Banking (CIB) For more than 170 years we ve support clients with their transaction banking, financial markets, corporate finance and borrowing needs and provide solutions to nearly 20, 000 clients in the world s fastest-growing economies and most active trade corridors. Key Responsibilities Data analysis and visualisation including: Support the development and execution of our data analytics strategy and roadmap. Develop and deploy analytical models to produce analytical solutions and provide insights that support business decisions, including coalition data viewer and expand data viewer. Translate business challenges into statistical problems and data analysis. Use data analysis techniques including trend analysis, regression analysis and the Monte Carlo simulation. Use analytical tools including Azure, Python and SQL to analyse datasets to gain key actionable insights to resolve business problems. Present key findings, insights and business recommendations to stakeholders using data storyboarding and visualisation techniques. Promote analytics-driven decision-making processes across our business to drive awareness of data led decision making and business opportunities. Build and automate data visualisation dashboards using tools such as Tableau and Power BI to enable stakeholder self-service. Partner with stakeholders to identify and optimise analytical tools including Dataiku, Python and Azure. Skills and Experience Statistical analysis. Agile project management. Big data management and analytics. Data monetisation. Financial mathematics. Business acumen entry. Emerging technologies. Client experience, behaviours and preferences. Financial services regulatory experience. Data governance and management. About Standard Chartered Were an international bank, nimble enough to act, big enough for impact. For more than 170 years, weve worked to make a positive difference for our clients, communities, and each other. We question the status quo, love a challenge and enjoy finding new opportunities to grow and do better than before. If youre looking for a career with purpose and you want to work for a bank making a difference, we want to hear from you. You can count on us to celebrate your unique talents and we cant wait to see the talents you can bring us. Our purpose, to drive commerce and prosperity through our unique diversity, together with our brand promise, to be here for good are achieved by how we each live our valued behaviours. When you work with us, youll see how we value difference and advocate inclusion. Together we: Do the right thing and are assertive, challenge one another, and live with integrity, while putting the client at the heart of what we do Never settle, continuously striving to improve and innovate, keeping things simple and learning from doing well, and not so well Are better together, we can be ourselves, be inclusive, see more good in others, and work collectively to build for the long term What we offer In line with our Fair Pay Charter, we offer a competitive salary and benefits to support your mental, physical, financial and social wellbeing. Core bank funding for retirement savings, medical and life insurance, with flexible and voluntary benefits available in some locations. Time-off including annual leave, parental/maternity (20 weeks), sabbatical (12 months maximum) and volunteering leave (3 days), along with minimum global standards for annual and public holiday, which is combined to 30 days minimum. Flexible working options based around home and office locations, with flexible working patterns. Proactive wellbeing support through Unmind, a market-leading digital wellbeing platform, development courses for resilience and other human skills, global Employee Assistance Programme, sick leave, mental health first-aiders and all sorts of self-help toolkits A continuous learning culture to support your growth, with opportunities to reskill and upskill and access to physical, virtual and digital learning. Being part of an inclusive and values driven organisation, one that embraces and celebrates our unique diversity, across our teams, business functions and geographies - everyone feels respected and can realise their full potential. Recruitment Assessments Some of our roles use assessments to help us understand how suitable you are for the role youve applied to. If you are invited to take an assessment, this is great news. It means your application has progressed to an important stage of our recruitment process. Visit our careers website www. sc. com/careers www. sc. com/careers 26933

At Johnson & Johnson, we believe health is everything. Our strength in healthcare innovation empowers us to build a world where complex diseases are prevented, treated, and cured, where treatments are smarter and less invasive, and solutions are personal. Through our expertise in Innovative Medicine and MedTech, we are uniquely positioned to innovate across the full spectrum of healthcare solutions today to deliver the breakthroughs of tomorrow, and profoundly impact health for humanity. Learn more at Job Function: Market Access Job Sub Function: Pricing Job Category: Professional All Job Posting Locations: Mumbai, India, Pune, Maharashtra, India Job Description: Pricing Manager (Regional Strategic Pricing), Pune / Mumbai, India Johnson & Johnson MedTech APAC Strategic Insights, Analytics, & Pricing is recruiting for a Pricing Manager , APAC to be located in Pune, India reporting into regional head of Strategy, Insights, Analytics & Pricing (SIA&P). The SI&AP team drives alignment across business units, platforms, and clusters through regionally-lead, cross-functional collaboration and solid foundation in research, and data analytics. The members of the regional team work closely with the Customer, Market, Finance, and BU teams to build value-based business cases and drive a portfolio of strategic initiatives focused on near and long-term revenue growth opportunities driving Profitable Growth. Job Description: The manager will be responsible for integrating critical internal as well as external pricing analytics and reporting within the Regional strategic pricing team. The key responsibilities for the broader team include development, implementation and oversight of regional pricing strategy, policies and long-term capabilities across the APAC J&J MedTech (JJMT) portfolio of products with gross Regional sales of around $6B. The role will work with various clusters and regional BU teams, and pricing and finance team in close collaboration to manage and provide pricing insights and recommendations, analyze product portfolios and recommend customer level pricing across platforms and regions. It will require a high degree of business sense and understanding and proactively recommend tools and techniques to support secondary market sources and marketplace understanding across the business. The role will be required to work with the Global pricing COE to drive training and adoption of global pricing assets and data; in particular seek collaboration with global COE to identify pricing opportunities and drive execution by APAC clusters and Business units. Key Responsibilities : Lead discussions to consult with business leaders to generate insights on customer price sensitivities, market intelligence, and profitability impacts, with the objective of Profit optimization. Perform advanced analysis to evaluate critical areas for improvement, including price setting, revenue optimization, and strategic alignment with channels, and customer segment. This may include correlation analysis and regression analysis Analyze existing price strategies and improve pricing models of potential changes to quantify sales and profitability impact to customer segments, brands and markets Perform data mining, cleansing, and manipulation; identify necessary data elements and their sources, use appropriate tools to acquire and consolidate large volumes of data from different sources, and identify and resolve any irrelevant, corrupt, missing, or incongruent data Derive insights that lead into actionable recommendations. Work cross-functionally with the Pricing Team, Finance and Marketing to define, deploy and direct robust and effective price analytics, delivery, and execution capabilities. Responsible for report development such as quarterly performance of critical metrics, profit optimization, and ad-hoc analyses while also supporting risk assessment and recommendations. Education: A minimum of a bachelor s degree. MBA preferred. Background in computer science, math, marketing, or another quantitative field is preferred. Experience and Skills: Required: A minimum of 4 years of hands-on experience in problem solving using quantitative research, analysis, and data. Ability to draw conclusions from complex situations, then recommend and implement a course of action in both a timely and proactive manner. Extreme attention to detail and commitment to quality. Proven ability to translate large amounts of data into actionable insights and coherent strategies. Excellent verbal and written communication skills and the ability to interact professionally with multiple business partners. Ability to find out-of-the-box/non-traditional ways of problem solving and apply innovative thinking when approaching and defining solutions. Enjoys the challenge posed by problems and enjoys solving them. Desire to work in a fast paced, growing, deadline driven, startup-up environment. Ability to inform rapid, but fact-based decision-making with imperfect data. Self-motivated, driven to achieve team s commitments. Ability to deal with ambiguity/insufficiency: Adopts change and encourages others throughout this process. At ease creating contingency plans and rallies others to do likewise.

Add to favorites Favorited View favorites Role and KEY RESPONSIBILITIES Develop and maintain a comprehensive forecasting model, using regression analysis knowledge Utilize Workforce Management tools to forecast call volume, AHT, and shrinkage to create staffing requirements Collaborate with tactical Workforce teams Determine yearly, monthly, daily and intraday staffing requirements by gathering data on contact center statistics, marketing campaigns, system events, etc. Coordinate and facilitate collaboration with Operations leadership, Marketing, Human Resources, Finance, IT, other outsourced partners to capture forecast and staff impacting activities Manage forecast results by providing feedback, input and reporting to business partners to develop more scientific and accurate forecasting methodology Align call demand with agent supply to achieve key performance objectives (service level, utilization, budgeting, etc.) Provide long-term forecasts to Operations leaders and product owners in support of future strategic initiatives Conduct workforce simulations to provide advice regarding the impact of business strategies within contact centers Provide medium and short term forecast to account for changes in campaigns or volume disruptors Provide recommendations on adjusting staffing levels based on future business needs. Regularly communicate with other units to foster an effective team environment and ensure these areas are aware of issues that may impact their area. Provide requirements for staffing, hiring plans and Mandatory training plans to the operations team. Analyze historical data for Client volumes and Agent line requirements on complex projects and work with the operations team to get the inputs on staffing requirements, Shrinkage details, Absenteeism & Attrition. Develop and run long, medium and short range forecasts based on operations requirement using different forecasting methods. Perform other work as required and assigned. Analyzing and providing the data based on the adhoc requests to the management team. Key Skills & Knowledge IEX WFM - and other Workforce Scheduling tools. (Admin, setup, use, updated, edits, reporting MS Office - Excel, PowerPoint, Word, Access, Outlook, etc. InContact/Oracle - ACD and other ACD platforms to support multi-channel Environment - (Voice/Chat/Email/SMS) Good knowledge of the call center industry. Good understanding of the financial impact of all decisions made within the Command Center (i.e.; system downtime; overtime; home early; utilization; percent answered; etc.). Knowledge of ACD and Call Center Workforce applications - preferred. Strong oral and written communication skills. Proficient in Microsoft Office. Ability to multi-task, prioritize, and meet timelines of deliverables. Self-starter, sense of urgency, and works well under pressure. High attention to detail, sense of professionalism and ability to develop relationships QUALIFICATIONS Graduate Be aware of employment fraud. All email communications from Ascensus or its hiring managers originate from @ascensus.com or @futureplan.com email addresses. We will never ask you for payment or require you to purchase any equipment. If you are suspicious or unsure about validity of a job posting, we strongly encourage you to apply directly through our website. For all virtual remote positions, in order to ensure associates can effectively perform their job duties with no distractions, we require an uninterrupted virtual work space and there is also an expectation of family care being in place during business hours. Additionally, there is an internet work speed requirement of 25 MBps or better for individual use. If more than one person is utilizing the same internet connection in the same household or building, then a stronger connection is required. If you are unsure of your internet speed, please check with your service provider. Note: For call center roles specifically, it is a requirement to either hardwire your equipment directly to the internet router or ensure your workstation is in close proximity to the router. Please ensure that you are able to meet these expectations before applying. At Ascensus, we aspire to make a difference for others. We are a technology-enabled services company that helps people save for a better future through our network of institutional, financial advisor, and state partners. Our culture is guided by sound principles, is committed to high standards, operates with transparency, and welcomes diversity housed within our Core Values: People Matter. Quality First. Integrity Always. Ascensus provides equal employment opportunities to all associates and applicants for employment without regard to ancestry, race, color, religion, sex, (including pregnancy, childbirth, breastfeeding and/or related medical conditions), gender, gender identity, gender expression, national origin, age, physical or mental disability, medical condition (including cancer and genetic characteristics), marital status, military or veteran status, genetic information, sexual orientation, criminal conviction record or any other protected category in accordance with applicable federal, state, or local laws ( Protected Status ). Tweet

This role is part of the Support Abuse Analytics and Insights team, which sits within a broader Global Planning, Strategy & Analytics team in Community Operations (CommOps). CommOps is responsible for developing a world-class customer support organization that scales effectively, is reliable and consistent, and provides unmatched service to our global Uber community. The Support Abuse data analytics specialist will help in defining and monitoring key business metrics for the Global Support Abuse program, which has a mission of driving efficient, fair, and accurate resolution of refunds and appeasements requests by Uber users by ensuring that automated and manual policies are not abused. This analytics team will also be partnering with many Product / Data Science / Operational teams to tackle key support abuse goals. As a data analytics specialist for the team, you will help drive impact by being a subject matter expert of our data, as we'll as assisting the team in driving projects through a data perspective. Your Impact in Role: Build and maintain source of truth dashboards, queries, and self-service data tools to be leveraged by stakeholders for monitoring business performance and guiding decisions Recommend and implement strategies to optimize queries, dashboards or analytic processes Proactively analyze data, identify trends and generate meaningful recommendations to drive business goals within the Support Abuse domain Performing impact analysis to assess the feasibility and effectiveness of programmatic or operational projects Occasionally train and mentor junior team members on analytic best practices The Experience you'll Bring: At least 2 years experience in data analytics Strong analytics, SQL, and web query skills with ability to: Select, clear and transform dataset Write simple nested statements and queries for complex problems Use Hive or Presto Experience within Python or R, with the ability to: Build self-operating dashboards Work with third-party APIs (basics) Use Pandas Library (skilled) Strong stakeholder management and communication skills, with the ability to: work with many business Stakeholders and tailor solutions to their needs explain complex technical details to non-technical business audience (excellent written and spoken English) Proficiency with at least 1 data visualization tool (eg Tableau, Looker Studio, Excel / Google Sheets) Preferred Qualifications: Coding with best practices (optimized & reusable code, versioning, etc) Creating flows (ex.: Lucidchart) Basic statistics knowledge, affinity with: experimental design and A/B Testing, Percentiles, distributions, regression analysis Exposure to: Scrum process (eg Jira) and interpretation and preparation of technical documentation Willingness to develop subject matter knowledge on Support Abuse and specific business processes to drive impactful analytic insights

Extract, clean, and prepare data from various sources (CRM, Marketo, web analytics, etc.) for analysis. Apply statistical methods hypothesis testing, correlation, forecasting, regression, sampling, time series analysis to understand the drivers of marketing performance and improve pipeline efficiency. Implement analytics strategies to understand buyer behaviors, segments, and channels across solutions. Conduct time series or regression analysis to identify trends, and understand seasonality in B2B customer behavior. Map multi-touch customer journeys to identify key behavioral signals that influence engagement, opportunity creation. and conversion Perform causal inference and experiment analysis to assess marketing lift and channel effectiveness. Collaborate with marketing and sales stakeholders to understand their business questions and translate them into analytical frameworks Build dashboards and reports and enable marketing teams with self-serve analytics tools for activation and performance monitoring. Partner with Marketing Operations to embed insights into MAP and CRM workflows. Skills & Qualifications 4+ Years of Experience in Data Science, Marketing Analytics or related fields in B2B A degree in Statistics, Data Science, Economics, Computer Science, Math or a similar domain Experience applying data science best practices to B2B marketing use cases such as lead scoring, propensity models, journey analytics, and account prioritization. Deep understanding of statistical analysis, segmentation techniques, and machine learning (e.g., regression, clustering, classification, uplift modeling). Ability to translate complex analytics into business action across marketing and sales. Comfortable working cross-functionally and presenting insights to non-technical stakeholders. Strong skills in Python (pandas, scikit-learn, seaborn/matplotlib), SQL, Google Sheet and Tableau. Familiarity with CRM/MAP, and Intent platforms (6sense, Bombora etc). Exposure to causal inference, experimentation (A/B testing), or time-to-event modeling. We are primarily an in-office environment and therefore, you will be expected to work from the Bangalore office in compliance with Pure s policies, unless you are on PTO, or work travel, or other approved leave.

Job_Description":" About Yubi Yubi, formerly known as CredAvenue, is re-defining global debt markets by freeing the flow of finance between borrowers, lenders, and investors. We are the world's possibility platform for the discovery, investment, fulfillment, and collection of any debt solution. At Yubi, opportunities are plenty and we equip you with tools to seize it. In March 2022, we became India's fastest fintech and most impactful startup to join the unicorn club with a Series B fundraising round of $137 million. In 2020, we began our journey with a vision of transforming and deepening the global institutional debt market through technology. Our two-sided debt marketplace helps institutional and HNI investors find the widest network of corporate borrowers and debt products on one side and helps corporates to discover investors and access debt capital efficiently on the other side. Switching between platforms is easy, which means investors can lend, invest and trade bonds - all in one place. Our platforms shake up the traditional debt ecosystem and offer new ways of digital finance. Yubi Credit Marketplace - With the largest selection of lenders on one platform, our credit marketplace helps enterprises partner with lenders of their choice for any capital requirements. Yubi Invest - Fixed income securities platform for wealth managers & financial advisors to channel client investments in fixed income Financial Services Platform - Designed for financial institutions to manage co-lending partnerships & asset-based securitization Spocto - Debt recovery & risk mitigation platform Accumn - Dedicated SaaS solutions platform powered by Decision-grade data, Analytics, Pattern Identifications, Early Warning Signals and Predictions to Lenders, Investors and Business Enterprises So far, we have onboarded more than 17000 enterprises, 6200 investors, and lenders and facilitated debt volumes of over INR 1,40,000 crore. Backed by marquee investors like Insight Partners, B Capital Group, Dragoneer, Sequoia Capital, LightSpeed and Lightrock, we are the only-of-its-kind debt platform globally, revolutionizing the segment. At Yubi, People are at the core of the business and our most valuable assets. Yubi is constantly growing, with 1000+ like-minded individuals today who are changing the way people perceive debt. We are a fun bunch who are highly motivated and driven to create a purposeful impact. Come join the club to be a part of our epic growth story. About the Role We seek a skilled Lead Data Scientist to join our team and help build \u201cCollection Campaign Recommendations/ Optimizations\u201d As a Lead Data Scientist, you will be key in designing, developing, and deploying ML/ RL models that experiments and optimizes the collection campaigns across digital,telecalling and field. Your experience in machine learning and strong Python programming skills will be crucial in driving innovation and business value for our clients. Key Responsibilities Develop, implement, and maintain advanced analytical models and algorithms specifically geared toward improving debt collection processes. Collaborate with business stakeholders to identify key opportunities for data-driven improvements in debt collection strategies. Enhance existing models and incorporate new data sources to continuously optimize our approach. Own the end-to-end process of metric design, tracking, and reporting related to debt collection performance. Continuously improve and update metrics to align with business objectives and regulatory requirements. Communicate findings effectively with both technical and non-technical stakeholders. Mentor, train, and support junior data scientists, fostering a culture of continuous improvement and collaboration Lead cross-functional teams on data projects, ensuring alignment between data science initiatives and business goals Stay abreast of the latest industry trends, tools, and best practices in analytics and debt management. Requirements Experience: 8 to 10 years Required Skills Technical Skills In-depth understanding of machine learning algorithms (supervised, unsupervised, and ensemble methods) and their application to risk. Expertise in statistical analysis, including hypothesis testing, regression analysis, probability theory, and data modeling techniques, to extract insights and validate machine learning models. Experience in designing, developing, and delivering end-to-end data products and solutions. Expertise in model explainability techniques (e.g., SHAP, LIME) and regulatory compliance for risk models. Strong proficiency in Python. Working knowledge of PySpark ( Good to have ) Proficiency in building and deploying models on cloud platforms (AWS). Proficiency in developing backend microservices using Fast API and working knowledge of MLOps. Experience with NLP techniques is good to have Domain Skills ( Good to have ) Prior domain expertise in debt collection processes, including credit risk assessment, regulatory compliance, and industry best practices. Proven ability to design, implement, and optimize performance metrics and key performance indicators tailored specifically for debt recovery initiatives. Education and Experience Bachelor\u2019s/Advanced degree in Data Science, Statistics, Mathematics, Computer Science, or a related field. 5 to 8 years of experience in the data science and machine learning domain Experience in the financial sector or Collection team is a bonus. ","

Job_Description":" About Yubi Yubi, formerly known as CredAvenue, is re-defining global debt markets by freeing the flow of finance between borrowers, lenders, and investors. We are the world's possibility platform for the discovery, investment, fulfillment, and collection of any debt solution. At Yubi, opportunities are plenty and we equip you with tools to seize it. In March 2022, we became India's fastest fintech and most impactful startup to join the unicorn club with a Series B fundraising round of $137 million. In 2020, we began our journey with a vision of transforming and deepening the global institutional debt market through technology. Our two-sided debt marketplace helps institutional and HNI investors find the widest network of corporate borrowers and debt products on one side and helps corporates to discover investors and access debt capital efficiently on the other side. Switching between platforms is easy, which means investors can lend, invest and trade bonds - all in one place. Our platforms shake up the traditional debt ecosystem and offer new ways of digital finance. Yubi Credit Marketplace - With the largest selection of lenders on one platform, our credit marketplace helps enterprises partner with lenders of their choice for any capital requirements. Yubi Invest - Fixed income securities platform for wealth managers & financial advisors to channel client investments in fixed income Financial Services Platform - Designed for financial institutions to manage co-lending partnerships & asset-based securitization Spocto - Debt recovery & risk mitigation platform Accumn - Dedicated SaaS solutions platform powered by Decision-grade data, Analytics, Pattern Identifications, Early Warning Signals and Predictions to Lenders, Investors and Business Enterprises So far, we have onboarded more than 17000 enterprises, 6200 investors, and lenders and facilitated debt volumes of over INR 1,40,000 crore. Backed by marquee investors like Insight Partners, B Capital Group, Dragoneer, Sequoia Capital, LightSpeed and Lightrock, we are the only-of-its-kind debt platform globally, revolutionizing the segment. At Yubi, People are at the core of the business and our most valuable assets. Yubi is constantly growing, with 1000+ like-minded individuals today who are changing the way people perceive debt. We are a fun bunch who are highly motivated and driven to create a purposeful impact. Come join the club to be a part of our epic growth story. About the Role We seek a skilled Lead Data Scientist to join our team and help build \u201cCollection Campaign Recommendations/ Optimizations\u201d As a Lead Data Scientist, you will be key in designing, developing, and deploying ML/ RL models that experiments and optimizes the collection campaigns across digital,telecalling and field. Your experience in machine learning and strong Python programming skills will be crucial in driving innovation and business value for our clients. Key Responsibilities Develop, implement, and maintain advanced analytical models and algorithms specifically geared toward improving debt collection processes. Collaborate with business stakeholders to identify key opportunities for data-driven improvements in debt collection strategies. Enhance existing models and incorporate new data sources to continuously optimize our approach. Own the end-to-end process of metric design, tracking, and reporting related to debt collection performance. Continuously improve and update metrics to align with business objectives and regulatory requirements. Communicate findings effectively with both technical and non-technical stakeholders. Mentor, train, and support junior data scientists, fostering a culture of continuous improvement and collaboration Lead cross-functional teams on data projects, ensuring alignment between data science initiatives and business goals Stay abreast of the latest industry trends, tools, and best practices in analytics and debt management. Requirements Experience: 8 to 10 years Required Skills Technical Skills In-depth understanding of machine learning algorithms (supervised, unsupervised, and ensemble methods) and their application to risk. Expertise in statistical analysis, including hypothesis testing, regression analysis, probability theory, and data modeling techniques, to extract insights and validate machine learning models. Experience in designing, developing, and delivering end-to-end data products and solutions. Expertise in model explainability techniques (e.g., SHAP, LIME) and regulatory compliance for risk models. Strong proficiency in Python. Working knowledge of PySpark ( Good to have ) Proficiency in building and deploying models on cloud platforms (AWS). Proficiency in developing backend microservices using Fast API and working knowledge of MLOps. Experience with NLP techniques is good to have Domain Skills ( Good to have ) Prior domain expertise in debt collection processes, including credit risk assessment, regulatory compliance, and industry best practices. Proven ability to design, implement, and optimize performance metrics and key performance indicators tailored specifically for debt recovery initiatives. Education and Experience Bachelor\u2019s/Advanced degree in Data Science, Statistics, Mathematics, Computer Science, or a related field. 5 to 8 years of experience in the data science and machine learning domain Experience in the financial sector or Collection team is a bonus. ","

We are seeking an experienced Advanced Analytics Specialist to join our dynamic team. This role focuses on leveraging advanced analytics techniques, including machine learning algorithms, Generative AI (GenAI), and large language models (LLMs), to drive data-driven decision-making within the retail/CPG domain. The ideal candidate will possess a strong quantitative background and a passion for transforming complex data into actionable insights. Key Responsibilities: Develop, implement, and maintain advanced analytical models using machine learning algorithms and GenAI applications Utilize various advanced analytics techniques to uncover trends, patterns, and insights from large and complex datasets. Collaborate with cross-functional teams to identify business needs and deliver data-driven solutions. Create visually compelling dashboards and reports to present findings to stakeholders. Continuously evaluate and improve existing analytics methodologies and models to enhance accuracy and performance. Stay abreast of industry trends and advancements in analytics and machine learning to drive innovation within the team. Mentor junior team members and contribute to knowledge sharing within the organization. Basic Qualifications: Bachelor s or Master s degree in Data Science, Business Analytics, Mathematics, Statistics, or a related field. 3+ years of experience in advanced analytics, data science, machine learning, Generative AI or a related field. Strong experience with quantitative modeling, predictive analytics, text analytics, and forecasting methodologies Proficiency in SQL (or Google BigQuery), Python, visualization tools like Tableau/PowerBI Familiarity with the Retail/CPG/Tech industry and experience with product, transaction, and customer-level data. Excellent communication skills, both verbal and written, with the ability to convey complex concepts to non-technical stakeholders. Strong analytical and problem-solving skills, with an inquisitive mindset. Desired Skills: Proficient in the following advanced analytics techniques: Descriptive Analytics: Statistical analysis, data visualization. Predictive Analytics: Regression analysis, time series forecasting, classification techniques, market mix modeling Prescriptive Analytics: Optimization, simulation modeling. Text Analytics: Natural Language Processing (NLP), sentiment analysis. Extensive knowledge of machine learning techniques, including: Supervised Learning: Linear regression, logistic regression, decision trees, support vector machines, random forests, gradient boosting machines among others Unsupervised Learning: K-means clustering, hierarchical clustering, principal component analysis (PCA), anomaly detection among others Reinforcement Learning: Q-learning, deep Q-networks, etc. Experience with Generative AI and large language models (LLMs) for text generation, summarization, and conversational agents. Researching, loading and application of the best LLMs (GPT, Gemini, LLAMA, etc. ) for various objectives Hyper parameter tuning Prompt Engineering Embedding Vectorization Fine tuning Proficiency in data visualization tools such as Tableau or Power BI. Strong skills in data management, structuring, and harmonization to support analytical needs. What We Offer: Opportunities for professional development and career growth. A collaborative and innovative work environment. If you are passionate about data analytics and want to make a significant impact in the retail/CPG industry, we encourage you to apply! Location: Bengaluru Brand: Merkle Time Type: Full time Contract Type: Permanent

We are seeking an experienced Advanced Analytics Specialist to join our dynamic team. This role focuses on leveraging advanced analytics techniques, including machine learning algorithms, Generative AI (GenAI), and large language models (LLMs), to drive data-driven decision-making within the retail/CPG domain. The ideal candidate will possess a strong quantitative background and a passion for transforming complex data into actionable insights. Key Responsibilities: Develop, implement, and maintain advanced analytical models using machine learning algorithms and GenAI applications Utilize various advanced analytics techniques to uncover trends, patterns, and insights from large and complex datasets. Collaborate with cross-functional teams to identify business needs and deliver data-driven solutions. Create visually compelling dashboards and reports to present findings to stakeholders. Continuously evaluate and improve existing analytics methodologies and models to enhance accuracy and performance. Stay abreast of industry trends and advancements in analytics and machine learning to drive innovation within the team. Mentor junior team members and contribute to knowledge sharing within the organization. Basic Qualifications: Bachelor s or Master s degree in Data Science, Business Analytics, Mathematics, Statistics, or a related field. 3+ years of experience in advanced analytics, data science, machine learning, Generative AI or a related field. Strong experience with quantitative modeling, predictive analytics, text analytics, and forecasting methodologies Proficiency in SQL (or Google BigQuery), Python, visualization tools like Tableau/PowerBI Familiarity with the Retail/CPG/Tech industry and experience with product, transaction, and customer-level data. Excellent communication skills, both verbal and written, with the ability to convey complex concepts to non-technical stakeholders. Strong analytical and problem-solving skills, with an inquisitive mindset. Desired Skills: Proficient in the following advanced analytics techniques: Descriptive Analytics: Statistical analysis, data visualization. Predictive Analytics: Regression analysis, time series forecasting, classification techniques, market mix modeling Prescriptive Analytics: Optimization, simulation modeling. Text Analytics: Natural Language Processing (NLP), sentiment analysis. Extensive knowledge of machine learning techniques, including: Supervised Learning: Linear regression, logistic regression, decision trees, support vector machines, random forests, gradient boosting machines among others Unsupervised Learning: K-means clustering, hierarchical clustering, principal component analysis (PCA), anomaly detection among others Reinforcement Learning: Q-learning, deep Q-networks, etc. Experience with Generative AI and large language models (LLMs) for text generation, summarization, and conversational agents. Researching, loading and application of the best LLMs (GPT, Gemini, LLAMA, etc. ) for various objectives Hyper parameter tuning Prompt Engineering Embedding Vectorization Fine tuning Proficiency in data visualization tools such as Tableau or Power BI. Strong skills in data management, structuring, and harmonization to support analytical needs. What We Offer: Opportunities for professional development and career growth. A collaborative and innovative work environment. If you are passionate about data analytics and want to make a significant impact in the retail/CPG industry, we encourage you to apply! Location: Bengaluru Brand: Merkle Time Type: Full time Contract Type: Permanent