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We are looking for an experienced AI/ML Architect to spearhead the design, development, and deployment of cutting-edge AI and machine learning systems. As the ideal candidate, you should possess a strong technical background in Python and data science libraries, profound expertise in AI and ML algorithms, and hands-on experience in crafting scalable AI solutions. This role demands a blend of technical acumen, leadership skills, and innovative thinking to enhance our AI capabilities. Your responsibilities will include identifying, cleaning, and summarizing complex datasets from various sources, developing Python/PySpark scripts for data processing and transformation, and applying advanced machine learning techniques like Bayesian methods and deep learning algorithms. You will design and fine-tune machine learning models, build efficient data pipelines, and leverage distributed databases and frameworks for large-scale data processing. In addition, you will lead the design and architecture of AI systems, with a focus on Retrieval-Augmented Generation (RAG) techniques and large language models. Your qualifications should encompass 5-7 years of total experience with 2-3 years in AI/ML, proficiency in Python and data science libraries, hands-on experience with PySpark scripting and AWS services, strong knowledge of Bayesian methods and time series forecasting, and expertise in machine learning algorithms and deep learning frameworks. You should also have experience in structured, unstructured, and semi-structured data, advanced knowledge of distributed databases, and familiarity with RAG systems and large language models for AI outputs. Strong collaboration, leadership, and mentorship skills are essential. Preferred qualifications include experience with Spark MLlib, SciPy, StatsModels, SAS, and R, a proven track record in developing RAG systems, and the ability to innovate and apply the latest AI techniques to real-world business challenges. Join our team at TechAhead, a global digital transformation company known for AI-first product design thinking and bespoke development solutions. With over 14 years of experience and partnerships with Fortune 500 companies, we are committed to driving digital innovation and delivering excellence. At TechAhead, you will be part of a dynamic team that values continuous learning, growth, and crafting tailored solutions for our clients. Together, let's shape the future of digital innovation worldwide!,

At Oracle Cloud Infrastructure (OCI), the future of cloud computing for Enterprises is being shaped by a diverse team of creators and innovators. Acting with the speed and mentality of a start-up, we maintain the scale and customer-focus of the world's leading enterprise software company. Our values form the bedrock of OCI, guiding us towards achieving excellence. We are dedicated to equity, inclusion, and respect for all individuals. Committed to the greater good in both our products and actions, we prioritize continuous learning and personal growth opportunities. Within our team, we challenge each other to transcend past achievements and collectively build a better future. As part of the AI Data organization, you will engage with fascinating challenges at the convergence of artificial intelligence and cutting-edge cloud infrastructure. Our focus involves developing cloud services utilizing Large Language Models (LLMs) and other generative models to create synthetic data for various applications including text, speech, vision, and multi-modal scenarios. Additionally, we are establishing ML benchmarking standards and frameworks to ensure the highest quality across verticals such as Healthcare and Fusion. You will operate at the IC2/IC3 career level with the following responsibilities: - Design and construct world-class Generative AI Models in text, vision, and multimodal settings for generating synthetic data. - Research and implement cutting-edge techniques such as Fine-tuning and RLHF to align Generative models with specific problem domains. - Develop tools for data acquisition, cleaning, augmentation, model training, and visualization. - Evaluate and implement ML/Deep learning/GenAI models from research papers and other public resources. - Optimize models for production usage and assist in productizing generation scenarios. - Create production code for feature processing, model prediction, serving, and monitoring in real-time and batch scenarios. - Engage in the entire software lifecycle including development, testing, CI, and production operations. - Strike a balance between product feature development and production operational considerations. Minimum Qualifications for this role include: - Ph.D. degree or Masters degree or equivalent experience in computer science, artificial intelligence, machine learning, operations research, or related technical field. - 5+ years with Masters or 3+ years with PhD of applying machine learning to solve real-world problems in industry. - Proficiency in Python or R. - Proficiency with at least one deep learning library (Pytorch, Tensorflow, or Keras) for building and deploying DNN models in production. - Expertise in NLP, Transformers, Large Language Models, and hugging face library. Optimization of LLM training and serving. - Experience in statistical models, Machine Learning solutions, and large scale Deep learning model development and serving across different data domains. - Proficiency in traditional ML libraries like scikit-learn, statsmodels, and pandas. - Track record of delivering large-scale ML solutions for complex business challenges. - Experience in production operations and ensuring quality code deployment with the ability to troubleshoot issues effectively. - Strong communication skills for articulating technical ideas through verbal and written means. At Oracle, we are committed to fostering an inclusive workforce that values diverse perspectives and backgrounds. Our dedication to innovation is fueled by hearing every voice, inspiring us to surpass previous achievements. Operating with integrity for over 40 years, we collaborate with industry leaders across various sectors. We prioritize work-life balance through a competitive suite of employee benefits designed on the principles of fairness and consistency. Our comprehensive benefits package includes flexible medical, life insurance, and retirement options. Employees are encouraged to contribute to their communities through volunteer programs. We are devoted to integrating individuals with disabilities at all stages of the employment process. If you require accessibility assistance or accommodation due to a disability, please contact us at +1 888 404 2494, option one. Disclaimer: Oracle is an Equal Opportunity Employer in the United States.,

Locations : Bengaluru | Gurgaon Who We Are Who We Are Boston Consulting Group partners with leaders in business and society to tackle their most important challenges and capture their greatest opportunities. BCG was the pioneer in business strategy when it was founded in 1963. Today, we help clients with total transformation-inspiring complex change, enabling organizations to grow, building competitive advantage, and driving bottom-line impact. To succeed, organizations must blend digital and human capabilities. Our diverse, global teams bring deep industry and functional expertise and a range of perspectives to spark change. BCG delivers solutions through leading-edge management consulting along with technology and design, corporate and digital ventures-and business purpose. We work in a uniquely collaborative model across the firm and throughout all levels of the client organization, generating results that allow our clients to thrive. We Are BCG X We’re a diverse team of more than 3,000 tech experts united by a drive to make a difference. Working across industries and disciplines, we combine our experience and expertise to tackle the biggest challenges faced by society today. We go beyond what was once thought possible, creating new and innovative solutions to the world’s most complex problems. Leveraging BCG’s global network and partnerships with leading organizations, BCG X provides a stable ecosystem for talent to build game-changing businesses, products, and services from the ground up, all while growing their career. Together, we strive to create solutions that will positively impact the lives of millions. What You'll Do Are you passionate about developing socially and ethically responsible AI systems? Are you excited by the prospect of supporting projects that apply cutting-edge AI and GenAI models to solve real-world problems? Imagine working with the BCG Responsible AI team, where you can develop and apply innovative tools for testing and evaluating GenAI products. Your daily work would involve designing and implementing testing and evaluation frameworks to help improve product quality and ensure AI systems are safe, secure, and equitable. Join a team dedicated to exploring creative solutions and pioneering advancements in Responsible AI. Your work will influence the development of GenAI applications, focusing on transparency, accountability, and trustworthiness. On the team, you'll collaborate with brilliant minds and make a tangible impact on shaping the future of AI, ensuring it meets the highest standards for responsibility and effectiveness. You will have the opportunity to support a wide variety of projects, spanning use cases, technologies, industries, and clients. Embrace the challenge of working at the intersection of cutting-edge technology, ethical innovation, and real-world applications. The Responsible AI Applied Scientist plays a critical role in the BCG Responsible AI team’s safety testing and red teaming efforts, working in conjunction with our AI and GenAI product teams to ensure alignment with our Responsible AI policy, principles, and standards, and to support the design, continuous improvement, and execution of the overall Responsible AI program at BCG. The Responsible AI Applied Scientist will work with a diverse set of stakeholders to: Develop tools and techniques to scale and accelerate AI risk assessment and measurement across BCG and our clients Collaborate with product teams to influence quality and risk measurement and mitigations in AI/GenAI products through manual efforts and scalable, quantitative approaches Research new and emerging threats and measurement/evaluation approaches to ensure our approaches stay on the cutting-edge Work with small technical teams executing risk assessment and measurement on AI/GenAI products Train and mentor technical practitioners on measurements and evaluation approaches for GenAI products Remain up to date on emerging frameworks, standards, and technical approaches, and related issues by participating in workshops, reading professional publications, maintaining personal networks, and participating in professional organizations What You'll Bring Ideal candidates will have a PhD in the social sciences field and at least 3 years of professional data science or quantitative research experience; prior professional services experience is a plus Ability to think critically about ethical, social, and business risks posed by AI systems Passion for building things and comfort working with modern data science development tools Experience designing and analyzing experiments using advanced statistical methods Experience and enthusiasm for working with Generative AI technologies Broad conceptual understanding of ML and AI paradigms (e.g., tree-based and gradient-boosted models, deep learning) Strong time management and organizational skills with the ability to prioritize and execute projects independently Team player mindset with an ability to work on diverse, cross-functional teams Strong written, verbal, and visual communication skills Ability to explain sophisticated data science concepts to non-technical audiences and translate analytical results into business implications #BCGXjob Technical Skills Must Have Experience Design and analysis of experiments Statistical modeling, including hierarchical linear models GenAI, including prompt engineering and programmatically interacting with foundation models through APIs, e.g., OpenAI, Anthropic, HuggingFace Python and the open-source data science ecosystem (e.g., Jupyter, pandas, scikit-learn, statsmodels, plotly, etc.) Version control with git Nice To Have Experience Experience with quantitative social science research. Familiarity with software engineering practices (e.g., unit testing, CI/CD). Exposure to cloud platforms (AWS, Azure, GCP) or SQL databases. Knowledge of AI risk management frameworks (e.g., NIST AI RMF) Developer tools including IDEs (e.g., VSCode, Pycharm), environment management (e.g., pyenv, conda, poetry, docker) Boston Consulting Group is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, age, religion, sex, sexual orientation, gender identity / expression, national origin, disability, protected veteran status, or any other characteristic protected under national, provincial, or local law, where applicable, and those with criminal histories will be considered in a manner consistent with applicable state and local laws. BCG is an E - Verify Employer. Click here for more information on E-Verify.

The role of AI Engineer at our company involves developing essential software features to ensure timely delivery while meeting the company's performance and quality standards. As an AI Engineer, you will be part of our team working on various data science initiatives, ranging from traditional analytics to cutting-edge AI applications. This position provides a great opportunity to gain experience in machine learning and artificial intelligence across different domains. Your core responsibilities will include developing and maintaining data processing pipelines using Python, creating and deploying GenAI applications through APIs and frameworks like semantic kernel and Langchain, conducting data analysis and generating insightful visualizations, collaborating with different teams to understand business requirements and implement AI solutions, contributing to the development and upkeep of language model evaluations and other AI applications, writing clean, documented, and tested code following best practices, and monitoring application performance while making necessary improvements. To qualify for this role, you should hold a Bachelor's degree in Computer Science, Statistics, Mathematics, or a related field, along with at least 2 years of hands-on experience in applied data science and machine learning. Proficiency in Python programming, familiarity with LLMs and their applications, experience with cloud platforms such as AWS, Azure, or GCP, version control using Git, strong analytical and problem-solving skills, and knowledge of PyTorch and Deep Learning fundamentals are essential requirements. In terms of technical skills, you should have knowledge of LLMs and Generative AI platforms, be familiar with popular LLM APIs, have experience with frameworks like Semantic Kernel, LangChain, OpenAI, and Google Vertex AI, be proficient in programming languages including Python, SQL, and R, have expertise in libraries such as HuggingFace, Transformers, Matplotlib, and Seaborn, be skilled in ML/Statistics with tools like scikit-learn, statsmodels, and PyTorch, understand data processing with Pandas, NumPy, and PySpark, and have experience working with cloud platforms like AWS, GCP, or Azure. This full-time permanent position is located in Bengaluru and is with the Merkle brand.,

Dreaming big is in our DNA. It’s who we are as a company. It’s our culture. It’s our heritage. And more than ever, it’s our future. A future where we’re always looking forward. Always serving up new ways to meet life’s moments. A future where we keep dreaming bigger. We look for people with passion, talent, and curiosity, and provide them with the teammates, resources and opportunities to unleash their full potential. The power we create together – when we combine your strengths with ours – is unstoppable. Are you ready to join a team that dreams as big as you do? AB InBev GCC was incorporated in 2014 as a strategic partner for Anheuser-Busch InBev. The center leverages the power of data and analytics to drive growth for critical business functions such as operations, finance, people, and technology. The teams are transforming Operations through Tech and Analytics. Do You Dream Big? We Need You. Job Description Job Title: Senior Data Scientist Location: Bangalore Reporting to: Senior Manager Purpose of the role This role sits at the intersection of data science and revenue growth strategy, focused on developing advanced analytical solutions to optimize pricing, trade promotions, and product mix. The candidate will lead the end-to-end design, deployment, and automation of machine learning models and statistical frameworks that support commercial decision-making, predictive scenario planning, and real-time performance tracking. By leveraging internal and external data sources—including transactional, market, and customer-level data—this role will deliver insights into price elasticity, promotional lift, channel efficiency, and category dynamics. The goal is to drive measurable improvements in gross margin, ROI on trade spend, and volume growth through data-informed strategies. Key tasks & accountabilities Design and implement price elasticity models using linear regression, log-log models, and hierarchical Bayesian frameworks to understand consumer response to pricing changes across channels and segments. Build uplift models (e.g., Linear Regression, XGBoost for treatment effect) to evaluate promotional effectiveness and isolate true incremental sales vs. base volume. Develop demand forecasting models using ARIMA, SARIMAX, and Prophet, integrating external factors such as seasonality, promotions, and competitor activity, time-series clustering and k-means segmentation to group SKUs, customers, and geographies for targeted pricing and promotion strategies. Construct assortment optimization models using conjoint analysis, choice modeling, and market basket analysis to support category planning and shelf optimization. Use Monte Carlo simulations and what-if scenario modeling to assess revenue impact under varying pricing, promo, and mix conditions. Conduct hypothesis testing (t-tests, ANOVA, chi-square) to evaluate statistical significance of pricing and promotional changes. Create LTV (lifetime value) and customer churn models to prioritize trade investment decisions and drive customer retention strategies. Integrate Nielsen, IRI, and internal POS data to build unified datasets for modeling and advanced analytics in SQL, Python (pandas, statsmodels, scikit-learn), and Azure Databricks environments. Automate reporting processes and real-time dashboards for price pack architecture (PPA), promotion performance tracking, and margin simulation using advanced Excel and Python. Lead post-event analytics using pre/post experimental designs, including difference-in-differences (DiD) methods to evaluate business interventions. Collaborate with Revenue Management, Finance, and Sales leaders to convert insights into pricing corridors, discount policies, and promotional guardrails. Translate complex statistical outputs into clear, executive-ready insights with actionable recommendations for business impact. Continuously refine model performance through feature engineering, model validation, and hyperparameter tuning to ensure accuracy and scalability. Provide mentorship to junior analysts, enhancing their skills in modeling, statistics, and commercial storytelling. Maintain documentation of model assumptions, business rules, and statistical parameters to ensure transparency and reproducibility. Other Competencies Required Presentation Skills: Effectively presenting findings and insights to stakeholders and senior leadership to drive informed decision-making. Collaboration: Working closely with cross-functional teams, including marketing, sales, and product development, to implement insights-driven strategies. Continuous Improvement: Actively seeking opportunities to enhance reporting processes and insights generation to maintain relevance and impact in a dynamic market environment. Data Scope Management: Managing the scope of data analysis, ensuring it aligns with the business objectives and insights goals. Act as a steadfast advisor to leadership, offering expert guidance on harnessing data to drive business outcomes and optimize customer experience initiatives. Serve as a catalyst for change by advocating for data-driven decision-making and cultivating a culture of continuous improvement rooted in insights gleaned from analysis. Continuously evaluate and refine reporting processes to ensure the delivery of timely, relevant, and impactful insights to leadership stakeholders while fostering an environment of ownership, collaboration, and mentorship within the team. Business Environment Main Characteristics: Work closely with Zone Revenue Management teams. Work in a fast-paced environment. Provide proactive communication to the stakeholders. This is an offshore role and requires comfort with working in a virtual environment. GCC is referred to as the offshore location. The role requires working in a collaborative manner with Zone/country business heads and GCC commercial teams. Summarize insights and recommendations to be presented back to the business. Continuously improve, automate, and optimize the process. Geographical Scope: Europe Qualifications, Experience, Skills Level of educational attainment required: Bachelor or Post-Graduate in the field of Business & Marketing, Engineering/Solution, or other equivalent degree or equivalent work experience. MBA/Engg. in a relevant technical field such as Marketing/Finance. Extensive experience solving business problems using quantitative approaches. Comfort with extracting, manipulating, and analyzing complex, high volume, high dimensionality data from varying sources. Previous Work Experience Required 5-8 years of experience in the Retail/CPG domain. Technical Skills Required Data Manipulation & Analysis: Advanced proficiency in SQL, Python (Pandas, NumPy), and Excel for structured data processing. Data Visualization: Expertise in Power BI and Tableau for building interactive dashboards and performance tracking tools. Modeling & Analytics: Hands-on experience with regression analysis, time series forecasting, and ML models using scikit-learn or XGBoost. Data Engineering Fundamentals: Knowledge of data pipelines, ETL processes, and integration of internal/external datasets for analytical readiness. Proficient in Python (pandas, scikit-learn, statsmodels), SQL, and Power BI. Skilled in regression, Bayesian modeling, uplift modeling, time-series forecasting (ARIMA, SARIMAX, Prophet), and clustering (k-means). Strong grasp of hypothesis testing, model validation, and scenario simulation. And above all of this, an undying love for beer! We dream big to create future with more cheers .

Dreaming big is in our DNA. It’s who we are as a company. It’s our culture. It’s our heritage. And more than ever, it’s our future. A future where we’re always looking forward. Always serving up new ways to meet life’s moments. A future where we keep dreaming bigger. We look for people with passion, talent, and curiosity, and provide them with the teammates, resources and opportunities to unleash their full potential. The power we create together – when we combine your strengths with ours – is unstoppable. Are you ready to join a team that dreams as big as you do? AB InBev GCC was incorporated in 2014 as a strategic partner for Anheuser-Busch InBev. The center leverages the power of data and analytics to drive growth for critical business functions such as operations, finance, people, and technology. The teams are transforming Operations through Tech and Analytics. Do You Dream Big? We Need You. Job Description Job Title: Senior Data Scientist Location: Bangalore Reporting to: Senior Manager Purpose of the role This role sits at the intersection of data science and revenue growth strategy, focused on developing advanced analytical solutions to optimize pricing, trade promotions, and product mix. The candidate will lead the end-to-end design, deployment, and automation of machine learning models and statistical frameworks that support commercial decision-making, predictive scenario planning, and real-time performance tracking. By leveraging internal and external data sources—including transactional, market, and customer-level data—this role will deliver insights into price elasticity, promotional lift, channel efficiency, and category dynamics. The goal is to drive measurable improvements in gross margin, ROI on trade spend, and volume growth through data-informed strategies. Key tasks & accountabilities Design and implement price elasticity models using linear regression, log-log models, and hierarchical Bayesian frameworks to understand consumer response to pricing changes across channels and segments. Build uplift models (e.g., Linear Regression, XGBoost for treatment effect) to evaluate promotional effectiveness and isolate true incremental sales vs. base volume. Develop demand forecasting models using ARIMA, SARIMAX, and Prophet, integrating external factors such as seasonality, promotions, and competitor activity, time-series clustering and k-means segmentation to group SKUs, customers, and geographies for targeted pricing and promotion strategies. Construct assortment optimization models using conjoint analysis, choice modeling, and market basket analysis to support category planning and shelf optimization. Use Monte Carlo simulations and what-if scenario modeling to assess revenue impact under varying pricing, promo, and mix conditions. Conduct hypothesis testing (t-tests, ANOVA, chi-square) to evaluate statistical significance of pricing and promotional changes. Create LTV (lifetime value) and customer churn models to prioritize trade investment decisions and drive customer retention strategies. Integrate Nielsen, IRI, and internal POS data to build unified datasets for modeling and advanced analytics in SQL, Python (pandas, statsmodels, scikit-learn), and Azure Databricks environments. Automate reporting processes and real-time dashboards for price pack architecture (PPA), promotion performance tracking, and margin simulation using advanced Excel and Python. Lead post-event analytics using pre/post experimental designs, including difference-in-differences (DiD) methods to evaluate business interventions. Collaborate with Revenue Management, Finance, and Sales leaders to convert insights into pricing corridors, discount policies, and promotional guardrails. Translate complex statistical outputs into clear, executive-ready insights with actionable recommendations for business impact. Continuously refine model performance through feature engineering, model validation, and hyperparameter tuning to ensure accuracy and scalability. Provide mentorship to junior analysts, enhancing their skills in modeling, statistics, and commercial storytelling. Maintain documentation of model assumptions, business rules, and statistical parameters to ensure transparency and reproducibility. Other Competencies Required Presentation Skills: Effectively presenting findings and insights to stakeholders and senior leadership to drive informed decision-making. Collaboration: Working closely with cross-functional teams, including marketing, sales, and product development, to implement insights-driven strategies. Continuous Improvement: Actively seeking opportunities to enhance reporting processes and insights generation to maintain relevance and impact in a dynamic market environment. Data Scope Management: Managing the scope of data analysis, ensuring it aligns with the business objectives and insights goals. Act as a steadfast advisor to leadership, offering expert guidance on harnessing data to drive business outcomes and optimize customer experience initiatives. Serve as a catalyst for change by advocating for data-driven decision-making and cultivating a culture of continuous improvement rooted in insights gleaned from analysis. Continuously evaluate and refine reporting processes to ensure the delivery of timely, relevant, and impactful insights to leadership stakeholders while fostering an environment of ownership, collaboration, and mentorship within the team. Business Environment Main Characteristics: Work closely with Zone Revenue Management teams. Work in a fast-paced environment. Provide proactive communication to the stakeholders. This is an offshore role and requires comfort with working in a virtual environment. GCC is referred to as the offshore location. The role requires working in a collaborative manner with Zone/country business heads and GCC commercial teams. Summarize insights and recommendations to be presented back to the business. Continuously improve, automate, and optimize the process. Geographical Scope: Europe 3. Qualifications, Experience, Skills Level of educational attainment required: Bachelor or Post-Graduate in the field of Business & Marketing, Engineering/Solution, or other equivalent degree or equivalent work experience. MBA/Engg. in a relevant technical field such as Marketing/Finance. Extensive experience solving business problems using quantitative approaches. Comfort with extracting, manipulating, and analyzing complex, high volume, high dimensionality data from varying sources. Previous Work Experience Required 5-8 years of experience in the Retail/CPG domain. Technical Skills Required Data Manipulation & Analysis: Advanced proficiency in SQL, Python (Pandas, NumPy), and Excel for structured data processing. Data Visualization: Expertise in Power BI and Tableau for building interactive dashboards and performance tracking tools. Modeling & Analytics: Hands-on experience with regression analysis, time series forecasting, and ML models using scikit-learn or XGBoost. Data Engineering Fundamentals: Knowledge of data pipelines, ETL processes, and integration of internal/external datasets for analytical readiness. Proficient in Python (pandas, scikit-learn, statsmodels), SQL, and Power BI. Skilled in regression, Bayesian modeling, uplift modeling, time-series forecasting (ARIMA, SARIMAX, Prophet), and clustering (k-means). Strong grasp of hypothesis testing, model validation, and scenario simulation. And above all of this, an undying love for beer! We dream big to create future with more cheers .

As a Data Scientist for AI Products at Linde, you will be an integral part of the Artificial Intelligence team within Linde's global corporate division. Your primary responsibility will involve working on real business challenges and opportunities across multiple countries. Your focus will be on supporting the AI team in extending existing AI products and developing new ones to cater to various use cases within Linde's business and value chain. Collaboration with diverse teams including Project Managers, Data Scientists, Data and Software Engineers will be a key aspect of your role. You will directly work with a variety of data sources, types, and structures to derive actionable insights. Developing, customizing, and managing AI software products based on Machine and Deep Learning backends will be among your core tasks. Your role will also entail supporting the replication of existing products and pipelines to other systems and geographies, defining data requirements for new developments, and interacting with business functions to identify opportunities with potential business impact. To excel in this role, you are required to have a Bachelor's or Master's degree in data science, Computational Statistics/Mathematics, Computer Science, Operations Research, or a related field. A strong understanding and practical experience in Multivariate Statistics, Machine Learning, and Probability concepts are essential. Additionally, hands-on experience with preprocessing, feature engineering, data cleansing, and Python programming skills are crucial. Proficiency in handling large datasets using SQL, knowledge of data architectures, and experience with data visualization tools like Tableau or PowerBI are desired. Your result-driven mindset, excellent communication skills, and ability to structure projects from ideation to implementation will be valuable assets in this role. Fluency in English is a must, and any experience with DevOps, MS Azure, Azure ML, Kedro, Airflow, MLflow, or similar tools will be advantageous. Working at Linde offers you the opportunity to be part of a leading global industrial gases and engineering company with a strong commitment to sustainable development and customer success. If you are looking for a challenging yet rewarding career where you can make a positive impact on the world, Linde provides limitless possibilities for your professional growth. Join us in our mission to make the world more productive and sustainable. Let's talk about how you can contribute to our team!,

About Us Udacity is on a mission of forging futures in tech through radical talent transformation in digital technologies. We offer a unique and immersive online learning platform, powering corporate technical training in fields such as Artificial Intelligence, Machine Learning, Data Science, Autonomous Systems, Cloud Computing and more. Our rapidly growing global organization is revolutionizing how the enterprise market bridges the talent shortage and skills gaps during their digital transformation journey. Udacity's mission is to democratize education. We're an online learning platform offering groundbreaking education in artificial intelligence, machine learning, robotics, virtual reality, and more fields. Focused on self-empowerment through learning, Udacity is making innovative technologies such as self-driving cars available to a global community of aspiring technologists while enabling learners at all levels to skill up with essentials like programming, web, and app development. Udacity is looking for people to join our Mentor Ops team. If you love a challenge and truly want to make a difference in the world, read on! Are you passionate about learning and helping others learn? Do you find people management and mentoring rewarding? Are you technically sound and eager to learn about different technologies? Do you thrive in a fast-paced environment with a diversity of intellectual challenges? We are looking for you! Responsibilities: Technical skills of new mentors: Responsible for selecting technically strong mentors who can provide superlative services (Project reviews and answers on the Knowledge platform) to students Technical quality of Services: Responsible for deploying processes to ensure that new and existing mentors are providing high-quality, technically accurate services to the students Mentor classification: Direct ownership of validating whether any mentor is a low, medium, or high performer. The validation exercise to encompass all data related to mentor performance, including students' ratings, P2P audit scores, and data collected by manually checking the quality of services High-performing mentors: Build and lead a community of technically skilled, high-performing mentors who would serve as technical experts for an array of Nanodegree programs Ongoing Technical certification: In a scalable manner, build technical certification modules for the mentors to strengthen their technical skills and develop the competency to support students in a better manner Technical Mentor Ops processes: Ensure timely execution of parts of Mentor ops processes that need a technical understanding of concepts. Methods include getting higher-quality answers to the students through mentors and plagiarism investigations. Select and onboard Session lead : Identifying high-performing and technical strong Session leads who would be taking virtual connect sessions for the Enterprise and Scholarship clients New Initiatives: Work closely with the rest of the Mentor Operations, Student Services, Product, Engineering, and Content teams to launch new programs and opportunities for enterprise customers, students, mentors, and more What are we looking for: Technically strong bend of mind with eagerness to learn An intermediate proficiency in Python or a similar language and development experience. Proficiency in data analysis, visualization, engineering, SQL, data Warehouses, data lakes, and data pipelines on both AWS and Azure. Exceptional ability to collect, analyze, and report on data Experience in designing, launching, and managing operational processes to drive processes at scale Proven experience in prioritizing and multitasking multiple urgent needs Intuition to guide Udacity mentors by encouraging best practices for tutoring and giving feedback Flexibility in using or learning to use different methods for tracking and conveying information, such as Zendesk, Google Docs, forums, online chat programs, and email Ideal Candidate: Strong expertise in Python, SQL, NoSQL databases (e.g., MySQL, MongoDB), data visualization tools (e.g., Tableau), statistical analysis (using Python, R, scipy, statsmodels), and data manipulation libraries (e.g., pandas, dplyr). Proficient in data integration concepts, tools for building data pipelines (like Apache Airflow), and cloud platforms (e.g., AWS, Azure) for data services deployment. Knowledgeable in big data frameworks (e.g., Apache Hadoop, Apache Spark) for large-scale data processing and analysis. Strong Problem-solving skills Good at researching and troubleshooting technical issues Empathetic and a great mentor Excellent organizational skills and ability to meet deadlines Driven by data to constantly iterate and improve An excellent communicator who excels in listening, writing, and responding professionally A team player Benefits: Experience a rewarding work environment with Udacity's perks and benefits! At Udacity, we offer you the flexibility of working from home. We also have in-person collaboration spaces in Mountain View, Cairo, Dubai and Noida and continue to build opportunities for team members to connect in person Flexible working hours Paid time off Comprehensive medical insurance coverage for you and your dependents Employee wellness resources and initiatives (access to wellness platforms like Headspace, Modern Health ) Quarterly wellness day off Personalized career development Unlimited access to Udacity Nanodegrees What We Do Forging futures in tech is our vision. Udacity is where lifelong learners come to learn the skills they need, to land the jobs they want, and to build the lives they deserve. Don't stop there! Please keep reading... You've probably heard the following statistic: Most male applicants only meet 60% of the qualifications, while women and other marginalized candidates only apply if they meet 100% of the qualifications. If you think you have what it takes but don't meet every single point in the job description, please apply! We believe that historically, many processes disproportionately hurt the most marginalized communities in society- including people of color, working-class backgrounds, women and LGBTQ people. Centering these communities at our core is pivotal for any successful organization and a value we uphold steadfastly. Therefore, Udacity strongly encourages applications from all communities and backgrounds. Udacity is proud to be an Equal Employment Opportunity employer. Please read our blog post for "6 Reasons Why Diversity, Equity, and Inclusion in the Workplace Exists" Last, but certainly not least… Udacity is committed to creating economic empowerment and a more diverse and equitable world. We believe that the unique contributions of all Udacians is the driver of our success. To ensure that our products and culture continue to incorporate everyone's perspectives and experience we never discriminate on the basis of race, color, religion, sex, gender, gender identity or expression, sexual orientation, marital status, national origin, ancestry, disability, medical condition (including genetic information), age, veteran status or military status, or any other basis protected by federal, state or local laws. As part of our ongoing work to build more diverse teams at Udacity, when applying, you will be asked to complete a voluntary self-identification survey. This survey is anonymous, we are unable to connect your application with your survey responses. Please complete this voluntary survey as we utilize the data for diversity measures in terms of gender and ethnic background in both our candidates and our Udacians. We consider this data seriously and appreciate your willingness to complete this step in the process, if you choose to do so. 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Roles and Responsibilities : Analyze category performance across sales channels (D2C, marketplaces, offline). Track KPIs like revenue, ASP, margin, sell-through, stock cover, and inventory turns. Conduct pricing, discount, and profitability analysis at SKU and category levels. Identify top-performing or underperforming products and uncover performance drivers. Build dashboards and automated reports for category health and inventory planning. Collaborate with marketing, SCM, and category teams to inform business decisions. Perform trend, seasonality, and cohort analysis to improve demand forecasting. Use customer behavior data (views, clicks, conversions) to support assortment planning. Automate reporting workflows and optimize SQL/Python pipelines. Support new product launches with benchmarks and success prediction models. Skills & Qualifications : 0–2 years of experience in a data analytics role, preferably in E- commerce or Retail. Proficiency in MySQL: writing complex queries, joins, window functions. Advanced Excel/Google Sheets: pivot tables, dynamic dashboards, conditional formatting. Experience in Python: Pandas, automation scripts, statsmodels/scikit- learn. Comfort with data visualization: Power BI / Tableau / Looker Studio. Understanding of product lifecycle, inventory metrics, pricing levers, and customer insights. Strong foundation in statistics: descriptive stats, A/B testing, forecasting models. Excellent problem-solving, data storytelling, and cross-functional collaboration skills. Preferred / Bonus Skills : Experience with Shopify, Magento, or other e-commerce platforms. Familiarity with Google Analytics 4 (GA4). Knowledge of merchandising or visual analytics. Exposure to machine learning (e.g., clustering, success prediction). Experience with VBA or Google Apps Script for reporting automation.

As a Senior Data Scientist with 5+ years of experience, you will play a crucial role in our team based in Indore/Pune. Your responsibilities will involve designing and implementing models, extracting insights from data, and interpreting complex data structures to facilitate business decision-making. You should have a strong background in Machine Learning areas such as Natural Language Processing, Machine Vision, Time Series, etc. Your expertise should extend to Model Tuning, Model Validation, Supervised and Unsupervised Learning. Additionally, hands-on experience with model development, data preparation, and deployment of models for training and inference is essential. Proficiency in descriptive and inferential statistics, hypothesis testing, and data analysis and exploration are key skills required for this role. You should be adept at developing code that enables reproducible data analysis. Familiarity with AWS services like Sagemaker, Lambda, Glue, Step Functions, and EC2 is expected. Knowledge of data science code development and deployment IDEs such as Databricks, Anaconda distribution, and similar tools is essential. You should also possess expertise in ML algorithms related to time-series, natural language processing, optimization, object detection, topic modeling, clustering, and regression analysis. Your skills should include proficiency in Hive/Impala, Spark, Python, Pandas, Keras, SKLearn, StatsModels, Tensorflow, and PyTorch. Experience with end-to-end model deployment and production for at least 1 year is required. Familiarity with Model Deployment in Azure ML platform, Anaconda Enterprise, or AWS Sagemaker is preferred. Basic knowledge of deep learning algorithms like MaskedCNN, YOLO, and visualization and analytics/reporting tools such as Power BI, Tableau, Alteryx would be advantageous for this role.,

Ciklum is looking for a Senior Data Scientist to join our team full-time in India. We are a custom product engineering company that supports both multinational organizations and scaling startups to solve their most complex business challenges. With a global team of over 4,000 highly skilled developers, consultants, analysts and product owners, we engineer technology that redefines industries and shapes the way people live. About the role: As a Senior Data Scientist, become a part of a cross-functional development team working for A healthcare technology company that provides platforms and solutions to improve the management and access of cost-effective pharmacy benefits. Our technology helps enterprise and partnership clients simplify their businesses and helps consumers save on prescriptions. Our client is a leader in SaaS technology for healthcare, They offer innovative solutions with integrated intelligence on a single enterprise platform that connects the pharmacy ecosystem. With their expertise and modern, modular platform, our partners use real-time data to transform their business performance and optimize their innovative models in the marketplace. Responsibilities: Development of prototype solutions, mathematical models, algorithms, machine learning techniques, and robust analytics to support analytic insights and visualization of complex data sets Work on exploratory data analysis so you can navigate a dataset and come out with broad conclusions based on initial appraisals Provide optimization recommendations that drive KPIs established by product, marketing, operations, PR teams, and others Interacts with engineering teams and ensures that solutions meet customer requirements in terms of functionality, performance, availability, scalability, and reliability Work directly with business analysts and data engineers to understand and support their use cases Work with stakeholders throughout the organization to identify opportunities for leveraging company data to drive business solutions Drive innovation by exploring new experimentation methods and statistical techniques that could sharpen or speed up our product decision-making processes Cross-trains other team members on technologies being developed, while also continuously learning new technologies from other team members Contribute to unit’s activities and community building, participate in conferences, and provide excellence in exercise and best practices Requirements: We know that sometimes, you can’t tick every box. We would still love to hear from you if you think you’re a good fit! 5+ years of development of Data Science solutions with a proven track record of leveraging analytics to drive significant business impact Bachelor's/Master's degree in Mathematics, Statistics, Computer Science, Operations Research, Econometrics or related field Proven ability to relate and solve business problems through machine learning and statistics 4+ years of experience applying various machine learning techniques: regression, classification, clustering, dimensional reduction, time series prediction, and/or outlier detection, recommendation systems Understanding of advantages and drawbacks of machine learning algorithms as well as their usage constraints including performance 4+ years of experience in Python development of machine learning solutions and statistical analysis: Pandas, SciPy, Scikit-learn, XGBoost, LightGBM, and/or statsmodels, imbalanced-learn libraries and ML libraries like scikit-learn, TensorFlow, PyTorch, data wrangling and visualization (e.g., Pandas, NumPy, Matplotlib, Seaborn Experience in working with large-scale datasets, including time series and healthcare data Experience with NLP, deep learning and GenAI Experience diving into data to consider hidden patterns and conducting error analysis 2+ years experience in data visualization: Power BI, Tableau, and/or Python libraries like Matplotlib and Seaborn Experience with SQL for data processing, data manipulation, sampling, reporting 3+ years experience creating/maintaining of OOP Machine Learning solutions Understanding of CRISP-ML(Q) / TDSP concept 1+ year of experience with MLOps: integration of reliable Machine Learning Pipelines in Production, Docker, containerization, orchestration 2+ years of experience with Clouds (AWS, Azure, GCP) and Clouds AI And ML Services(e.g. Amazon Sage Maker, Azure ML) Excellent time and project management skills, with the ability to manage detailed work and communicate project status effectively to all levels Desirable: Probability Theory & Statistics knowledge and intuition as well as understanding of Mathematics behind Machine Learning 1+ year of experience in Deep Learning solution development with Tensorflow or PyTorch libraries Data Science / Machine Learning certifications, or research experience with papers being published Experience with Kubernetes Experience with Databricks, Snowflake platforms 1+ year of BigData experience, i.e. Hadoop / Spark Experience with No-SQL, and/or columnar/graph databases What`s in it for you? Care: your mental and physical health is our priority. We ensure comprehensive company-paid medical insurance, as well as financial and legal consultation Tailored education path: boost your skills and knowledge with our regular internal events (meetups, conferences, workshops), Udemy license, language courses and company-paid certifications Growth environment: share your experience and level up your expertise with a community of skilled professionals, locally and globally Opportunities: we value our specialists and always find the best options for them. Our Resourcing Team helps change a project if needed to help you grow, excel professionally, and fulfil your potential Global impact: work on large-scale projects that redefine industries with international and fast-growing clients Welcoming environment: feel empowered with a friendly team, open-door policy, informal atmosphere within the company and regular team-building events About us: India is a strategic growth market for Ciklum. Be a part of a big story created right now. Let’s grow our delivery center in India together! Boost your skills and knowledge: create and innovate with like-minded professionals — all of that within a global company with a local spirit and start-up soul. Supported by Recognize Partners and expanding globally, we will engineer the experiences of tomorrow! Be bold, not bored! Interested already? We would love to get to know you! Submit your application. We can’t wait to see you at Ciklum.

Who You'll Work With Driving lasting impact and building long-term capabilities with our clients is not easy work. You are the kind of person who thrives in a high performance/high reward culture - doing hard things, picking yourself up when you stumble, and having the resilience to try another way forward. In return for your drive, determination, and curiosity, we'll provide the resources, mentorship, and opportunities you need to become a stronger leader faster than you ever thought possible. Your colleagues—at all levels—will invest deeply in your development, just as much as they invest in delivering exceptional results for clients. Every day, you'll receive apprenticeship, coaching, and exposure that will accelerate your growth in ways you won’t find anywhere else. When you join us, you will have: Continuous learning: Our learning and apprenticeship culture, backed by structured programs, is all about helping you grow while creating an environment where feedback is clear, actionable, and focused on your development. The real magic happens when you take the input from others to heart and embrace the fast-paced learning experience, owning your journey. A voice that matters: From day one, we value your ideas and contributions. You’ll make a tangible impact by offering innovative ideas and practical solutions. We not only encourage diverse perspectives, but they are critical in driving us toward the best possible outcomes. Global community: With colleagues across 65+ countries and over 100 different nationalities, our firm’s diversity fuels creativity and helps us come up with the best solutions for our clients. Plus, you’ll have the opportunity to learn from exceptional colleagues with diverse backgrounds and experiences. World-class benefits: On top of a competitive salary (based on your location, experience, and skills), we provide a comprehensive benefits package to enable holistic well-being for you and your family. Your Impact You will be responsible for developing deep Retail domain understanding in at least one of the following areas –Customer Analytics, Pricing Optimization, Inventory Management, E-commerce, or Digital Transformation. Collaboration with business stakeholders, engineers and internal teams to build and implement extraordinary retail focused data products (reusable asset) and solutions and delivering them right to the client will be of utmost importance. You will work on the frameworks and libraries that our teams of Data Scientists and Data Engineers use to progress from data to impact and guide global companies through data science solutions to transform their businesses and enhance performance across industries including E-commerce, Grocery, F&B and CPG. Your Qualifications and Skills Masters's or PhD degree in computer science, engineering or mathematics, or equivalent experience 6+ years of relevant experience with strong foundations of statistics and machine learning techniques Proven experience applying machine learning techniques to solve business problems Proven experience in translating technical methods to non-technical stakeholder Proven experience writing production-grade code (Python / Pyspark) for machine learning in a professional setting Strong understanding of analytics libraries (e.g., pandas, numpy, matplotlib, scikit-learn, statsmodels, kedro, mlflow) Experience in any cloud platforms (AWS, Azure, or GCP) Familiarity with containerization technologies (Docker, Docker-compose) Experience with Git-based workflows and automation frameworks, specifically GitHub Actions and GitLab CI/CD Familiarity or hands-on experience with data visualization tools (PowerBI, Tableau, etc.)

Job Description First Solar reserves the right to offer you a role most applicable to your experience and skillset. Basic Job Functions: This position manages organizational strategy and operations through design and statistical analysis of business initiatives and experiments. Works with business partners to understand what the business needs and issues are to address. Applies advanced knowledge of statistics and data mining (e.g., predictive modelling, simulation) or other mathematical techniques to recognize patterns and create insights from business data. Designs, develops, and evaluates statistical and predictive models that lead to business solutions. Serves as lead statistician for the unit, providing expertise, oversight, and guidance on statistical analysis efforts. Communicate findings and recommendations to management across different departments. Supports implementation efforts. Should lead and mentor the team working in the Data Competency Centre. Education/Experience: Bachelor’s degree in data science, Computer science, Electrical Engineering, Applied Statistics, or Physics with 8-10 years of relevant work experience in Data Science, Artificial Intelligence or Machine Learning algorithm development Master’s degree in data science, Computer science, Electrical Engineering, Applied Statistics, or Physics with 5+ years of relevant work experience in Data Science, Artificial Intelligence or Machine Learning algorithm development PhD degree in Data Science, Computer science, Electrical Engineering, Applied Statistics, or Physics with 4+ years of relevant work experience in Data Science, Artificial Intelligence or Machine Learning algorithm development Working knowledge of budgets and financial statements Required Skills/Competencies: Demonstrated skill of managing teams; Ability to coach and mentor team members to drive results Demonstrated experience with programming languages and statistical software tools (Python, SAS, R, JMP or similar), relational databases (SQL server), data analysis and visualization software (preferably PowerBI, SAS). Demonstrated experience with standard data science and machine learning packages such as Numpy, Pandas, Matplotlib, seaborn, bokeh, plotly Demonstrated experience with the machine learning model stack (regression, classification, neural networks, time series) and packages (Scikit learn, Xgboost, Keras, Pytorch, Tensorflow, statsmodels) Demonstrated experience of the machine learning model tradeoffs such as hyper-parameter tuning, regularization, cross-validation, skewness in data, dimensionality reduction, and complexity vs interpretability. Demonstrated experience with utilizing advanced descriptive statistics and analysis techniques (such as forecasting, analysis of variance, t-tests, categorical data analysis, nonparametric data analysis, cluster analysis, factor analysis and multivariate statistical analysis) design business experiments and measure the impact of business actions. Demonstrated experience with computer vision models (e.g. image classification, object detection, and segmentation) Demonstrated experience working with various business partners to scope and design the statistical framework for business solutions and socialize and help integrate results. Strong communication skills to work with groups, and experience with communicating business implications of complex data relationships and results of statistical models to multiple business partners. Essential Responsibilities: Statistical Analysis & Model Development Works with business partners to identify and scope new opportunities for statistical analysis applications to evaluate business performance and to support business decisions. Works internally and with I/S and Enterprise Data Management to define, secure and prepare datasets for statistical modeling. Explores data using a variety of statistical (e.g., data mining, regression, cluster analysis) techniques to answer business questions or guide future model development. Build programs for running statistical tests on data and for understanding correlation of various attributes. Builds hypotheses, identifies research data attributes and determines the best approach to address business issues. Working with business partners leads development of experimental design for business initiatives. Applies advanced statistical techniques, including analysis of variance, t-tests, factor analysis, regression and multivariate analyses or simulation, to analyze the effects of business initiatives. Build predictive models (e.g. logistic regression, generalized linear models) as appropriate to support business partner objectives. Builds and deploys computer vision models (e.g., image classification, object detection, segmentation) to meet business needs. Prepares testing scenarios and tests model performance. Incorporates findings and provides insights as part of model development and enhancement. Provides guidance and direction related to statistical analysis to less experienced Data Science & Analytics staff as needed. Provides peer review related to analytics methods and results. Responsible for advanced analytics, including experimental design and analysis, for the most complex business experiments. Model Consultation, Implementation, & Communication Serves as statistical expert within the unit as well as in consultation to various areas of the business, to support design and analysis of business experiments. Leads analytics projects or components related to large, complex business initiatives. Prepare recommendations and findings for business partners. Works with research and analytics staff and other areas of the business on model application and implementation. Effectively communicates and delivers statistical and predictive model results to business partners, supporting socialization and adoption of analysis results into business activities and decisions. Assists with knowledge transfer and training to business areas regarding new analytics applications as part of implementation process. Works closely with business stakeholders to identify and answer critical questions. Assists in the development of standard analytical approaches and methodologies for the department. Provides knowledge transfer and training on new modeling and statistical analysis tools and methodologies to less experienced staff. Industry Research Research and maintain awareness of industry’s best practices and business strategies. Proactively brings in new and innovative ideas and approaches to develop business solutions. Research and leverage new statistical techniques and technologies to apply in their statistical research work. Reporting Relationships: Will report to Head- Automation Digital Transformation USA This role will have direct reports Travel: Physical Requirements: Will sit and stand for long periods of time during the day. Will walk, climb stairs and on equipment. May reach above shoulder heights and below the waist May lift up to 50 lbs. Required to use hands to finger, lift, handle, carry or feel objects. May stoop, kneel, bend, talk and hear. Specific vision abilities are required. All associates working on the production floor may be required to wear a respirator at any given time and thus, the ability to wear a respirator is a condition of employment and continued employment (require little or no facial hair). Office Physical Requirements: All positions in our office require interaction with people and technology while either standing or sitting. To best service our customers, internal and external, all associates must be able to communicate face-to-face and on the phone with or without reasonable accommodation. First Solar is committed to compliance with its obligations under all applicable state and federal laws prohibiting employment discrimination. In keeping with this commitment, it attempts to reasonably accommodate applicants and employees in accordance with the requirements of the disability discrimination laws. It also invites individuals with disabilities to participate in a good faith, interactive process to identify reasonable accommodations that can be made without imposing an undue hardship. Potential candidates will meet the education and experience requirements provided on the above job description and excel in completing the listed responsibilities for this role. All candidates receiving an offer of employment must successfully complete a background check and any other tests that may be required. Equal Opportunity Employer Statement: First Solar is an Equal Opportunity Employer that values and respects the importance of a diverse and inclusive workforce. It is the policy of the company to recruit, hire, train and promote persons in all job titles without regard to race, color, religion, sex, age, national origin, veteran status, disability, sexual orientation, or gender identity. We recognize that diversity and inclusion is a driving force in the success of our company. I have read and understand the above ‘Roles and Responsibilities’ for this position. I believe I meet the ‘Minimum Qualifications’ to perform the required ‘Essential Functions & Responsibilities’ to the best of my abilities.

Gurgaon, India We are seeking an Associate Consultant to join our India team based in Gurgaon. This role at Viscadia offers a unique opportunity to gain hands-on experience in the healthcare industry, with comprehensive training in core consulting skills such as critical thinking, market analysis, and executive communication. Through project work and direct mentorship, you will develop a deep understanding of healthcare business dynamics and build a strong foundation for a successful consulting career. ROLES AND RESPONSIBILITIES Technical Responsibilities Design and build full-stack forecasting and simulation platforms using modern web technologies (e.g., React, Node.js, Python) hosted on AWS infrastructure (e.g., Lambda, EC2, S3, RDS, API Gateway). Automate data pipelines and model workflows using Python for data preprocessing, time-series modeling (e.g., ARIMA, Exponential Smoothing), and backend services. Develop and enhance product positioning, messaging, and resources that support the differentiation of Viscadia from its competitors. Conduct research and focus groups to elucidate key insights that augment positioning and messaging Replace legacy Excel/VBA tools with scalable, cloud-native applications, integrating dynamic reporting features and user controls via web UI. Use SQL and cloud databases (e.g., AWS RDS, Redshift) to query and transform large datasets as inputs to models and dashboards. Develop interactive web dashboards using frameworks like React + D3.js or embed tools like Power BI/Tableau into web portals to communicate insights effectively. Implement secure, modular APIs and microservices to support modularity, scalability, and seamless data exchange across platforms. Ensure cost-effective and reliable deployment of solutions via AWS services, CI/CD pipelines, and infrastructure-as-code (e.g., CloudFormation, Terraform). Business Responsibilities Support the development and enhancement of forecasting and analytics platforms tailored to the needs of pharmaceutical clients across various therapeutic areas Build in depth understanding of pharma forecasting concepts, disease areas, treatment landscapes, and market dynamics to contextualize forecasting models and inform platform features Partner with cross-functional teams to ensure forecast deliverables align with client objectives, timelines, and decision-making needs Contribute to a culture of knowledge sharing and continuous improvement by mentoring junior team members and helping codify best practices in forecasting and business analytics Grow into a client-facing role, combining an understanding of commercial strategy with forecasting expertise to lead engagements and drive value for clients QUALIFICATIONS Bachelor’s degree (B.Tech/B.E.) from a premier engineering institute, preferably in Computer Science, Information Technology, Electrical Engineering, or related disciplines 2+ years of experience in full-stack development, with a strong focus on designing, developing, and maintaining AWS-based applications and services SKILLS & TECHNICAL PROFICIENCIES Technical Skills Proficient in Python, with practical experience using libraries such as pandas, NumPy, matplotlib/seaborn, and statsmodels for data analysis and statistical modeling Strong command of SQL for data querying, transformation, and seamless integration with backend systems Hands-on experience in designing and maintaining ETL/ELT data pipelines, ensuring efficient and scalable data workflows Solid understanding and applied experience with cloud platforms, particularly AWS; working familiarity with Azure and Google Cloud Platform (GCP) Full-stack web development expertise, including building and deploying modern web applications, web hosting, and API integration Proficient in Microsoft Excel and PowerPoint, with advanced skills in data visualization and delivering professional presentations Soft Skills Excellent verbal and written communication skills, with the ability to effectively engage both technical and non-technical stakeholders Strong analytical thinking and problem-solving abilities, with a structured and solution-oriented mindset Demonstrated ability to work independently as well as collaboratively within cross-functional teams Adaptable and proactive, with a willingness to thrive in a dynamic, fast-growing environment Genuine passion for consulting, with a focus on delivering tangible business value for clients Domain Expertise (Good to have) Strong understanding of pharmaceutical commercial models, including treatment journeys, market dynamics, and key therapeutic areas Experience working with and interpreting industry-standard datasets such as IQVIA, Symphony Health, or similar secondary data sources Familiarity with product lifecycle management, market access considerations, and sales performance tracking metrics used across the pharmaceutical value chain

Job Description Change the world. Love your job. Texas Instruments is seeking experienced Data Scientist to join our team. As the Data Scientist in TI's Demand Analytics team, you will play a pivotal role in shaping and executing our demand planning and inventory buffer strategies for the company. You will be working side by side with a team of highly technical professionals that will consists of application developers, system architects, data scientists and data engineers. This role will be responsible for solving complex business problems through innovative solutions that deliver tangible business value. This position requires a technical leader with a strong technical background in AI/ML, simulation solutions, strategic thinking, and a passion for innovation through data.This team is responsible for:portfolio management for demand forecasting algorithms, generation of inventory buffer targets, segmentation of TI's products and simulation/validation frameworks, defining specs/reference architectures to best achieve business outcomes and ensuring security and interoperability between capabilities. Roles And Duties Stakeholder engagement: Work collaboratively and strategically with stakeholder groups to achieve TI business strategy and goals Communicate complex technical concepts and influence final business outcomes with stakeholders effectively Partner with cross-functional teams to identify and prioritize actionable, high-impact insights across a variety of core business areas Technology and platforms: Build simple, scalable and modular technology stacks using modern technologies and software engineering principles. Simulate real world scenarios with various models and approaches to determine best fit of algorithms by varying the inputs across hundreds to thousands of variables Research, experiment and implement new approaches and models that flex with the business strategy transformations Leads data acquisition and engineering efforts Develops and applies machine learning, AI and data engineering framework Solutions, writes and debugs code for complex development projects Oversees, evaluates and determines the best modeling techniques for various scenarios letting the data drive the conversation Qualifications Minimum requirements: MS or PhD in a quantitative field (e.g., Computer Science, Statistics, Engineering, Mathematics) or equivalent practical experience. 8+ years of professional experience in data science or a related role. 5+ years of hands-on experience developing and deploying time series forecasting models in a professional setting. Demonstrated experience in the supply chain domain (e.g., Semiconductor, Retail, CPG, Pharmaceutical), with a deep understanding of concepts like demand forecasting, S&OP, or inventory management. Expert-level proficiency in Python and its core data science libraries (e.g., Pandas, NumPy, Scikit-learn, Statsmodels) and forecasting packages (e.g., Prophet, PyTorch Forecasting). Proven experience taking machine learning models from prototype to production, including knowledge of CI/CD and model monitoring. Preferred Qualifications Experience with MLOps tools and platforms (e.g., MLflow, Kubeflow, Airflow, Docker, Kubernetes). Practical experience with cloud data science platforms (e.g., AWS SageMaker, Azure ML, Google AI Platform). Familiarity with advanced forecasting techniques such as probabilistic forecasting, causal inference, or using Transformers for time series. Experience applying NLP to extract features from unstructured text to enhance forecasting models. Strong SQL skills and experience working with large-scale data warehousing solutions (e.g., Snowflake, BigQuery, Redshift). About Us Why TI? Engineer your future. We empower our employees to truly own their career and development. Come collaborate with some of the smartest people in the world to shape the future of electronics. We're different by design. Diverse backgrounds and perspectives are what push innovation forward and what make TI stronger. We value each and every voice, and look forward to hearing yours. Meet the people of TI Benefits that benefit you. We offer competitive pay and benefits designed to help you and your family live your best life. Your well-being is important to us. About Texas Instruments Texas Instruments Incorporated (Nasdaq: TXN) is a global semiconductor company that designs, manufactures and sells analog and embedded processing chips for markets such as industrial, automotive, personal electronics, communications equipment and enterprise systems. At our core, we have a passion to create a better world by making electronics more affordable through semiconductors. This passion is alive today as each generation of innovation builds upon the last to make our technology more reliable, more affordable and lower power, making it possible for semiconductors to go into electronics everywhere. Learn more at TI.com . Texas Instruments is an equal opportunity employer and supports a diverse, inclusive work environment. If you are interested in this position, please apply to this requisition. About The Team TI does not make recruiting or hiring decisions based on citizenship, immigration status or national origin. However, if TI determines that information access or export control restrictions based upon applicable laws and regulations would prohibit you from working in this position without first obtaining an export license, TI expressly reserves the right not to seek such a license for you and either offer you a different position that does not require an export license or decline to move forward with your employment.

We are seeking an Full Stack Developer (Associate Consultant) to join our India team based in Gurgaon. This role at Viscadia offers a unique opportunity to gain hands-on experience in the healthcare industry, with comprehensive training in core consulting skills such as critical thinking, market analysis, and executive communication. Through project work and direct mentorship, you will develop a deep understanding of healthcare business dynamics and build a strong foundation for a successful consulting career. ROLES AND RESPONSIBILITIES Technical Responsibilities Design and build full-stack forecasting and simulation platforms using modern web technologies (e.g., React, Node.js, Python) hosted on AWS infrastructure (e.g., Lambda, EC2, S3, RDS, API Gateway). Automate data pipelines and model workflows using Python for data preprocessing, time-series modeling (e.g., ARIMA, Exponential Smoothing), and backend services. Replace legacy Excel/VBA tools with scalable, cloud-native applications, integrating dynamic reporting features and user controls via web UI. Use SQL and cloud databases (e.g., AWS RDS, Redshift) to query and transform large datasets as inputs to models and dashboards. Develop interactive web dashboards using frameworks like React + D3.js or embed tools like Power BI/Tableau into web portals to communicate insights effectively. Implement secure, modular APIs and microservices to support modularity, scalability, and seamless data exchange across platforms. Ensure cost-effective and reliable deployment of solutions via AWS services, CI/CD pipelines, and infrastructure-as-code (e.g., CloudFormation, Terraform). Business Responsibilities Support the development and enhancement of forecasting and analytics platforms tailored to the needs of pharmaceutical clients across various therapeutic areas Build in depth understanding of pharma forecasting concepts, disease areas, treatment landscapes, and market dynamics to contextualize forecasting models and inform platform features Partner with cross-functional teams to ensure forecast deliverables align with client objectives, timelines, and decision-making needs Contribute to a culture of knowledge sharing and continuous improvement by mentoring junior team members and helping codify best practices in forecasting and business analytics Grow into a client-facing role, combining an understanding of commercial strategy with forecasting expertise to lead engagements and drive value for clients QUALIFICATIONS Bachelor’s degree (B.Tech/B.E.) from a premier engineering institute, preferably in Computer Science, Information Technology, Electrical Engineering, or related disciplines 2+ years of experience in full-stack development, with a strong focus on designing, developing, and maintaining AWS-based applications and services SKILLS AND TECHNICAL PROFICIENCIES Technical Skills Proficient in Python, with practical experience using libraries such as pandas, NumPy, matplotlib/seaborn, and statsmodels for data analysis and statistical modeling Strong command of SQL for data querying, transformation, and seamless integration with backend systems Hands-on experience in designing and maintaining ETL/ELT data pipelines, ensuring efficient and scalable data workflows Solid understanding and applied experience with cloud platforms, particularly AWS; working familiarity with Azure and Google Cloud Platform (GCP) Full-stack web development expertise, including building and deploying modern web applications, web hosting, and API integration Proficient in Microsoft Excel and PowerPoint, with advanced skills in data visualization and delivering professional presentations Soft Skills Excellent verbal and written communication skills, with the ability to effectively engage both technical and non-technical stakeholders Strong analytical thinking and problem-solving abilities, with a structured and solution-oriented mindset Demonstrated ability to work independently as well as collaboratively within cross-functional teams Adaptable and proactive, with a willingness to thrive in a dynamic, fast-growing environment Genuine passion for consulting, with a focus on delivering tangible business value for clients Domain Expertise Strong understanding of pharmaceutical commercial models, including treatment journeys, market dynamics, and key therapeutic areas Experience working with and interpreting industry-standard datasets such as IQVIA, Symphony Health, or similar secondary data sources Familiarity with product lifecycle management, market access considerations, and sales performance tracking metrics used across the pharmaceutical value chain

Urgently Hiring for AI/ML Role We are seeking an experienced AI/ML Engineer with 3–5 years of hands-on experience in building and deploying machine learning solutions in the fintech and spend management domain. You will work on real-time forecasting, intelligent document processing (invoices/receipts), fraud detection, and other AI-powered features that enhance our finance intelligence platform. This role demands expertise in both time series forecasting and computer vision, as well as a solid understanding of how ML applies to enterprise finance operations. Key Responsibilities: Design, train, and deploy ML models for spend forecasting, budget prediction, expense categorization, and risk scoring. Build and optimize OCR-based invoice and receipt parsing systems using computer vision and NLP techniques. Implement time-series models (Prophet, ARIMA, LSTM, XGBoost, etc.) for forecasting trends in financial transactions, expenses, and vendor payments. Work on intelligent document classification, key-value extraction, and line-item detection from unstructured financial documents (PDFs, scanned images). Collaborate with product and finance teams to define high-impact AI use cases and deliver business-ready solutions. Integrate ML pipelines into production using scalable tools and platforms (Docker, CI/CD, cloud services). Monitor model performance post-deployment, conduct drift analysis, and implement retraining strategies. Required Skills & Qualifications: Core Machine Learning Strong knowledge of supervised and unsupervised ML techniques applied to structured and semi-structured financial data Experience in time-series analysis and forecasting algorithms such as: ARIMA, SARIMA Facebook Prophet XGBoost for regression LSTM / GRU models for sequential data Proficiency in Python and key libraries: scikit-learn, Pandas, NumPy, StatsModels, PyTorch, TensorFlow. Computer Vision & Document AI Hands-on experience with OCR tools such as Tesseract, Google Vision API, or AWS Textract. Knowledge of document layout analysis and field-level extraction using OpenCV, LayoutLM, or Google Document AI. Familiarity with annotation tools (Label Studio, CVAT) and post-processing OCR outputs for structured data extraction. Deployment & Engineering Experience in exposing ML models via Flask or FastAPI. Model packaging and deployment with Docker, version control with Git, and ML lifecycle tools like MLflow or DVC. Working knowledge of cloud platforms (AWS/GCP/Azure) and integrating models with backend microservices. Data & Domain Understanding of financial documents: invoices, receipts, expense reports, and GL data. Ability to work with tabular, image-based, and PDF-based financial datasets. SQL proficiency and familiarity with financial databases or ERP systems is a plus.

Job Title: Data Scientist Type: Contract Experience: 5+ years Contract Duration: 6 months + Extendable Location: Remote Time zone: IST/UK Shift Key Responsibilities: Develop predictive models using time series and regression techniques etc.. Perform diagnostic analysis to identify patterns, outliers, and potential drivers of campaign performance Evaluate data quality and recommend strategies to address gaps or improve model accuracy Work closely with data engineering team Translate business objectives into data science approaches that are explainable and reliable Required Skills: Strong experience in statistical modeling, machine learning, and time series forecasting Proficiency in Python (Pandas, scikit-learn, statsmodels) and SQL Experience building rule-based or constraint-based decision models Comfort designing interpretable logic or simulation frameworks to support “what-if” planning and tactical recommendations Experience using/implementing LLMs or NLP Nice to Have: Familiarity with attribution modeling, marketing mix modeling Prior work on AI-driven reporting/insight tools using LLMs or NLP Experience working with marketing/media data Exposure to cloud-based environments (AWS preferred)

As a Senior Data Scientist with 5+ years of experience, you will be responsible for designing and implementing models, mining data for insights, and interpreting complex data structures to drive business decision-making. Your expertise in machine learning, including areas such as NLP, Machine vision, and Time series, will be essential in this role. You will be expected to have strong skills in Model Tuning, Model Validation, Supervised and Unsupervised Learning, and hands-on experience with model development, data preparation, training, and inference-ready deployment of models. Your proficiency in descriptive and inferential statistics, hypothesis testing, and data analysis will help in developing code for reproducible analysis of data. Experience with AWS services like Sagemaker, Lambda, Glue, Step functions, and EC2 is necessary, along with knowledge of Databricks, Anaconda distribution, and similar data science code development and deployment IDEs. Your familiarity with ML algorithms related to time-series, natural language processing, optimization, object detection, topic modeling, clustering, and regression analysis will be highly valued. You should have expertise in Hive/Impala, Spark, Python, Pandas, Keras, SKLearn, StatsModels, Tensorflow, and PyTorch. End-to-end model deployment and production experience of at least 1 year is required, along with a good understanding of Model Deployment in Azure ML platform, Anaconda Enterprise, or AWS Sagemaker. Basic knowledge of deep learning algorithms such as MaskedCNN, YOLO, and familiarity with Visualization and analytics/Reporting Tools like Power BI, Tableau, and Alteryx will be considered advantageous for this role.,

What You'll Work On Develop state-of-the-art time series models for anomaly detection and forecasting in observability data. Design a root cause analysis system using LLMs, causal analysis, machine learning and anomaly detection algorithms. Develop Large Language Models for time series analysis Create highly scalable ML pipelines for real-time monitoring and alerting. Build and maintain ML Ops workflows for model deployment, evaluation, monitoring, and updates. Build frameworks to evaluate AI agents. Handle large datasets using Python and its ML ecosystem (e.g., NumPy, Pandas, Scikit-Learn, TensorFlow, PyTorch, Statsmodels). Use Bayesian methods, Granger causality, counterfactual analysis, and other techniques to derive meaningful system insights. Collaborate with other teams to deploy ML-driven observability solutions in production. What We're Looking For 5+ years of hands-on experience in Machine Learning, Time Series Analysis, and Causal Analytics. Bachelors degree in Computer Science, Mathematics or Statistics. Masters or PhD is a plus Strong proficiency in Python and libraries like Scikit-Learn, TensorFlow, PyTorch, Statsmodels, Prophet, or similar. Deep understanding of time-series modeling, forecasting, and anomaly detection techniques. Expertise in causal inference, Bayesian statistics, and causal graph modeling. Experience in ML Ops, model evaluation, and deployment in production environments. Working knowledge of databases and data processing frameworks (SQL, Spark, Dask, etc.). Experience in observability, monitoring, or AI-driven system diagnostics is a big plus. Background in AI Agent evaluation and optimization is a plus. Working with LLMs, fine-tuning LLMs, LLM Ops, LLM Agents is a big plus Our Values Loyalty & Long-term Commitment - We invest in people who invest in us. Opinionated yet Open-Minded - We value strong perspectives but encourage constructive discussions. Passion - We seek individuals who are passionate about their craft. Humility & Integrity - Honest, transparent, and accountable team members are key. Adaptability & Self-Sufficiency - Ability to thrive in a fast-paced and evolving environment. Build Fast and Break Fast - We believe in rapid iteration and learning from failures. What You'll Work On You will be instrumental in building the next-generation Observability platform for automated Root Cause Analysis using LLMs, Machine Learning algorithms. You will be innovating on building LLMs for time series analysis. You'll have the opportunity to work with an experienced team, gain deep insights into how startups are built, and be at the forefront of disruptive innovation in Observability. Comp - upto 2Cr+ (ref:hirist.tech)

At American Express, our culture is built on a 175-year history of innovation, shared values and Leadership Behaviors, and an unwavering commitment to back our customers, communities, and colleagues. As part of Team Amex, you'll experience this powerful backing with comprehensive support for your holistic well-being and many opportunities to learn new skills, develop as a leader, and grow your career. Here, your voice and ideas matter, your work makes an impact, and together, you will help us define the future of American Express. How will you make an impact in this role? This Position is in GSG Advanced Analytics team as part of GSG MIS COE, is looking for full time candidates as Data Science Analysts. The Advanced Analytics team works across multiple Data Science/Machine Learning portfolio of projects across GSG organization across multiple areas of Servicing. Understand the overall business perspective and help conceptualize the business problem into a Data Science/ML roadmap Have a research bend of mind and read/engage/apply new techniques and algorithms in the field to generate efficiencies/process improvements. Rigorous testing of algorithms as per business norms and delivering significant working leverage over status quo and generate value for the business. Capability of writing, debugging and compiling codes in multiple Machine Learning environment and understanding of Python stack is necessary Research focus on problem solving through NLP(Natural Language Processing) is critical. Clear application on performance testing and validation framework of machine learning models Understand and deploy mathematical foundations of cutting edge NLP techniques on varied sources of data Willingness to derive insights from terabyte sized data and capability to design scalable solutions is paramount Minimum Qualifications · Proven experience of applying using Machine Learning techniques like Regression, Classification, Supervised or Unsupervised Recommenders, Deep Learning etc. · Ability to work in cross functional teams · Excellent data wrangling and visualization skills · Hands on knowledge of SQL is expected · A research mindset with a zeal to experiment new algorithms is expected Preferred Qualifications: · Master’s in a quantitative field (e.g., Finance, Engineering, Mathematics, Statistics Computer Science or Economics) from a top institute. · A set of high impact research papers on applied NLP/ Deep Learning/ GenAI · Prior experience working with Transformers/LSTMs/CNNs preferred · Working knowledge of finetuning Large Language Models(LLMs) is a plus · Deep knowledge of Statistics and Maths and ability to dissect problems from the first principle. Exposure to fields like Linear Algebra, Bayesian Statistics, Group theory is desirable · Complete grip on Python environment and libraries (pandas, numpy, nltk, statsmodels, gensim, pyspark, spacy, transformers), Deep learning expertise is preferred any of Tensorflow/Torch. We back you with benefits that support your holistic well-being so you can be and deliver your best. This means caring for you and your loved ones' physical, financial, and mental health, as well as providing the flexibility you need to thrive personally and professionally: Competitive base salaries Bonus incentives Support for financial-well-being and retirement Comprehensive medical, dental, vision, life insurance, and disability benefits (depending on location) Flexible working model with hybrid, onsite or virtual arrangements depending on role and business need Generous paid parental leave policies (depending on your location) Free access to global on-site wellness centers staffed with nurses and doctors (depending on location) Free and confidential counseling support through our Healthy Minds program Career development and training opportunities American Express is an equal opportunity employer and makes employment decisions without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, veteran status, disability status, age, or any other status protected by law. Offer of employment with American Express is conditioned upon the successful completion of a background verification check, subject to applicable laws and regulations.

At American Express, our culture is built on a 175-year history of innovation, shared values and Leadership Behaviors, and an unwavering commitment to back our customers, communities, and colleagues. As part of Team Amex, you'll experience this powerful backing with comprehensive support for your holistic well-being and many opportunities to learn new skills, develop as a leader, and grow your career. Here, your voice and ideas matter, your work makes an impact, and together, you will help us define the future of American Express. How will you make an impact in this role? This Position is in GSG Advanced Analytics team as part of GSG MIS COE, is looking for full time candidates as Data Science Analysts. The Advanced Analytics team works across multiple Data Science/Machine Learning portfolio of projects across GSG organization across multiple areas of Servicing. Understand the overall business perspective and help conceptualize the business problem into a Data Science/ML roadmap Have a research bend of mind and read/engage/apply new techniques and algorithms in the field to generate efficiencies/process improvements. Rigorous testing of algorithms as per business norms and delivering significant working leverage over status quo and generate value for the business. Capability of writing, debugging and compiling codes in multiple Machine Learning environment and understanding of Python stack is necessary Research focus on problem solving through NLP(Natural Language Processing) is critical. Clear application on performance testing and validation framework of machine learning models Understand and deploy mathematical foundations of cutting edge NLP techniques on varied sources of data Willingness to derive insights from terabyte sized data and capability to design scalable solutions is paramount Minimum Qualifications Proven experience of applying using Machine Learning techniques like Regression, Classification, Supervised or Unsupervised Recommenders, Deep Learning etc. Ability to work in cross functional teams Excellent data wrangling and visualization skills Hands on knowledge of SQL is expected A research mindset with a zeal to experiment new algorithms is expected Preferred Qualifications: Master’s in a quantitative field (e.g., Finance, Engineering, Mathematics, Statistics Computer Science or Economics) from a top institute. A set of high impact research papers on applied NLP/ Deep Learning/ GenAI Prior experience working with Transformers/LSTMs/CNNs preferred Working knowledge of finetuning Large Language Models(LLMs) is a plus Deep knowledge of Statistics and Maths and ability to dissect problems from the first principle. Exposure to fields like Linear Algebra, Bayesian Statistics, Group theory is desirable Complete grip on Python environment and libraries (pandas, numpy, nltk, statsmodels, gensim, pyspark, spacy, transformers), Deep learning expertise is preferred any of Tensorflow/Torch. We back you with benefits that support your holistic well-being so you can be and deliver your best. This means caring for you and your loved ones' physical, financial, and mental health, as well as providing the flexibility you need to thrive personally and professionally: Competitive base salaries Bonus incentives Support for financial-well-being and retirement Comprehensive medical, dental, vision, life insurance, and disability benefits (depending on location) Flexible working model with hybrid, onsite or virtual arrangements depending on role and business need Generous paid parental leave policies (depending on your location) Free access to global on-site wellness centers staffed with nurses and doctors (depending on location) Free and confidential counseling support through our Healthy Minds program Career development and training opportunities American Express is an equal opportunity employer and makes employment decisions without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, veteran status, disability status, age, or any other status protected by law. Offer of employment with American Express is conditioned upon the successful completion of a background verification check, subject to applicable laws and regulations.

Role : AIML Engineer Location : Madurai/ Chennai Language: Python DBs : SQL Core Libraries: Time Series & Forecasting: pmdarima, statsmodels, Prophet, GluonTS, NeuralProphet SOTA ML : ML Models, Boosting & Ensemble models etc. Explainability : Shap / Lime Required skills: Deep Learning: PyTorch, PyTorch Forecasting, Data Processing: Pandas, NumPy, Polars (optional), PySpark Hyperparameter Tuning: Optuna, Amazon SageMaker Automatic Model Tuning Deployment & MLOps: Batch & Realtime with API endpoints, MLFlow Serving: TorchServe, Sagemaker endpoints / batch Containerization: Docker Orchestration & Pipelines: AWS Step Functions, AWS SageMaker Pipelines AWS Services: SageMaker (Training, Inference, Tuning) S3 (Data Storage) CloudWatch (Monitoring) Lambda (Trigger-based Inference) ECR, ECS or Fargate (Container Hosting)

Job Summary JD- Having a background in Retail will be a Big Plus. Advanced in Python: Proven experience with core libraries like pandas, numpy, scikit-learn, and matplotlib, plus advanced tools like statsmodels, xgboost, lightgbm, prophet, deep learning-based forecasting (e.g. Neural forecast). Advanced Forecasting Techniques: Experience with ensemble models, hierarchical forecasting, probabilistic forecasting, and multivariate time series. Pricing Models: Background in price elasticity modeling, good to have experience in optimization - at least one of the 2 resources Model Evaluation: Familiarity with time-series cross-validation, backtesting, and metrics such as MAE, MAPE, RMSE, SMAPE, and prediction intervals. SQL Proficiency: Ability to query and manage data from relational databases. Version Control: Comfortable working with Git/GitHub for collaboration and code management. Mandate skill- python and advanced forcesting skills with models like arima etc. Any shift- Second shift Location-Banglore

Job Summary JD- Having a background in Retail will be a Big Plus. Advanced in Python: Proven experience with core libraries like pandas, numpy, scikit-learn, and matplotlib, plus advanced tools like statsmodels, xgboost, lightgbm, prophet, deep learning-based forecasting (e.g. Neural forecast). Advanced Forecasting Techniques: Experience with ensemble models, hierarchical forecasting, probabilistic forecasting, and multivariate time series. Pricing Models: Background in price elasticity modeling, good to have experience in optimization - at least one of the 2 resources Model Evaluation: Familiarity with time-series cross-validation, backtesting, and metrics such as MAE, MAPE, RMSE, SMAPE, and prediction intervals. SQL Proficiency: Ability to query and manage data from relational databases. Version Control: Comfortable working with Git/GitHub for collaboration and code management. Mandate skill- python and advanced forcesting skills with models like arima etc. Any shift- Second shift Location-Banglore