1487 Data Scientist Jobs - Page 24

This position allows the successful incumbent to develop deep technical and broad commercial skills by being exposed to, and working on a wide variety of internal projects. Working as part of a large, sophisticated analytics team, this role will be required to: Manipulate and analyse data for the development and validation of predictive models in the areas of credit risk, demographics, marketing, fraud and ratings, in distributed computing environment Monitor Equifax s cutting edge scorecards and risk tools Create business case and analytic insight materials that show the value of predictive modelling and visualise the insights Conduct ad hoc queries such as bureau insights, testing solutions Lead small projects and quality check own and others outputs guide junior data scientists Maintain documentation that supports Analytics platform of databases, data products and analytical solutions. What you'll Do: Project Leadership / Mentoring Mentor Analysts through development process Driving a focus on learning so that the team benefits from your coaching and other learning events that contribute to improved performance. Develop and maintain a network of influence. Demonstrate leadership by example. Data Analysis Leading statistical and data analysis, sometimes as project team leader. Demonstrate analytic leadership in the approaches used and proactively provide technical guidance and support to analysts. Demonstrate a high level of skill in programming required to perform analysis such as demonstrated experience with SQL, R, Python and Tableau on Cloud environments such as GCP or equivalent. Process and analyse large volumes of data in the development of insights. Prepare documentation for all work, to ensure that an audit trail is sufficient for a colleague to be able to quality review and/or repeat your analysis. Quality check your own and other analyst work output to ensure error-free delivery of information and analysis. Develop extensive repertoire of analytical methodologies and techniques for investigating data relationships and insights Adhere to Equifax project management standards and effective use of project management resources (methodology, templates, time recording systems and project office). Product and Service Contributing to analytic roadmap, product development and innovation Develop a detailed understanding of the full product and service offering available through Equifax as we'll as the market dynamics and requirements within the data driven marketing space. Proactively use this understanding to work with the team and stakeholders to enhance and expand Equifax s data and insights assets. What experience you need BS degree in a STEM major or equivalent discipline 5-7 years of experience in a related analytical role Proven track record of designing and developing predictive models in real-world applications Experience with model performance evaluation and predictive model optimization for accuracy and efficiency Cloud certification strongly preferred Additional role-based certifications may be required depending upon region/BU requirements Process Improvement and Efficiencie Drive transition to more advanced modelling environments, utilising distributed computing and methodologies such as machine learning Demonstrate an understanding of business needs, making recommendations relating to new or improved data and insights assets. Supporting the other teams within the Analytics function by working with them to improve processes as needed. Systems and Processes Develop a detailed understanding of Equifax databases, data structures and core data analysis procedures, as we'll as maximising output through a Hadoop based file system. Develop understanding of best practice model management framework to ensure Equifax s models remain optimal in terms of performance and stability Develop familiarity with Equifax s documented project management methodology and resources (templates, time recording system, work scheduling etc). What could set you apart Passion for data science, data mining, machine learning and experience with big data architectures and methods A Masters degree in a quantitative field (Statistics, Mathematics, Economics) Cloud certification such as GCP strongly preferred Self Starter Excellent communicator / Client Facing Ability to work in fast paced environment Flexibility work across A/NZ time zones based on project needs

The Senior Data Scientist in the Interaction Insights team will help in generating actionable insights for driving the creation of fact-based research from client interactions and other Gartner internal and external data assets. At the core we are looking for a person who is passionate about learning new technologies, text analytics, digging into rows of unstructured data, drawing recommendations & actionable insights, and using creative ways to visualize & interpret it for research. This person will have a flair of innovation along with a strong experience in Python, Data Science, NLP, Machine Learning, Deep Learning, LLMs and the analysis of unstructured data. They would be working closely with various stakeholders to explore opportunities to optimize data mining techniques and improve the accuracy of insights generated using NLP or various types of Machine Learning/Deep Learning/LLM models. What you will do: Execute large-scale, high-impact data science projects, translating research objectives into actionable data and insights from both internal and external data assets Provide ad hoc modeling and analytical insights to inform strategic and operational initiatives Analyze unstructured text data to discover insights and patterns using advanced data science techniques, including machine learning (ML) and natural language processing (NLP) Interpret data-driven patterns and insights in alignment with original business objectives Address critical business challenges by leveraging data science, ML, and NLP methodologies Interact with internal and external stakeholders to refine and enhance findings Collaborate as part of a team in a fast-paced environment, meeting strict SLAs and turnaround times Develop a deep understanding of the technology industry and maintain expertise in the data science domain Ensure delivery of high-quality data science solutions with a focus on accuracy and coverage Be accountable for the scalability, stability, and business adoption of data science solutions Maintain proper documentation and adhere to code reusability and best practices Take ownership of algorithms, including their ongoing enhancement and optimization to meet evolving business requirements Stay current with advancements in AI/ML models and technologies, and apply disruptive data science solutions as appropriate. Collaborate with engineering and product teams to launch MVPs and iterate quickly based on feedback Independently plan, drive and execute data science projects that deliver clear and measurable business value What you will need: Education - masters in engineering, Computer Science, Computer Applications, Statistics, Mathematics, Applied Mathematics, Computer Science with focus on AI or Data Science; BE/BTech or Bachelors (Comp. Sc./AI) with relevant experience Total experience - 7 to 10 years of which 5+ yrs as hands-on Data Science, AI/ML experience on real-world industry problems, with focus on Text Mining and Natural Language Processing/text analytics Advanced proficiency in Python and SQL, with experience using key data science libraries and tools (eg, Pandas, Numpy, scikit-learn, TensorFlow, PyTorch, Spacy, NLTK, Scipy) Hands-on experience with machine learning, deep learning, NLP (including LLMs/GenAI), and applying these models to real-world business problems Strong background in data preparation, including cleaning, normalization, and handling unstructured text data for modeling Experience with cloud computing platforms such as AWS or Azure for model training, testing, and deployment Familiarity with both relational (eg, Oracle) and NoSQL databases (eg, MongoDB, graph databases), as we'll as distributed computing frameworks like Spark Proficiency in best coding practices and code/repo management using GitHub or Bitbucket Basic skills in Power BI, Excel, and PowerPoint Strong analytical, critical thinking, and problem-solving skills, with the ability to extract insights from complex and unstructured datasets Demonstrated ability to collaborate across product, engineering, and data science teams, and to influence stakeholders at all levels Excellent communication skills in both technical and business contexts Self-motivated, eager to learn, adaptable to feedback, and comfortable working in a fast-paced, milestone-driven environment What you will get: Competitive salary, generous paid time off policy, charity match program, Group Medical Insurance, Parental Leave, Employee Assistance Program (EAP) and more! Collaborative, team-oriented culture that embraces diversity Professional development and unlimited growth opportunities

The Client Services BI & Analytics team strives to create an open, trusting data culture where the cost of curiosity - the number of steps, amount of time, and complexity of effort needed to use operational data to derive insights - is as low as possible. We govern Client Services operational data and metrics, create easily usable dashboards and data sources, and analyze data to share insights. We are a part of the Client Services Global Business Operations function and work with all levels of stakeholders, from executive leaders sharing insights with the C-Suite to customer-facing colleagues who rely on our assets to incorporate data into their daily responsibilities. This specialist role makes data available from new sources, builds robust data models, creates and optimizes data enrichment pipelines, and provides engineering support to specific projects. You will partner with our Data Visualizers and Solution Designers to ensure that data needed by the business is available and accurate and to develop certified data sets. This technical lead and architect role is a force multiplier to our Visualizers, Analysts, and other data users across Client Services. Responsibilities Design, develop, and maintain scalable data pipelines and systems. Monitor and troubleshoot data pipeline issues to ensure seamless data flow. Establish data processes and automation based on business and technology requirements, leveraging Visa s supported data platforms and tools Deliver small to large data engineering and Machine learning projects either individually or as part of a project team Setup ML Ops pipelines to Productionalize ML models and setting up Gen AI pipelines Collaborate with cross-functional teams to understand data requirements and ensure data quality, with a focus on implementing data validation and data quality checks at various stages of the pipeline Provide expertise in data warehousing, ETL, and data modeling to support data-driven decision making, with a strong understanding of best practices in data pipeline design and performance optimization Extract and manipulate large datasets using standard tools such as Hadoop (Hive), Spark, Python (pandas, NumPy), Presto, and SQL Develop data solutions using Agile principles Provide ongoing production support Communicate complex concepts in a clear and effective manner Stay up to date with the latest data engineering trends and technologies to ensure the companys data infrastructure is always state-of-the-art, with an understanding of best practices in cloud-based data engineering This is a remote position. A remote position does not require job duties be performed within proximity of a Visa office location. Remote positions may be required to be present at a Visa office with scheduled notice. Basic Qualifications -2 or more years of work experience with a Bachelor s Degree or an Advanced Degree (e.g. Masters, MBA, JD, MD, or PhD) Preferred Qualifications -3 or more years of work experience with a Bachelor s Degree or more than 2 years of work experience with an Advanced Degree (e.g. Masters, MBA, JD, MD) -3+ years of work experience with a bachelor s degree in the STEM field. -Strong experience with SQL, Python, Hadoop, Spark, Hive, Airflow and MPP data bases -5+ years of analytics experience with a focus on data Engineering and AI -Experience with both traditional data warehousing tools and techniques (such as SSIS, ODI, and on-prem SQL Server, Oracle) as well as modern technologies (such as Hadoop, Denodo, Spark, Airflow, and Python), and a solid understanding of best practices in data engineering -Advanced knowledge of SQL (e.g., understands subqueries, self-joining tables, stored procedures, can read an execution plan, SQL tuning, etc.) -Solid understanding of best practices in data warehousing, ETL, data modeling, and data architecture. -Experience with NoSQL databases (e.g., MongoDB, Cassandra) -Experience with cloud-based data warehousing and data pipeline management (AWS, GCP, Azure) -Experience in Python, Spark, and exposure to scheduling tools like Tuber/Airflow is preferred. -Able to create data dictionaries, setup and monitor data validation alerts, and execute periodic jobs to maintain data pipelines for completed projects -Experience with visualization software (e.g., Tableau, QlikView, PowerBI) is a plus. -A team player and collaborator, able to work well with a diverse group of individuals in a matrixed environment

F2F Weekend Drive - Bangalore- 14th June - DS Gen AI Job description We are having a F2F weekend drive for the requirement of a Data Scientist + Gen AI at our LTIM Bangalore Whitefield office. Date - 14th June 2025 Experience - 6+ Years Mandatory Skills - Data Science, Gen AI, Python, RAG and Azure/AWS, AI/ML, NLPt Location - LTIMindtree Bangalore Whitefield Office Secondary - (Any) Machine Learning, Deep Learning, ChatGPT, Langchain, Prompt, vector stores, RAG, llama, Computer vision, Deep learning, Machine learning, OCR, Transformer, regression, forecasting, classification, hyper parameter tunning, MLOps, Inference, Model training, Model Deployment Generic JD- More than 6 years of experience in Data Engineering, Data Science and AI / ML domain Excellent understanding of machine learning techniques and algorithms, such as GPTs, CNN, RNN, k-NN, Naive Bayes, SVM, Decision Forests, etc. Experience using business intelligence tools (e.g. Tableau, PowerBI) and data frameworks (e.g. Hadoop) Experience in Cloud native skills. Knowledge of SQL and Python; familiarity with Scala, Java or C++ is an asset Analytical mind and business acumen and Strong math skills (e.g. statistics, algebra) Experience with common data science toolkits, such as TensorFlow, KERAs, PyTorch, PANDAs, Microsoft CNTK, NumPy etc. Deep expertise in at least one of these is highly desirable. Experience with NLP, NLG and Large Language Models like BERT, LLaMa, LaMDA, GPT, BLOOM, PaLM, DALL-E, etc. Great communication and presentation skills. Should have experience in working in a fast-paced team culture. Experience with AIML and Big Data technologies like AWS SageMaker, Azure Cognitive Services, Google Colab, Jupyter Notebook, Hadoop, PySpark, HIVE, AWS EMR etc. Experience with NoSQL databases, such as MongoDB, Cassandra, HBase, Vector databases Good understanding of applied statistics skills, such as distributions, statistical testing, regression, etc. Should be a data-oriented person with analytical mind and business acumen.

Application Deadline: 21 June 2025 Title Senior Analyst- Data Scientist Department Data Value Location Gurgaon Reports To Suman Kaur Level 3 We re proud to have been helping our clients build better financial futures for over 50 years. How have we achieved this? By working together - and supporting each other - all over the world. So, join our Data Value team and feel like you re part of something bigger. About your team Data Value team drives the renewed focus of extracting value from Fidelity s data for business and client insights and working as one voice with the business, technology, and data teams. The team s vision is to create measurable business impact by leveraging technology and utilising the skills to generate valuable insights and streamline engagements. The Data Science function within Data Value supports Fidelity International s Sales, Marketing, Propositions, Risk, Finance, Customer Service and HR teams across the globe. The key objectives of the function are: To develop deep customer insights for our businesses helping them segment and target customers more effectively To develop a fact-based understanding of sales trends and identify actionable sales growth opportunities for each of our sales channels To understand customer preferences in terms of products, service attributes and marketing activity to help refine each of these To help develop new services lines e.g. develop customer analytics for key IFAs, DC Clients, Individual clients etc. To develop market and competitive intelligence in our key markets to help shape our business planning in those markets The function works directly with business heads and other senior stakeholder s stakeholders to identify areas of analytics, define problem statements and develop key insights. About your role You will be expected to take a leading role in developing the Data Science and Advanced Analytics solutions for our business. This will involve: Engaging with the key stakeholders to understand Fidelity s sales, marketing, client services and propositions context Implement advanced analytics solutions on On-Premises/Cloud platforms, develop proof-of-concepts and engage with internal and external ecosystem to progress the proof of concepts to production. Engaging and collaborating with different other internal teams like Data engineering, DevOps, technology team etc for development of new tools, capabilities, and solutions. Maximize Adoption of Cloud Based advanced analytics solutions: Build out sandbox analytics environments using Snowflake, AWS, Adobe, Salesforce. About you Key Responsibilities Developing and Delivering Data Science solutions for business (40%) Partner with internal (FIL teams) & external ecosystem to design and deliver advanced analytics enabled Data Science solutions Create advanced analytics solution on quantitative and text data using Artificial Intelligence, Machine Learning and NLP techniques. Create compelling visualisations that enable the smooth consumption of predictions and insights for customer benefit . Stakeholder Management (30%) Works with channel heads/stakeholders and other sponsors understand the business problem and translate it into appropriate analytics solution. Engages with key stakeholders for smooth execution, delivery, and implementation of solutions Adoption of Cloud enabled Data Science solutions: (20%) Maximize Adoption of Cloud Based advanced analytics solution Build out sandbox analytics environments using Snowflake, AWS, Adobe, Salesforce Deploy solutions in productions while adhering to best practices involving Model Explainability, MLOps, Feature Stores, Model Management, Responsible AI etc Collaboration and Ownership (10%) Sharing of knowledge, best practices with the team including coaching or training in some of deep learning/machine learning methodologies. Provides mentoring, coaching, and consulting advice and guidance to staff, e.g. analytic methodologies, data recommendations Takes complete independent ownership of the projects and the initiatives in the team with the minimal support Experience and Qualifications Required Qualifications: Engineer from IIT/Master s in field related to Data Science/Economics/Mathematics (Tie1 Institutions like ISI, Delhi School of Economics)/M.B.A from tier 1 institutions Must have Skills & Experience Required: Overall, 8+ years of experience in Data Science and Analytics 5+ years of hands-on experience in - Statistical Modelling /Machine Learning Techniques/Natural Language Processing/Deep Learning 5+ years of experience in Python/Machine Learning/Deep Learning Excellent problem-solving skills Should be able to run analytics applications such as Python, SAS and interpret statistical results Implementation of models with clear measurable outcomes Good to have Skills & Experience Required: Ability to engage in discussion with senior stakeholders on defining business problems, designing analyses projects, and articulating analytical insights to stakeholders. Experience on SPARK/Hadoop/Big Data Platforms is a plus Experience with unstructured data and big data Experience with secondary data and knowledge of primary market research is a plus. Ability to independently own and manage the projects with minimal support. Excellent analytical skills and a strong sense for structure and logic Ability to develop, test and validate hypotheses. Feel rewarded

Job Summary What you need to know about the role Each Data Scientist on this team has full ownership of a portfolio of a product and is responsible for end-to-end management of loss and decline rates. Day-to-day duties include data analysis, monitoring and forecasting, creating the logic for and implementing risk rules and strategies, providing requirements to data scientists and technology teams on attribute, model and platform requirements, and communicating with global stakeholders to ensure we deliver the best possible customer experience while meeting loss rate targets. Meet our team PayPals Global Fraud Protection team is responsible for partnering with global business units to manage a variety of risk of various types, including identity fraud, account takeover, stolen financial fraud, and credit issues. This is an exciting department that plays an important role in contributing PayPals bottom line financial savings, ensuring safe and secure global business growth, and delivering the best customer experience. This open opportunity is within the Large Merchant and Markets Fraud Risk team. This portfolio is comprised of PayPal s newest leading-edge payments solutions, such as Risk-as-Service, Fastlane, PayPal Complete Payments, etc. as well as customized experiences developed for the company s highest-priority strategic Markets and Partnerships. Job Description Your way to impact You will be the Data Scientist in the Fraud Risk team , where you will work on leading new projects to build and improve the Risk strategies to prevent fraud using the Risk tooled and custom data & AL/ML models. In this position, you will be partnering with the corresponding Business Units to align with and influence their strategic priorities, educate business partners about Risk management principles, and collaboratively optimize the Risk treatments and experiences for these unique products and partners. Your day to day In your day to day role you will - In this role you will have full ownership of a portfolio of merchants and is responsible for end-to-end management of loss and decline rates. Collaborate with different teams to develop strategies for fraud prevention, loss savings, and optimize transaction declines or improve customer friction. You will work together with cross-functional teams to deliver solutions and providing Risk analytics on frustration trend/ KPIs monitoring or alerting for fraud events. These solutions will adapt PayPal s advanced proprietary fraud prevention tools enabling business growth. What do you need to bring- 2-4 years of relevant experience working with large-scale complex dataset. Strong analytical mindset, ability to decompose business requirements into an analytical plan, and execute the plan to answer those business questions Excellent communication skills, equally adept at working with engineers as well as business leaders Want to build new solutions and invent new approaches to big, ambiguous, critical problems Strong working knowledge of Excel, SQL and Python/R Technical Proficiency Exploratory Data Analysis and expertise in preparing a clean and structured data for model development. Experience in applying AI/ML techniques for business decisioning including supervised and unsupervised learning (e.g., regression, classification, clustering, decision trees, anomaly detection, etc.). Knowledge of model evaluation techniques such as Precision, Recall, ROC-AUC Curve, etc. along with basic statistical concepts. Preferred Qualification Subsidiary PayPal Travel Percent 0 For the majority of employees, PayPals balanced hybrid work model offers 3 days in the office for effective in-person collaboration and 2 days at your choice of either the PayPal office or your home workspace, ensuring that you equally have the benefits and conveniences of both locations. Our Benefits We have great benefits including a flexible work environment, employee shares options, health and life insurance and more. To learn more about our benefits please visit https//www.paypalbenefits.com . Who We Are Click Here to learn more about our culture and community. Commitment to Diversity and Inclusion PayPal provides equal employment opportunity (EEO) to all persons regardless of age, color, national origin, citizenship status, physical or mental disability, race, religion, creed, gender, sex, pregnancy, sexual orientation, gender identity and/or expression, genetic information, marital status, status with regard to public assistance, veteran status, or any other characteristic protected by federal, state, or local law. In addition, PayPal will provide reasonable accommodations for qualified individuals with disabilities. . Belonging at PayPal Our employees are central to advancing our mission, and we strive to create an environment where everyone can do their best work with a sense of purpose and belonging. Belonging at PayPal means creating a workplace with a sense of acceptance and security where all employees feel included and valued. We are proud to have a diverse workforce reflective of the merchants, consumers, and communities that we serve, and we continue to take tangible actions to cultivate inclusivity and belonging at PayPal. Any general requests for consideration of your skills, please Join our Talent Community . We know the confidence gap and imposter syndrome can get in the way of meeting spectacular candidates. Please don t hesitate to apply.

About Amazon Regulatory Intelligence, Safety, and Compliance (RISC). Amazon RISC s vision is to make Amazon the Earth s most trusted shopping destination for safe and compliant products. Towards this mission, we take a science-first approach to building technology, products and services, that protect customers from unsafe, illegal, controversial, or policy-violating products while offering the optimal selling partner experience. Job Summary We are seeking an exceptional Data Scientist to join a team of experts in the field of AI/ML, and work together to tackle challenging business problems across diverse compliance domains. We leverage and train state-of-the-art multi-modal, large-language-models (LLMs), and vision language models (VLMs) to detect illegal and unsafe products across the Amazon catalog. We work on machine learning problems for generative AI, agentic system, multi-modal classification, intent detection, information retrieval, anomaly and fraud detection. This is an exciting and challenging position to deliver scientific innovations into production systems at Amazon-scale to make immediate, meaningful customer impacts while also pursuing ambitious, long-term research. You will work in a highly collaborative environment where you can analyze and process large amounts of images, texts, documents, and tabular data. You will work on hard science problems that have not been solved before, conduct rapid prototyping to validate your hypothesis, and deploy your algorithmic ideas at scale. There will be something new to learn every day as we work in an environment with rapidly evolving regulations and adversarial actors looking to outwit your best ideas. Design and evaluate state-of-the-art algorithms and approaches in generative AI, agentic system, multi-modal classification, intent detection, information retrieval, anomaly and fraud detection. Translate product and CX requirements into measurable science problems and metrics. Collaborate with product and tech partners and customers to validate hypothesis, drive adoption, and increase business impact Key author in writing high quality scientific papers in internal and external peer-reviewed conferences. A day in the life Understanding customer problems, project timelines, and team/project mechanisms Proposing science formulations and brainstorming ideas with team to solve business problems Writing code, and running experiments with re-usable science libraries Reviewing labels and audit results with investigators and operations associates Sharing science results with science, product and tech partners and customers Writing science papers for submission to peer-review venues, and reviewing science papers from other scientists in the team. Contributing to team retrospectives for continuous improvements Driving science research collaborations and attending study groups with scientists across Amazon About the team We are a team of scientists and engineers building AI/ML solutions to make Amazon the Earth s most trusted shopping destination for safe and compliant products. PhD, or Masters degree with 2+ years of machine learning experience, or bachelor degree with 3+ years of machine learning experience Experience programming in Python, Java, C++, or related language Experience with neural deep learning methods, LLM, and natural language processing Experience with conducting research in a corporate setting Experience with large scale machine learning systems such as profiling and debugging and understanding of system performance and scalability

We are seeking an exceptional Data Scientist to join a team of experts in the field of machine learning, and work together to tackle challenging problems across diverse compliance domains. We leverage risk models (including boosted trees and graph neural networks) as well as vision and large-language-models (LLMs) to detect illegal and unsafe products across the Amazon catalog. We work on machine learning problems for multi-modal classification, intent detection, information retrieval, anomaly and fraud detection, and generative AI. This is an exciting and challenging position to deliver scientific innovations into production systems at Amazon-scale to make immediate, meaningful customer impacts while also pursuing ambitious, long-term research. You will work in a highly collaborative environment where you can analyze and process large amounts of image, text and tabular data. You will work on hard science problems that have not been solved before, conduct rapid prototyping to validate your hypothesis, and deploy your algorithmic ideas at scale. There will be something new to learn every day as we work in an environment with rapidly evolving regulations and adversarial actors looking to outwit your best ideas. Explore and evaluate state-of-the-art algorithms and approaches in risk modeling and vision/language models Translate product and CX requirements into measurable science problems and metrics. Collaborate with product and tech partners and customers to validate hypothesis, drive adoption, and increase business impact Evaluate model performance in production and refresh/implement necessary updates to maintain optimal system performance. A day in the life Understanding customer problems, project timelines, and team/project mechanisms Proposing science formulations and brainstorming ideas with team to solve business problems Writing code, and running experiments with re-usable science libraries Reviewing labels and audit results with investigators and operations associates Sharing science results with science, product and tech partners and customers Contributing to team retrospectives for continuous improvements Participating in science research collaborations and attending study groups with scientists across Amazon About the team We are a team of scientists building AI/ML solutions to make Amazon Earth s most trusted shopping destination for safe and compliant products. 2+ years of data scientist experience 3+ years of data querying languages (e.g. SQL), scripting languages (e.g. Python) or statistical/mathematical software (e.g. R, SAS, Matlab, etc.) experience 3+ years of machine learning/statistical modeling data analysis tools and techniques, and parameters that affect their performance experience Experience applying theoretical models in an applied environment Knowledge of relevant statistical measures such as confidence intervals, significance of error measurements, development and evaluation data sets, etc. Experience in Python, Perl, or another scripting language Experience in a ML or data scientist role with a large technology company

We are seeking an exceptional Data Scientist to join a team of experts in the field of machine learning, and work together to tackle challenging problems across diverse compliance domains. We leverage multi-modal and large-language-models (LLMs) to detect illegal and unsafe products across the Amazon catalog. We work on machine learning problems for multi-modal classification, intent detection, information retrieval, anomaly and fraud detection, and generative AI. This is an exciting and challenging position to deliver scientific innovations into production systems at Amazon-scale to make immediate, meaningful customer impacts while also pursuing ambitious, long-term research. You will work in a highly collaborative environment where you can analyze and process large amounts of image, text and tabular data. You will work on hard science problems that have not been solved before, conduct rapid prototyping to validate your hypothesis, and deploy your algorithmic ideas at scale. There will be something new to learn every day as we work in an environment with rapidly evolving regulations and adversarial actors looking to outwit your best ideas. Explore and evaluate state-of-the-art algorithms and approaches in multi-modal classification, large language models (LLMs), intent detection, information retrieval, anomaly and fraud detection, and generative AI Translate product and CX requirements into measurable science problems and metrics. Collaborate with product and tech partners and customers to validate hypothesis, drive adoption, and increase business impact A day in the life Understanding customer problems, project timelines, and team/project mechanisms Proposing science formulations and brainstorming ideas with team to solve business problems Writing code, and running experiments with re-usable science libraries Reviewing labels and audit results with investigators and operations associates Sharing science results with science, product and tech partners and customers Contributing to team retrospectives for continuous improvements Participating in science research collaborations and attending study groups with scientists across Amazon About the team We are a team of scientists building AI/ML solutions to make Amazon Earth s most trusted shopping destination for safe and compliant products. 2+ years of data scientist experience 2+ years of data querying languages (e.g. SQL), scripting languages (e.g. Python) or statistical/mathematical software (e.g. R, SAS, Matlab, etc.) experience 2+ years of machine learning/statistical modeling data analysis tools and techniques, and parameters that affect their performance experience Experience applying theoretical models in an applied environment Knowledge of relevant statistical measures such as confidence intervals, significance of error measurements, development and evaluation data sets, etc. Experience in Python, Perl, or another scripting language Experience in a ML or data scientist role with a large technology company

At Globant, we are working to make the world a better place, one step at a time. We enhance business development and enterprise solutions to prepare them for a digital future. With a diverse and talented team present in more than 30 countries, we are strategic partners to leading global companies in their business process transformation. We seek a Data Scientist Senior-Level (Senior) who shares our passion for innovation and change. This role is critical to helping our business partners evolve and adapt to consumers personalized expectations in this new technological era. What will help you succeed: AI/Gen AI + LLM/RAG/Langchain Machine Learning Python AWS AI/ML services - especially Bedrock, SageMaker, Lambda This job can be filled in Pune location. Create with us digital products that people love. We will bring businesses and consumers together through AI technology and creativity, driving digital transformation to impact the world positively. We may use AI and machine learning technologies in our recruitment process. Globant is an Equal Opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, disability, veteran status, or any other characteristic protected by applicable federal, state, or local law. Globant is also committed to providing reasonable accommodations for qualified individuals with disabilities in our job application procedures. If you need assistance or an accommodation due to a disability, please let your recruiter know. Final compensation offered is based on multiple factors such as the specific role, hiring location, as well as individual skills, experience, and qualifications. In addition to competitive salaries, we offer a comprehensive benefits package. Learn more about life at Globant here: Globant Experience Guide .

Senior Data Scientist - S&A Now, more than ever, the Toast team is committed to our customers. We re taking steps to help restaurants navigate these unprecedented times with technology, resources, and community. We focus on building the restaurant platform that helps restaurants adapt, take control, and get back to what they do best: building the businesses they love. And because our technology is purpose-built for restaurants, by restaurant people, restaurants can trust that we ll deliver on their needs for today while investing in experiences that will power their restaurant of the future. Bready* to make a change? As the Senior Data Scientist in our Bangalore Data Science team, you will contribute to building machine learning algorithms using our huge reservoir of point of sale transaction data. You will work with architects, engineers and product managers to solve business and customer problems and turn machine learning models into business impact across product lines, including financial processing and fraud. About this Roll* : Design, build, train and evaluate machine learning models to drive business value for Toast and our restaurant customers Collaborate closely with internal and external product stakeholders, both technical and non-technical and help translate deep machine learning knowledge to product applications Break down larger ML initiatives into smaller problems that enables data science to deliver incremental business value and lead the team to execute on them Work closely with Production Engineering and Data Platform teams to deploy models to production and regularly monitor for efficiency, key KPIs and enhance them as needed Work with incident response and problem resolution teams to check and resolve any problems/challenges as and when identified in the model deployed in the production Effectively document all steps and manage code repositories for easy scalability and knowledge sharing with the the team Incorporate up-to-date ML technology and DS approach as best practice for the team Help in continuing to build out and expand the Data Science and ML Engineering teams Work effectively in a dynamic, changing environment while focusing on key goals and objectives Do you have the right ingredients* ? Advanced degree in Data Science, Statistics, Applied Math, Computer Science, Engineering or other equivalent quantitative disciplines 6 + years of industry experience in the field of Data Science and Machine Learning Experience in time series modelling. Familiarity with ARIMA, SARIMA, ETS, VAR models. Familiarity with forecasting tools like Facebook Prophet, GluonTS, or NeuralProphet. Strong proficiency in Python and SQL; experience with some of the following languages, tools, and frameworks: R, Spark, Scala, scikit-learn, Tensorflow, PyTorch, etc. Familiarity with standard software engineering practices and tools including object-oriented programming, test-driven development, CI/CD, git, shell scripting, task orchestration (Airflow, Luigi, etc.) and preferably AWS tooling (Sagemaker, DynamoDB, ECS, etc.) Strong knowledge of underlying mathematical foundations of statistics and machine learning Prior success deploying machine learning solutions in large-scale production environments Experience collaborating with cross-functional teams and stakeholders to evaluate new Machine Learning opportunities Problem solver who loves to dig into different kinds of data and can communicate their findings to cross-functional stakeholders Bonus ingredients* : Passion for research and curiosity that calls you to go beyond good enough to create something innovative and exciting Diversity, Equity, and Inclusion is Baked into our Recipe for Success At Toast, our employees are our secret ingredient when they thrive, we thrive. The restaurant industry is one of the most diverse, and we embrace that diversity with authenticity, inclusivity, respect, and humility. By embedding these principles into our culture and design, we create equitable opportunities for all and raise the bar in delivering exceptional experiences. We Thrive Together We embrace a hybrid work model that fosters in-person collaboration while valuing individual needs. Our goal is to build a strong culture of connection as we work together to empower the restaurant community. To learn more about how we work globally and regionally, check out: https: / / careers.toasttab.com / locations-toast . Apply today! Toast is committed to creating an accessible and inclusive hiring process. As part of this commitment, we strive to provide reasonable accommodations for persons with disabilities to enable them to access the hiring process. If you need an accommodation to access the job application or interview process, please contact . ------ For roles in the United States, It is unlawful in Massachusetts to require or administer a lie detector test as a condition of employment or continued employment. An employer who violates this law shall be subject to criminal penalties and civil liability.

We are looking for an experienced AI ML Developers experience in data science specializing in machine learning python statistical modelling and big data technologies pyspark sql. The ideal candidate will have a strong background in developing and deploying machine learning models optimizing ML pipelines and handling largescale structured and unstructured data to drive business impact. Deep understanding of supervised and unsupervised learning including regression classification Multiclass classification clustering and NLP Proficiency in statistical analysis AB testing and causal inference techniques Experience with model deployment and MLOps in cloud environments AWS GCP Key Responsibilities Develop and deploy machine learning models and predictive analytics solutions for business impact Work with largescale structured and unstructured data to extract insights and build scalable models Design implement and optimize ML pipelines for realtime and batch processing Collaborate with engineering product and business stakeholders to translate business problems into data science solutions Apply statistical modeling AB testing and causal inference techniques to evaluate business performance Apply machine learning and statistical techniques for audience segmentation helping to identify patterns and optimise business strategies Drive research and innovation by staying updated with cuttingedge MLAI advancements and incorporating them into our solutions Optimize data science models for performance scalability and interpretability in production environments Mentor junior data scientists and contribute to best practices in data science and engineering

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

Associate Scientist - Data Sourcing & Solutions Gurgaon/Bangalore, India AXA XL recognises data and information as critical business assets, both in terms of managing risk and enabling new business opportunities This data should not only be high quality, but also actionable - enabling AXA XLs executive leadership team to maximise benefits and facilitate sustained enterprise advantage Our Innovation, Data, and Analytics Office (IDA) is focused on driving innovation by optimizing how we leverage data to drive strategy and create a new business model - disrupting the insurance market As we develop an enterprise-wide data and digital strategy that moves us toward a greater focus on the use of data and data-driven insights, we are seeking an Associate Scientist for our Data Sourcing & Solutions team The role sits across the IDA Department to make sure customer requirements are properly captured and transformed into actionable data specifications Success in the role will require a focus on proactive management of the sourcing and management of data from source through usage What you ll be DOING What will your essential responsibilities include? Accountable for documenting data requirements (Business and Function Requirements) and assessing the reusability of Axiom assets Build processes to simplify and expedite data sourcing to focus on delivering data to AXA XL business stakeholders frequently Develops and operationalizes strategic data products, and answers and proactively manages the sourcing and management of data from source through usage (reusable Policy and Claim Domain data assets) Data Validation Testing of the data products in partnership with the AXA XL business to ensure the accuracy of the data and validation of the requirements Assesses all data required as part of the Data Ecosystem to make sure data has a single version of the truth Respond to ad-hoc data requests to support AXA XLs business Instill a customer-first attitude, prioritizing service for our business stakeholders above all else Internalize and execute IDA and company-wide goals to become a data-driven organization Contribute to best practices and standards to make sure there is a consistent and efficient approach to capturing business requirements and translating them into functional, non-functional, and semantic specifications Develop a comprehensive understanding of the data and our customers Drive root cause analysis for identified data deficiencies within reusable data assets delivered via IDA Identify solution options to improve the consistency, accuracy, and quality of data when captured at its source You will report to the Team Lead - Data Sourcing & Solutions What you will BRING We re looking for someone who has these abilities and skills: Required Skills and Abilities: Experience in a data role (business analyst, data analyst, analytics) preferably in the Insurance industry and within a data division A minimum of a bachelor s or masters degree (preferred) in a relevant discipline Robust SQL knowledge and technical ability to query AXA XL data sources to understand our data Excellent presentation, communication (oral & written), and relationship-building skills, across all levels of management and customer interaction Insurance experience in data, underwriting, claims, and/or operations, including influencing, collaborating, and leading efforts in complex, disparate, and interrelated teams with competing priorities Passion for data and experience working within a data-driven organization Work together internal data with external industry data to deliver holistic answers Work with unstructured data to unlock information needed by the business to create unique products for the insurance industry Possesses robust exploratory analysis skills and high intellectual curiosity Displays exceptional organizational skills and is detail-oriented The robust conceptual thinker who connects dots, and has critical thinking, and analytical skills Desired Skills and Abilities: Ability to work with team members across the globe and departments Ability to take ownership, work under pressure, and meet deadlines Builds trust and rapport within and across groups Applies in-depth knowledge of business and specialized areas to solve business problems and understand integration challenges and long-term impact creatively and strategically Ability to manage data needs of an individual project(s) while being able to understand the broader enterprise data perspective Expected to recommend innovation and improvement to policies, and procedures, deploying resources, and performing core activities Experience with SQL Server, Azure Databricks Notebook, Qlikview, PowerBI, and Jira/Confluence a plus

Position: Data Scientist Location: Trivandrum Job Description : We are urgently looking for a motivated Data Scientist with a focus on Computer Vision and Machine Learning. The candidate will have a passion for solving complex problems using deep learning, image processing, and AI-driven techniques. He shall work closely with a team of data scientists, engineers, etc and to build, optimize, and deploy machine learning models for real-world applications Key Responsibilities : Develop, train, and optimize deep learning models for image classification, object detection, segmentation, and other computer vision tasks. Implement and fine-tune machine learning algorithms for structured and unstructured data analysis. Preprocess and augment image/video datasets to improve model accuracy and robustness. Work with frameworks such as YOLO, TensorFlow, PyTorch, and OpenCV to build scalable models. Assist in deploying models to production environments, including cloud and edge computing platforms. Collaborate with cross-functional teams to integrate AI solutions into existing workflows and products. Stay up-to-date with the latest research and trends in AI, computer vision, and machine learning. Qualifications : Bachelors or masters degree in computer science, Data Science, AI/ML, or a related field. Minimum of 3 year of professional experience in Python programming and AI/ML integrations Solid understanding of machine learning concepts, neural networks, and deep learning architectures. Hands-on experience in training and optimizing computer vision models. Familiarity with data preprocessing techniques, image annotation tools, and model evaluation metrics. Strong problem-solving skills and the ability to work in a fast-paced environment. Joining: Immediate to less than 30 days Budget: 13 - 14 LPA ",

Key Responsibilities: Design, build, and maintain robust and scalable data pipelines to support analytics and reporting needs. Manage and optimize data lake architectures, with a focus on Apache Atlas for metadata management, data lineage, and governance. Integrate and curate data from multiple structured and unstructured sources to enable advanced analytics. Collaborate with data scientists and business analysts to ensure availability of clean, well-structured data. Implement data quality, validation, and monitoring processes across data pipelines. Develop and manage Power BI datasets and data models, supporting dashboard and report creation. Support data cataloging and classification using Apache Atlas for enterprise-wide discoverability and compliance. Ensure adherence to data security, privacy, and compliance policies.

#Jobs Team is looking for resources with a data analytics and data science background. Expert SQL skills.From the Data Science side must be able to write open source data models (not from scratch) but be able to talk through the process. SKILLS REQUIRED: 1. SQL skills must be strong. 2. Create Data Science operating models. 3. must have experience with Looker or Tableau. (Both are preferable) IDEAL CANDIDATE: SQL/Tableau/looker and building forecasting and open so

At McCormick, we bring our passion for flavor to work each day. We encourage growth, respect everyones contributions and do whats right for our business, our people, our communities and our planet. Join us on our quest to make every meal and moment better. Founded in Baltimore, MD in 1889 in a room and a cellar by 25-year-old Willoughby McCormick with three employees, McCormick is a global leader in flavour. With over 14,000 employees around the world and more than $6 Billion in annual sales, the Company manufactures, markets, and distributes spices, seasoning mixes, condiments and other flavourful products to the entire food industry, retail outlets, food manufactures, food service businesses and consumers. While our global headquarters are in the Baltimore, Maryland, USA area, McCormick operates and serves customers from nearly 60 locations in 25 countries and 170 markets in Asia-Pacific, China, Europe, Middle East and Africa, and the Americas. At McCormick, we have over a 100-year legacy based on our Power of People principle. This principle fosters an unusually dedicated workforce requiring a culture of respect, recognition, inclusion and collaboration based on the highest ethical values. Position Overview Provide the business with analytic tools and insights that drive growth and/or productivity. Provide technical leadership for analytics community via forward thinking attitude, use of cutting-edge tools and approaches and business consulting. Individual should help shape business and analytics strategies for our business units globally. Key Responsibilities Bringing new tools to the business; leading data mining and analytics, interpreting and reporting of large integrated data sets built with structured and unstructured data; developing tools to leverage new proprietary data sources. Statistical model building and deployment in the areas of forecasting, marketing mix, machine learning/AI, etc. Continuously seeking out industry best practices and skills development to create new capabilities for data analytics at McCormick to drive marketing strategy. May include managing/coaching direct reports to enable responsibilities above. Required Qualifications & Experience Bachelor s or Master s degree in Mathematics, Statistics, Engineering or Data Analytics/Science, or closely related field. Demonstrated skills and results in analyzing complex datasets, generating insights and building robust statistical models; Demonstrated sound understanding of concepts, principles and practices in Marketing and Sales and a working knowledge of practices in other areas including Finance and Supply Chain. Demonstrated ability to connect the dots between complex data/analytics and business understanding. Expertise in data management, integration & harmonization. Expertise in SQL, coding in one or more languages (R & Python preferred) Experience with data visualization software (Tableau preferred) Comfortable working with structured and unstructured data sources, including syndicated data, SAP Strong technical curiosity and passion for problem solving and innovation Interpersonal Skills Strong global cross-functional leadership, influence, communication and teamwork skills. Ability to manage multiple priorities simultaneously and foresee and address issues before they become significant obstacles WHY WORK AT MCCORMICK? United by flavor. Driven by results. As a McCormick employee you ll be empowered to focus on more than your individual responsibilities. You ll have the opportunity to be part of something bigger than yourself to have a say in where the company is going and how it s growing. Between our passion for flavor, our 130-year history of leadership and integrity, the competitive and comprehensive benefits we offer, and our culture, which is built on respect and opportunities for growth, there are many reasons to join us at McCormick.

Responsibilities: - Contribute and build an internal product library that is focused on solving business problems related to prediction & recommendation. Research unfamiliar methodologies, techniques to fine tune existing models in the product suite and, recommend better solutions and/or technologies. Improve features of the product to include newer machine learning algorithms in the likes of product recommendation, real time predictions, fraud detection, offer personalization etc Collaborate with client teams to on-board data, build models and score predictions. Participate in building automations and standalone applications around machine learning algorithms to enable a One Click solution to getting predictions and recommendations. Analyze large datasets, perform data wrangling operations, apply statistical treatments to filter and fine tune input data, engineer new features and eventually aid the process of building machine learning models. Run test cases to tune existing models for performance, check criteria and define thresholds for success by scaling the input data to multifold. Demonstrate a basic understanding of different machine learning concepts such as Regression, Classification, Matrix Factorization, K-fold Validations and different algorithms such as Decision Trees, Random Forrest, K-means clustering. Demonstrate working knowledge and contribute to building models using deep learning techniques, ensuring robust, scalable and high-performance solutions Minimum Qualifications: Education: Master's or PhD in a quantitative discipline (Statistics, Economics, Mathematics, Computer Science) is highly preferred. Deep Learning Mastery: Extensive experience with deep learning frameworks (TensorFlow, PyTorch, or Keras) and advanced deep learning projects across various domains, with a focus on multimodal data applications. Generative AI Expertise: Proven experience with generative AI models and techniques, such as RAG, VAEs, Transformers, and applications at scale in content creation or data augmentation. Programming and Big Data: Expert-level proficiency in Python and big data/cloud technologies (Databricks and Spark) with a minimum of 4-5 years of experience . Recommender Systems and Real-time Predictions: Expertise in developing sophisticated recommender systems, including the application of real-time prediction frameworks. Machine Learning Algorithms: In-depth experience with complex algorithms such as logistic regression, random forest, XGBoost, advanced neural networks, and ensemble methods. Experienced with machine learning algorithms such as logistic regression, random forest, XG boost, KNN, SVM, neural network, linear regression, lasso regression and k-means. Desirable Qualifications: Generative AI Tools Knowledge: Proficiency with tools and platforms for generative AI (such as OpenAI, Hugging Face Transformers). Databricks and Unity Catalog: Experience leveraging Databricks and Unity Catalog for robust data management, model deployment, and tracking. Working experience in CI/CD tools such as GIT & BitBucket

job requisition idJR1027352 Job Summary Synechron is seeking an analytical and innovative Senior Data Scientist to support and advance our data-driven initiatives. The ideal candidate will have a solid understanding of data science principles, hands-on experience with AI/ML tools and techniques, and the ability to interpret complex data sets to deliver actionable insights. This role contributes to the organizations strategic decision-making and technology innovation by applying advanced analytics and machine learning models in a collaborative environment. Software Required Skills: Python (including libraries such as pandas, scikit-learn, TensorFlow, PyTorch) proficiency in developing and deploying models R (optional, but preferred) Data management tools (SQL, NoSQL databases) Cloud platforms (preferably AWS or Azure) for data storage and ML deployment Jupyter Notebooks or similar interactive development environments Version control tools such as Git Preferred Skills: Big data technologies (Spark, Hadoop) Model deployment tools (MLflow, Docker, Kubernetes) Data visualization tools (Tableau, Power BI) Overall Responsibilities Analyze and interpret large and complex data sets to generate insights for business and technology initiatives. Assist in designing, developing, and implementing AI/ML models and algorithms to solve real-world problems. Collaborate with cross-functional teams including data engineers, software developers, and business analysts to integrate models into production systems. Stay current with emerging trends, research, and best practices in AI/ML/Data Science and apply them to ongoing projects. Document methodologies, modeling approaches, and insights clearly for technical and non-technical stakeholders. Support model validation, testing, and performance monitoring to ensure accuracy and reliability. Contribute to the development of data science workflows and standards within the organization. Performance Outcomes: Accurate and reliable data models that support strategic decision-making. Clear documentation and communication of findings and recommendations. Effective collaboration with technical teams to deploy scalable models. Continuous adoption of best practices in AI/ML and data management. Technical Skills (By Category) Programming Languages: Essential: Python (best practices in ML development), SQL Preferred: R, Java (for integration purposes) Databases/Data Management: SQL databases, NoSQL (MongoDB, Cassandra) Cloud data storage solutions (AWS S3, Azure Blob Storage) Cloud Technologies: AWS (S3, EC2, SageMaker, Lambda) Azure Machine Learning (preferred) Frameworks & Libraries: TensorFlow, PyTorch, scikit-learn, Keras, XGBoost Development Tools & Methodologies: Jupyter Notebooks, Git, CI/CD pipelines Agile and Scrum processes Security Protocols: Best practices in data security and privacy, GDPR compliance Experience 8+ years of professional experience in AI, ML, or Data Science roles. Proven hands-on experience designing and deploying ML models in real-world scenarios. Demonstrated ability to analyze complex data sets and translate findings into business insights. Previous experience working with cloud-based data science solutions is preferred. Strong portfolio showcasing data science projects, models developed, and practical impact. Alternative Pathways: Candidates with extensive research or academic experience in AI/ML can be considered, provided they demonstrate practical application of skills. Day-to-Day Activities Conduct data exploration, cleaning, feature engineering, and model development. Collaborate with data engineers to prepare data pipelines for model training. Build, validate, and refine machine learning models. Present insights, models, and recommendations to technical and business stakeholders. Support deployment of models into production environments. Monitor model performance and iterate to improve effectiveness. Participate in team meetings, project planning, and reviewing progress. Document methodologies and maintain version control of codebase. Qualifications Bachelors degree in Computer Science, Mathematics, Statistics, Data Science, or a related field; Masters or PhD highly desirable. Evidence of relevant coursework, certifications, or professional training in AI/ML. Professional certifications (e.g., AWS Certified Machine Learning Specialty, Microsoft Certified Data Scientist) are a plus. Commitment to ongoing professional development in AI/ML methodologies. Professional Competencies Strong analytical and critical thinking to solve complex problems. Effective communication skills for technical and non-technical audiences. Demonstrated ability to work collaboratively in diverse teams. Aptitude for learning new tools, techniques, and technologies rapidly. Innovation mindset with a focus on applying emerging research. Strong organizational skills to manage multiple projects and priorities.

About Us: Celebal Technologies is a leading Solution Service company that provide Services the field of Data Science, Big Data, Enterprise Cloud & Automation. We are at the forefront of leveraging cuttingedge technologies to drive innovation and enhance our business processes. As part of our commitment to staying ahead in the industry, we are seeking a talented and experienced Data & AI Engineer with strong Azure cloud competencies to join our dynamic team. Job Summary: We are looking for a highly skilled Data Scientist with deep expertise in time series forecasting, particularly in demand forecasting and customer lifecycle analytics (CLV). The ideal candidate will be proficient in Python or PySpark, have hands-on experience with tools like Prophet and ARIMA, and be comfortable working in Databricks environments. Familiarity with classic ML models and optimization techniques is a plus. Key Responsibilities • Develop, deploy, and maintain time series forecasting models (Prophet, ARIMA, etc.) for demand forecasting and customer behavior modeling. • Design and implement Customer Lifetime Value (CLV) models to drive customer retention and engagement strategies. • Process and analyze large datasets using PySpark or Python (Pandas). • Partner with cross-functional teams to identify business needs and translate them into data science solutions. • Leverage classic ML techniques (classification, regression) and boosting algorithms (e.g., XGBoost, LightGBM) to support broader analytics use cases. • Use Databricks for collaborative development, data pipelines, and model orchestration. • Apply optimization techniques where relevant to improve forecast accuracy and business decision-making. • Present actionable insights and communicate model results effectively to technical and non-technical stakeholders. Required Qualifications • Strong experience in Time Series Forecasting, with hands-on knowledge of Prophet, ARIMA, or equivalent Mandatory. • Proven track record in Demand Forecasting Highly Preferred. • Experience in modeling Customer Lifecycle Value (CLV) or similar customer analytics use cases Highly Preferred. • Proficiency in Python (Pandas) or PySpark Mandatory. • Experience with Databricks Mandatory. • Solid foundation in statistics, predictive modeling, and machine learning

At Alstom, we understand transport networks and what moves people. From high-speed trains, metros, monorails, and trams, to turnkey systems, services, infrastructure, signalling and digital mobility, we offer our diverse customers the broadest portfolio in the industry. Every day, 80,000 colleagues lead the way to greener and smarter mobility worldwide, connecting cities as we reduce carbon and replace cars. Your future role Take on a new challenge and apply your data science expertise in a cutting-edge field. You’ll work alongside innovative and collaborative teammates. You'll play a key role in shaping Alstom’s next-generation data-driven solutions for the mobility industry. Day-to-day, you’ll work closely with teams across the business (engineering experts, data engineers, DevOps/MLOps engineers, and HMI designers), develop machine learning models, and contribute to the development of proof-of-concept applications in maintenance, operations, energy, and city flow domains. You’ll specifically take care of extracting key insights from mobility data using advanced tools and techniques, but also contribute to building AI/ML software modules to enhance customer performance and experience. We’ll look to you for: Designing and developing data-driven solutions, integrating engineering aspects and evaluating financial impacts Implementing feature selection/extraction methods to improve ML models and derive interpretable insights Building and optimizing machine learning models, including supervised and unsupervised approaches Assessing and enhancing the quality of incoming data and model outputs using appropriate evaluation metrics Collaborating with domain experts to define and meet business requirements Creating reports and explanatory materials to communicate insights effectively Evaluating opportunities from emerging mathematical approaches and data science technologies Applying strong testing and quality assurance practices All about you We value passion and attitude over experience. That’s why we don’t expect you to have every single skill. Instead, we’ve listed some that we think will help you succeed and grow in this role: Degree in computer science or engineering, supplemented by training in data science/ML or related disciplines Excellent knowledge of Python programming Understanding of modern statistics, including time-series and signal processing, text mining, or image processing Experience with Python data science stack (e.g., pandas, scikit-learn, keras, numpy, tensorflow) Strong knowledge of artificial intelligence and machine learning algorithms (e.g., classification, regression, dimensionality reduction, neural networks, deep learning) Experience in building and optimizing supervised and unsupervised ML models Experience with database management (SQL, ElasticSearch, etc.) Proficiency in a LINUX environment (shell scripting) [Optional: Experience in PHM, predictive maintenance, traffic modelling, NLP, video analytics, or sequence mining] [Optional: Familiarity with Git and release management] Things you’ll enjoy Join us on a life-long transformative journey – the rail industry is here to stay, so you can grow and develop new skills and experiences throughout your career. You’ll also: Enjoy stability, challenges and a long-term career free from boring daily routines Work with cutting-edge technologies to revolutionize digital mobility Collaborate with cross-functional teams and supportive colleagues Contribute to innovative projects in the mobility domain Utilise our flexible and inclusive working environment Steer your career in whatever direction you choose across functions and countries Benefit from our investment in your development, through award-winning learning programs Progress towards leadership or technical expert roles Benefit from a fair and dynamic reward package that recognizes your performance and potential, plus comprehensive and competitive social coverage (life, medical, pension) You don’t need to be a train enthusiast to thrive with us. We guarantee that when you step onto one of our trains with your friends or family, you’ll be proud. If you’re up for the challenge, we’d love to hear from you! Important to note As a global business, we’re an equal-opportunity employer that celebrates diversity across the 63 countries we operate in. We’re committed to creating an inclusive workplace for everyone. Job Segment: Testing, Computer Science, Quality Assurance, Database, Linux, Technology

Overview The Senior Data Science Engineer will leverage advanced data science techniques to solve complex business problems, guide decision-making processes, and mentor junior team members. This role requires a combination of technical expertise in data analysis, machine learning, and project management skills. Responsibilities Data Analysis and Modeling Analyze large-scale telecom datasets to extract actionable insights and build predictive models for network optimization and customer retention. Conduct statistical analyses to validate models and ensure their effectiveness. Machine Learning Development Design and implement machine learning algorithms for fraud detection, churn prediction, and network failure analysis. Telecom-Specific Analytics Apply domain knowledge to improve customer experience by analyzing usage patterns, optimizing services, and predicting customer lifetime value. ETL Processes Develop robust pipelines for extracting, transforming, and loading telecom data from diverse sources. Collaboration Work closely with data scientists, software engineers, and telecom experts to deploy solutions that enhance operational efficiency. Data Governance : Ensure data integrity, privacy, security and compliance with industry standards Advanced degree in Data Science, Statistics, Computer Science, or a related field. Extensive experience in data science roles with a strong focus on machine learning and statistical modeling. Proficiency in programming languages such as Python or R and strong SQL skills. Familiarity with big data technologies (e.g., Hadoop, Spark) is advantageous. Expertise in cloud platforms such as AWS or Azure.

Job Description: Senior Data Scientist – Cognitive Services and AI/ML Experience Level: 6-12 years Competency: Cognitive Services Chennai-WFO‎ Primary Skill: Artificial Intelligence & Machine Learning (AI/ML) Algorithms Secondary Skill: Natural Language Processing (NLP) Computer Vision Cloud-based AI Services (AWS SageMaker, Azure Cognitive Services, Google AI Platform) Job Description (JD): The Data Scientist specializing in Cognitive Services will develop and deploy AI/ML solutions that leverage advanced algorithms to solve complex business problems. The role focuses on integrating machine learning models into applications powered by cognitive capabilities such as image recognition, speech-to-text, and sentiment analysis. . . ‎ Roles and Responsibilities: AI/ML Model Development : Design and implement machine learning models tailored for cognitive services. Algorithm Design: Leverage algorithms for regression, classification, clustering, NLP, and computer vision tasks. Data Integration: Collaborate with data engineers to ensure high-quality and well-structured data pipelines. Cloud Services: Utilize AI/ML tools on platforms like AWS, Azure, or Google for training, deployment, and scalability. Model Deployment: Work with MLOps frameworks to deploy and monitor models in production environments. Cross-functional Collaboration: Partner with software developers and business analysts to integrate cognitive services into customer-facing applications. Performance Optimization: Optimize models and algorithms for speed and scalability. Research & Innovation: Stay abreast of emerging AI/ML technologies and incorporate them into cognitive solutions. Qualifications: Master’s or PhD in Data Science, Machine Learning, or a related field. 8+ years of hands-on experience in AI/ML with a focus on cognitive services. Proficiency in frameworks such as TensorFlow, Py Torch, and Scikit-learn. Expertise in Python, R, and SQL. Experience with cloud-based AI tools and services like AWS Sage Maker or Azure Cognitive Services. Strong understanding of ML Ops practices. Preferred Skills: Familiarity with neural networks for advanced deep learning tasks. Knowledge of speech recognition, image processing, and sentiment analysis technologies. Experience with big data tools such as Apache Spark and Hadoop. Certification in AWS, Azure, or Google Cloud AI services. Show more Show less

Strong proficiency in Advanced SQL with experience in writing optimized queries for large datasets. Mandatory skill : Data Analyst, Python ,SQL, Power BI Exposure in, including predictive modeling and machine learning techniques. Required Candidate profile Hands-on experience with Python, R, or similar analytical tools is a plus. Familiarity with cloud platforms such as AWS, Azure, or GCP for data processing and analytics.