1440 Data Scientist Jobs - Page 17

Before you apply to a job, select your language preference from the options available at the top right of this page. Explore your next opportunity at a Fortune Global 500 organization. Envision innovative possibilities, experience our rewarding culture, and work with talented teams that help you become better every day. We know what it takes to lead UPS into tomorrow—people with a unique combination of skill + passion. If you have the qualities and drive to lead yourself or teams, there are roles ready to cultivate your skills and take you to the next level. Job Description DATA SCIENTIST Job Summary This Data Scientist creates and implements advanced analytics models and solutions to yield predictive and prescriptive insights from large volumes of structured and unstructured data. This position works with a team responsible for the research and implementation of predictive requirements by leveraging industry standard machine learning and data visualization tools to draw insights that empower confident decisions and product creation. This position leverages emerging tools and technologies available in On-prem and Cloud environments. This position utilizes industry standard machine learning and data visualization tools to transform data and analytics requirements into predictive solutions and provide data literacy on a range of machine learning systems at UPS. This position identifies opportunities for driving descriptive to predictive and prescriptive solutions, which become inputs to department and project teams on their decisions supporting projects. Responsibilities Defines key data sources from UPS and external sources to deliver models. Develops and implements pipelines that facilitates data cleansing, data transformations, data enrichments from multiple sources (internal and external) that serve as inputs for data and analytics systems. For larger teams, works with data engineering teams to validate and test data and model pipelines identified during proof of concepts. Develops data design based on the exploratory analysis of large amounts of data to discover trends and patterns that meet stated business needs. Defines model key performance indicator (KPI) expectations and validation, testing, and re-training of existing models to meet business objectives. Reviews and creates repeatable solutions through written project documentation, process flowcharts, logs, and commented clean code to produce datasets that can be used in analytics and/or predictive modeling. Synthesizes insights and documents findings through clear and concise presentations and reports to stakeholders. Presents operationalized analytic findings and provides recommendations. Incorporates best practices on the use of statistical modeling, machine learning algorithms, distributed computing, cloud-based AI technologies, and run time performance tuning with the goal of deployment and market introduction. Leverages emerging tools and technologies together with the use of open-source or vendor products in the creation and delivery of insights that support predictive and prescriptive solutions. Qualifications Expertise in R, SQL, Python and/or any other high-level languages. Exploratory data analysis (EDA), data engineering and development of advanced analytics models. Experience in development of AI and ML using platforms like VertexAI, Databricks or Sagemaker, and familiarity with available frameworks like PyTorch, Tensorflow and Keras. Experience applying models from small to medium scaled problems. Strong analytical skills and attention to detail. Able to engage key business and executive-level stakeholders to translate business problems to a high-level analytics solution approach. Expertise with statistical techniques, machine learning, and/or operations research and their application in business. Deep understanding of data management pipelines and experience in launching moderate scale advanced analytics projects in production. Demonstrated experience in Cloud-AI technologies and knowledge of environments both in Linux/Unix and Windows. Experience implementing open-source technologies and cloud services; with or without the use of enterprise data science platforms. Core AI / Machine Learning knowledge and application in supervised and unsupervised learning domains. Familiarity with Java or C++ is a plus. Solid oral and written communication skills, especially around analytical concepts and methods. Ability to communicate data through a story framework to convey data-driven results to technical and non-technical audiences. Master’s Degree in a quantitative field of mathematics, computer science, physics, economics, engineering, statistics (operations research, quantitative social science, etc.), international equivalent, or equivalent job experience. Last Day Posted - 2/25/2024 Employee Type Permanent UPS is committed to providing a workplace free of discrimination, harassment, and retaliation. Show more Show less

Avant de postuler à un emploi, sélectionnez votre langue de préférence parmi les options disponibles en haut à droite de cette page. Découvrez votre prochaine opportunité au sein d'une organisation qui compte parmi les 500 plus importantes entreprises mondiales. Envisagez des opportunités innovantes, découvrez notre culture enrichissante et travaillez avec des équipes talentueuses qui vous poussent à vous développer chaque jour. Nous savons ce qu’il faut faire pour diriger UPS vers l'avenir : des personnes passionnées dotées d’une combinaison unique de compétences. Si vous avez les qualités, de la motivation, de l'autonomie ou le leadership pour diriger des équipes, il existe des postes adaptés à vos aspirations et à vos compétences d'aujourd'hui et de demain. Fiche De Poste DATA SCIENTIST Job Summary This Data Scientist creates and implements advanced analytics models and solutions to yield predictive and prescriptive insights from large volumes of structured and unstructured data. This position works with a team responsible for the research and implementation of predictive requirements by leveraging industry standard machine learning and data visualization tools to draw insights that empower confident decisions and product creation. This position leverages emerging tools and technologies available in On-prem and Cloud environments. This position utilizes industry standard machine learning and data visualization tools to transform data and analytics requirements into predictive solutions and provide data literacy on a range of machine learning systems at UPS. This position identifies opportunities for driving descriptive to predictive and prescriptive solutions, which become inputs to department and project teams on their decisions supporting projects. Responsibilities Defines key data sources from UPS and external sources to deliver models. Develops and implements pipelines that facilitates data cleansing, data transformations, data enrichments from multiple sources (internal and external) that serve as inputs for data and analytics systems. For larger teams, works with data engineering teams to validate and test data and model pipelines identified during proof of concepts. Develops data design based on the exploratory analysis of large amounts of data to discover trends and patterns that meet stated business needs. Defines model key performance indicator (KPI) expectations and validation, testing, and re-training of existing models to meet business objectives. Reviews and creates repeatable solutions through written project documentation, process flowcharts, logs, and commented clean code to produce datasets that can be used in analytics and/or predictive modeling. Synthesizes insights and documents findings through clear and concise presentations and reports to stakeholders. Presents operationalized analytic findings and provides recommendations. Incorporates best practices on the use of statistical modeling, machine learning algorithms, distributed computing, cloud-based AI technologies, and run time performance tuning with the goal of deployment and market introduction. Leverages emerging tools and technologies together with the use of open-source or vendor products in the creation and delivery of insights that support predictive and prescriptive solutions. Qualifications Expertise in R, SQL, Python and/or any other high-level languages. Exploratory data analysis (EDA), data engineering and development of advanced analytics models. Experience in development of AI and ML using platforms like VertexAI, Databricks or Sagemaker, and familiarity with available frameworks like PyTorch, Tensorflow and Keras. Experience applying models from small to medium scaled problems. Strong analytical skills and attention to detail. Able to engage key business and executive-level stakeholders to translate business problems to a high-level analytics solution approach. Expertise with statistical techniques, machine learning, and/or operations research and their application in business. Deep understanding of data management pipelines and experience in launching moderate scale advanced analytics projects in production. Demonstrated experience in Cloud-AI technologies and knowledge of environments both in Linux/Unix and Windows. Experience implementing open-source technologies and cloud services; with or without the use of enterprise data science platforms. Core AI / Machine Learning knowledge and application in supervised and unsupervised learning domains. Familiarity with Java or C++ is a plus. Solid oral and written communication skills, especially around analytical concepts and methods. Ability to communicate data through a story framework to convey data-driven results to technical and non-technical audiences. Master’s Degree in a quantitative field of mathematics, computer science, physics, economics, engineering, statistics (operations research, quantitative social science, etc.), international equivalent, or equivalent job experience. Last Day Posted - 2/25/2024 Type De Contrat en CDI Chez UPS, égalité des chances, traitement équitable et environnement de travail inclusif sont des valeurs clefs auxquelles nous sommes attachés. Show more Show less

Job Summary: We are seeking a highly skilled and passionate Data Scientist with 3-6 years of experience to join our dynamic team in Chennai. The ideal candidate will possess a strong background in machine learning and deep learning methodologies, coupled with expert-level proficiency in PySpark and SQL for large-scale data manipulation and analysis. You will be instrumental in transforming complex data into actionable insights, building predictive models, and deploying robust data-driven solutions that directly impact our business objectives. Key Responsibilities: Data Analysis & Feature Engineering: Perform extensive exploratory data analysis (EDA) to identify trends, patterns, and anomalies in large, complex datasets. Develop and implement robust data preprocessing, cleaning, and feature engineering pipelines using PySpark and SQL to prepare data for model training. Work with structured and unstructured data, ensuring data quality and integrity. Model Development & Implementation (Machine Learning & Deep Learning): Design, develop, and implement advanced Machine Learning (ML) and Deep Learning (DL) models to solve complex business problems, such as prediction, classification, recommendation, and anomaly detection. Apply a wide range of ML algorithms (e.g., Regression, Classification, Clustering, Ensemble methods) and DL architectures (e.g., CNNs, RNNs, Transformers) as appropriate for the problem at hand. Optimize and fine-tune models for performance, accuracy, and scalability. Experience with ML/DL frameworks such as TensorFlow, PyTorch, Scikit-learn, etc. Big Data Processing: Leverage PySpark extensively for distributed data processing, ETL operations, and running machine learning algorithms on big data platforms (e.g., Hadoop, Databricks, Spark clusters). Write efficient and optimized SQL queries for data extraction, transformation, and loading from relational and non-relational databases. Deployment & MLOps: Collaborate with MLOps engineers and software development teams to integrate and deploy machine learning and deep learning models into production environments. Monitor model performance, identify degradation, and implement retraining strategies to ensure sustained accuracy and relevance. Contribute to building CI/CD pipelines for ML model deployment. Insights & Communication: Translate complex analytical findings and model results into clear, concise, and actionable insights for both technical and non-technical stakeholders. Create compelling data visualizations and reports to effectively communicate findings and recommendations. Act as a subject matter expert, guiding business teams on data-driven decision-making. Research & Innovation: Stay abreast of the latest advancements in data science, machine learning, deep learning, and big data technologies. Proactively identify opportunities to apply new techniques and tools to enhance existing solutions or develop new capabilities. Required Qualifications: Bachelor's or Master's degree in Computer Science, Statistics, Mathematics, Engineering, or a related quantitative field. 3-6 years of hands-on experience as a Data Scientist or in a similar role. Expert proficiency in Python for data science, including libraries such as Pandas, NumPy, Scikit-learn. Strong expertise in PySpark for large-scale data processing and machine learning. Advanced SQL skills with the ability to write complex, optimized queries for data extraction and manipulation. Proven experience in applying Machine Learning algorithms to real-world problems. Solid understanding and hands-on experience with Deep Learning frameworks (e.g., TensorFlow, PyTorch) and architectures. Experience with big data technologies like Hadoop or Spark ecosystem. Strong understanding of statistical concepts, hypothesis testing, and experimental design. Excellent problem-solving, analytical, and critical thinking skills. Ability to work independently and collaboratively in a fast-paced environment. Strong communication and presentation skills, with the ability to explain complex technical concepts to diverse audiences.

Who We Are Simpplr is the AI-powered platform that unifies the digital workplace – bringing together engagement, enablement, and services to transform the employee experience. It streamlines communication, simplifies interactions, automates workflows, and elevates the everyday experience of work. The platform is intuitive, highly extensible, and built to integrate seamlessly with your existing technology. More than 1,000 leading organizations – including AAA, the NHS, Penske, and Moderna – trust Simpplr to foster a more aligned and productive workforce. Headquartered in Silicon Valley with global offices, Simpplr is backed by Norwest Ventures, Sapphire Ventures, Salesforce Ventures, and Tola Capital. Learn more at simpplr.com. About The Role Join our forward-thinking team as a Data Scientist, where you will address real-world challenges through the lens of AI innovation, specifically focusing on Enterprise Search, Personalization, Content Recommendation, and pioneering work with custom LLM fine-tuning. Work in an environment that fosters collaboration among highly skilled professionals to build next-generation products that significantly impact our clients' operational effectiveness. Key Responsibilities Innovate and develop scalable solutions leveraging AI technologies to process and analyze vast amounts of data efficiently. Quickly prototype, test, and deploy effective AI solutions, managing project timelines and deliverables while incorporating the latest advancements in AI research. Engage with cross-disciplinary teams to identify and implement AI-driven enhancements for user experiences, leading the charge from ideation to deployment. What We’re Looking For 1-3 years of experience in crafting and implementing AI models, with a particular interest in applications within Enterprise Search and Content Personalization. Solid grounding in AI technologies, with proficiency in Python and familiarity with AI development frameworks. Interest or experience in ML-Ops, emphasizing the journey from concept to production scalability of ML models. Openness to candidates with a robust background in backend development who have delved into AI, especially those who have engaged in Enterprise Search, Developing learning to rank models, Agentic Workflows and LLM fine-tuning. Knowledge in developing analytical applications and working with cloud platforms, capable of managing large data sets and complex AI models. Technical skill sets Strong coding skills Understanding basics of Machine Learning, Deep Learning, and Natural Language Processing algorithms Experience in working with data annotation tools and building ML evaluation pipelines Comfort with working in multiple tech stacks Experience in API Development, Docker and AWS Services Education - Bachelor's degree from a Tier-1 college (IITs, NITs, BITS, or equivalent preferred). Nice To Have Experience in ML research, focusing on LLMs, Information Retrieval Systems, Reinforcement Learning, Knowledge Graphs, Agentic Workflows, Retrieval-Augmented Generation (RAG), Recommender Systems, Scaling, Monitoring, and Deploying LLMs Our Ideal Candidate We are in search of individuals who are not merely experienced but deeply passionate about unearthing new challenges and inquiries in the realm of AI. We value creativity, positivity, work ethic and the pursuit of answering intricate questions with methodical accuracy. Multiple positions at different seniority levels are available. Simpplr’s Hub-Hybrid-Remote Model At Simpplr we believe that when work is good, life is better and that belief guides all we do. Including how we approach our flexible work model. Simpplr operates with a Hub-Hybrid-Remote model. This model is role-based with exceptions and provides employees with the flexibility that many have told us they want. Hub - 100% work from Simpplr office. Role requires Simpplifier to be in the office full-time. Hybrid - Hybrid work from home and office. Role dictates the ability to work from home, plus benefit from in-person collaboration on a regular basis. Remote - 100% remote. Role can be done anywhere within your country of hire, as long as the requirements of the role are met. Show more Show less

Purpose Of The Position: We are looking for a highly experienced Senior Data Scientist with a deep understanding of AI/ML technologies, including Recommendation Systems, Chatbots, Generative AI, and Large Language Models (LLMs). The ideal candidate will have hands-on experience in applying these technologies to solve real-world problems, working with large datasets, and collaborating with cross-functional teams to deliver innovative data-driven solutions.. Key Responsibilities : Design, develop, and optimize recommendation systems to enhance user experience and engagement across platforms. Build and deploy chatbots with advanced NLP capabilities for automating customer interactions and improving business processes. Lead the development of Generative AI solutions, including content generation and automation. Research and apply Large Language Models (LLMs) like GPT, BERT, and others to solve business-specific problems and create innovative solutions. Collaborate with engineering teams to integrate machine learning models into production systems, ensuring scalability and reliability. Perform data exploration, analysis, and feature engineering to improve model performance. Stay updated on the latest advancements in AI and ML technologies, proposing new techniques and tools to enhance our product capabilities. Mentor junior data scientists and engineers, providing guidance on best practices in AI/ML model development and deployment. Collaborate with product managers and business stakeholders to translate business goals into AI-driven solutions. Work on model interpretability, explainability, and ensure models are built in an ethical and responsible manner. Required Skills And Qualifications: 5+ years of experience in data science or machine learning, with a focus on building and deploying AI models. Strong expertise in designing and developing recommendation systems and working with collaborative filtering, matrix factorization, and content-based filtering techniques. Hands-on experience with chatbots using Natural Language Processing (NLP) and conversational AI frameworks. In-depth understanding of Generative AI, including transformer-based models and GANs (Generative Adversarial Networks). Experience working with Large Language Models (LLMs) such as GPT, BERT, T5, etc. Proficiency in machine learning frameworks such as TensorFlow, PyTorch, and Scikit-learn. Strong programming skills in Python and libraries such as NumPy, Pandas, Hugging Face, and NLTK. Experience with cloud platforms like AWS, GCP, or Azure for deploying and scaling machine learning models. Solid understanding of data pipelines, ETL processes, and working with large datasets using SQL or NoSQL databases. Knowledge of MLOps and experience deploying models in production environments. Strong problem-solving skills and a deep understanding of statistical methods and algorithms. Preferred Qualifications: Experience with Reinforcement Learning and Recommender Systems personalization techniques. Experience of working with AWS Bedrock services. Familiarity with ethical AI and model bias mitigation techniques. Experience with A/B testing, experimentation, and performance tracking for AI models in production. Prior experience mentoring junior data scientists and leading AI/ML projects. Strong communication and collaboration skills, with the ability to convey complex technical concepts to non-technical stakeholders. Why Join Us? Opportunity to be part of a rapidly growing, innovative product-based company. Collaborate with a talented, driven team focused on building high-quality software solutions. Competitive compensation and benefits package.

An Individual Contributor role Productive h ands on programming, supporting deliverables in the study / project / portfolio / standards team, of medium - high complex statistical programming deliverables to support assets and study teams Performs tasks with limited supervision early in role and independently later in role. Is capable of handling standards/study programming specific activities independently including collaboration across stakeholders at various timezones Ensures adherence to high quality programming standards in their daily work Ensure the tasks are completed on time with quality and are compliant to the process at Pfizer with needed guidance. Work collaboratively with study teams and stakeholders such as clinicians and statisticians on milestones and deliverables. Active self-learning and delivering on solutions in the space of statistical programming and data standards Contribute to SDSA initiatives globally and locally. Work Location Assignment: Flexible Work Location Assignment: Hybrid Medical #LI-PFE

The Global Data Insights and Analytics (GDI&A) department at Ford Motors Company is looking for qualified people who can develop scalable solutions to complex real-world problems using Machine Learning, Big Data, Statistics, Econometrics, and Optimization. The candidate should possess the ability to translate a business problem into an analytical problem, identify the relevant data sets needed for addressing the analytical problem, recommend, implement, and validate the best suited analytical algorithm(s), and generate/deliver insights to stakeholders. Candidates are expected to regularly refer to research papers and be at the cutting-edge with respect to algorithms, tools, and techniques. The role is that of an individual contributor; however, the candidate is expected to work in project teams of 2 to 3 people and interact with Business partners on regular basis. Masters degree in computer science, Operational research, Statistics, Applied mathematics, or in any other engineering discipline. Proficient in querying and analyzing large datasets using BigQuery on GCP. Strong Python skills for data wrangling and automation. 2+ years of hands-on experience in Python programming for data analysis, machine learning, and with libraries such as NumPy, Pandas, Matplotlib, Scikit-learn, TensorFlow, PyTorch, NLTK, spaCy, and Gensim. 2+ years of experience with both supervised and unsupervised machine learning techniques. 2+ years of experience with data analysis and visualization using Python packages such as Pandas, NumPy, Matplotlib, Seaborn, or data visualization tools like Dash or QlikSense. 1+ years experience in SQL programming language and relational databases. Understand business requirements and analyze datasets to determine suitable approaches to meet analytic business needs and support data-driven decision-making by FCSD business team Design and implement data analysis and ML models, hypotheses, algorithms and experiments to support data-driven decision-making Apply various analytics techniques like data mining, predictive modeling, prescriptive modeling, math, statistics, advanced analytics, machine learning models and algorithms, etc. ; to analyze data and uncover meaningful patterns, relationships, and trends Design efficient data loading, data augmentation and data analysis techniques to enhance the accuracy and robustness of data science and machine learning models, including scalable models suitable for automation Research, study and stay updated in the domain of data science, machine learning, analytics tools and techniques etc. ; and continuously identify avenues for enhancing analysis efficiency, accuracy and robustness

Candidates for this position are preferred to be based in Bangalore, India and will be expected to comply with their teams hybrid work schedule requirements. The Advertising Optimization & Automation Science team is central to this effort. We leverage machine learning and generative AI to streamline campaign workflows, delivering impactful recommendations on budget allocation, target Return on Ad Spend (tROAS), and SKU selection. Additionally, we are developing intelligent systems for creative optimization and exploring agentic frameworks to further simplify and enhance advertiser interactions. We are looking for an experienced Senior Machine Learning Scientist to join the Advertising Optimization & Automation Science team. In this role, you will be responsible for building intelligent, ML-powered systems that drive personalized recommendations and campaign automation within Wayfair s advertising platform. You will work closely with other scientists, as well as members of our internal Product and Engineering teams, to apply your ML expertise to define and deliver 0-to-1 capabilities that unlock substantial commercial value and directly enhance advertiser outcomes. What You ll do: Design and build intelligent budget, tROAS, and SKU recommendations, and simulation-driven decisioning that extends beyond the current advertising platform capabilities. Lead the next phase of GenAI-powered creative optimization and automation to drive significant incremental ad revenue and improve supplier outcomes. Raise technical standards across the team by promoting best practices in ML system design and development. Partner cross-functionally with Product, Engineering, and Sales to deliver scalable ML solutions that improve supplier campaign performance. Ensure systems are designed for reuse, extensibility, and long-term impact across multiple advertising workflows. Research and apply best practices in advertising science, GenAI applications in creative personalization, and auction modeling. Keep Wayfair at the forefront of innovation in supplier marketing optimization. Collaborate with Engineering teams (AdTech, ML Platform, Campaign Management) to build and scale the infrastructure needed for automated, intelligent advertising decisioning. We Are a Match Because You Have: Bachelors or Master s degree in Computer Science, Mathematics, Statistics, or related field. 9+ years of experience in building large scale machine learning algorithms. 4+ years of experience working in an architect or technical leadership position. Strong theoretical understanding of statistical models such as regression, clustering and ML algorithms such as decision trees, neural networks, transformers and NLP techniques. Proficiency in programming languages such as Python and relevant ML libraries (e.g., TensorFlow, PyTorch) to develop production-grade products. Strategic thinker with a customer-centric mindset and a desire for creative problem solving, looking to make a big impact in a growing organization. Demonstrated success influencing senior level stakeholders on strategic direction based on recommendations backed by in-depth analysis; Excellent written and verbal communication. Ability to partner cross-functionally to own and shape technical roadmaps Intellectual curiosity and a desire to always be learning! Nice to have: Experience with GCP, Airflow, and containerization (Docker). Experience building scalable data processing pipelines with big data tools such as Hadoop, Hive, SQL, Spark, etc. Familiarity with Generative AI and agentic workflows. Experience in Bayesian Learning, Multi-armed Bandits, or Reinforcement Learning. Your personal data is processed in accordance with our Candidate Privacy Notice ( https: / / www.wayfair.com / careers / privacy ).

Growexx is looking for smart and passionate Data Scientist/Analyst, who will empower Marketing, Product, Sales teams to make strategic, data-driven decisions. Key Responsibilities Mine, process, and analyse hit/event level web, product, sales, and digital marketing data. Leverage LLMs (Large Language Models) and traditional machine learning to mine, process, and analyze web, product, sales, and digital marketing event-level data. Develop and fine-tune LLM-driven solutions for tasks such as text summarization, customer support automation, personalization, and user journey understanding. Build and deploy predictive models and ML algorithms across structured and unstructured customer profile, journey, and usage datasets. Deploy LLM and ML models into production environments for activation across websites, product applications, and sales/marketing channels. Design and implement model activation strategies, including A/B testing plans, benchmarking studies, and measurement of final business impact. Conduct comprehensive evaluation of LLMs, including performance benchmarking (accuracy, latency, token usage, cost), prompt effectiveness testing, fine-tuning impact analysis, and safety/bias assessments. Design, build, and deploy LLM-based agentic systems using frameworks such as LangChain, AutoGen, CrewAI, or custom orchestration for complex workflows (e.g., multi-agent collaboration, function-calling pipelines, dynamic task execution). Integrate LLM agents with APIs, internal knowledge bases, retrieval systems (RAG architectures), and external tools to enable autonomous or semi-autonomous decision-making. Partner with data engineering teams to enhance and maintain the Customer360 data model, including creating new feature engineering requirements, improving taxonomy, and identifying and resolving data quality issues. Collaborate with cross-functional teams (Enterprise Data Warehouse, Salesforce MOPS, IT, Product, Marketing) to continuously improve data integration and quality for advanced modeling use cases. Build a deep understanding of business models, objectives, challenges, and opportunities by working closely with leadership and key stakeholders. Document model methodologies, evaluation frameworks, agent workflows, deployment architectures, and post-activation performance results in a structured and reproducible format. Stay current with advancements in LLMs, agentic AI, retrieval-augmented generation (RAG), and ML technologies to recommend and implement innovative solutions. Key Skills Experience using Python, SciKit, SQL, Snowflake, product usage data, Jupyter Notebooks, Amazon SageMaker, Airflow, Github. Proficient in data mining, advanced statistical analysis, feature engineering, and mathematical modeling. Deep experience with machine learning techniques including supervised, unsupervised, reinforcement learning, causal inference, and predictive modeling. Skilled across the full ML lifecycle: data preparation, feature creation and selection, model training, hyperparameter tuning, evaluation, and deployment for inference/prediction. Extensive hands-on experience with cookie-level advertising and digital marketing data (Google Ads, Bing, Epsilon, LinkedIn, Facebook) for demand generation KPIs such as ROAS, CTRs, impressions, multi-touch attribution (MTA). Proven experience designing, fine-tuning, evaluating, and deploying Large Language Models (LLMs) and generative AI applications. Experience designing and deploying agentic systems using frameworks such as LangChain, AutoGen, CrewAI, and custom function-calling pipelines. Expertise integrating LLM agents with APIs, knowledge bases, retrieval systems (RAG architecture), and orchestrating dynamic multi-agent workflows. Strong understanding of evaluation metrics for LLMs, including prompt testing, token optimization, bias/safety analysis, latency, and cost benchmarks. Deep familiarity with cookie-level web and product behavior data (usage metrics, conversion funnels, bounce rates, sessions, hits/events, journey optimization). Expertise in designing and executing A/B, multivariate, and lift tests to measure activated ML/LLM model performance across digital and offline channels. Skilled in gathering business requirements, translating them into ML use cases, and clearly communicating methodologies and results to both technical and non-technical stakeholders. Continuous learner, keeping up-to-date with the latest advances in transformers, generative AI models, retrieval-augmented generation (RAG), and agentic AI frameworks. Preferred: practical experience in an engineering capacity building, testing, deploying, and optimizing ensemble ML and LLM solutions in production environments. Education and Experience B Tech or B. E. (Computer Science / Information Technology) 5 + years as a Data Scientist or similar roles.

We are seeking a highly skilled AI Data Scientist to join our growing data science team. The ideal candidate will possess strong analytical capabilities, machine learning expertise, and practical experience deploying AI solutions. You will work on cutting-edge projects involving deep learning, NLP, and predictive analytics to solve complex business challenges.

Job Description: Data Scientist 1. Expertise in Data Science & AI/ML: 3-8 years experience designing, developing, and deploying scalable AI/ML solutions for Big Data, with proficiency in Python, SQL, TensorFlow, PyTorch, Scikit-learn, and Big Data ML libraries (e.g., Spark MLlib). 2. Cloud Proficiency: Proven experience with cloud-based Big Data services (GCP preferred, AWS/Azure a plus) for AI/ML model deployment and Big Data pipelines.; understanding of data modeling, warehousing, and ETL in Big Data contexts. 3. Analytical & Communication Skills: Ability to extract actionable insights from large datasets, apply statistical methods, and effectively communicate complex findings to both technical and non-technical audiences (visualization skills a plus). 4. Educational Background: Bachelors or Masters degree in a quantitative field (Computer Science, Data Science, Engineering, Statistics, Mathematics). EXPERIENCE 3-4.5 Years SKILLS Primary Skill: Data Science Sub Skill(s): Data Science Additional Skill(s): Python, Data Science, SQL, TensorFlow, Pytorch

Project Role : Responsible AI Engineer Project Role Description : Assess AI systems for adherence to predefined thresholds and benchmarks related to responsible, ethical and sustainable practices. Design and implement technology mitigation strategies for systems to ensure ethical and responsible standards are achieved. Must have skills : Large Language Models Good to have skills : NA Minimum 5 year(s) of experience is required Educational Qualification : 15 years full time education Summary: As an AI Platform Engineer, you will be responsible for developing applications and systems that utilize AI to improve performance and efficiency. Your typical day will involve working with Large Language Models, deep learning, neural networks, chatbots, and natural language processing. Roles & Responsibilities: - Design and develop scalable and efficient AI-based applications and systems using Large Language Models, deep learning, neural networks, chatbots, and natural language processing. - Collaborate with cross-functional teams to identify and prioritize AI use cases, and develop solutions that meet business requirements. - Implement and maintain AI models and algorithms, and ensure their accuracy, reliability, and scalability. - Develop and maintain AI infrastructure, including data pipelines, model training and deployment pipelines, and monitoring and logging systems. - Stay updated with the latest advancements in AI and machine learning, and integrate innovative approaches for sustained competitive advantage. Professional & Technical Skills: - Must To Have Skills: Experience with Large Language Models. - Strong understanding of deep learning, neural networks, chatbots, and natural language processing. - Experience with AI infrastructure, including data pipelines, model training and deployment pipelines, and monitoring and logging systems. - Proficiency in programming languages such as Python, Java, or C++. - Experience with cloud platforms such as AWS, Azure, or GCP. - Experience with containerization technologies such as Docker and Kubernetes. Additional Information: - The ideal candidate will possess a strong educational background in computer science, artificial intelligence, or a related field, along with a proven track record of delivering impactful AI-driven solutions.

Sr.Data Scientist - Soulpage IT Solutions Home Sr.Data Scientist May 28, 2024 Job Title: Data Scientist Work Exp: 3+ yrs Approximate CTC: Industry Standards Location: Hyderabad Functional Area: IT Software System Programming Qualification: B.Tech/B.E/M.Tech/B.Sc(math or statistics)/MSc(Statistics) Job Description: We are looking for an experienced Data Scientist with a strong hold on Machine Learning and Deep Learning model building, deployment and has problem solving skills. Skills & Responsibilities: Excellent skills in Deep learning-based algorithms with image and text data and ML algorithms with structured datasets. Strong hold on computer vision libraries like OpenCV and Pillow and NLP libraries like Huggingface and Spacy. Ability to conceptualize and implement different deep neural network architectures in Python using Pytorch and Tensorflow. Strong mathematical statistical understanding behind the algorithms. Ideate, conceptualize and formulate Data Science use case of significant impact for the business Develop and evaluate various Machine Learning models before zeroing in on the best one and ability to run Machine Learning models on huge amount of data Drive discussions with Business to ensure the complete understanding with respect to the data science use case; Gain and demonstrate Data and Domain knowledge Evaluate the Data Quality and Metadata information of Key Data Elements before any modelling effort to ensure minimal surprises in the later part of the project Design holistic data science solution covering Descriptive, Predictive & Prescriptive analytics Build reusable ML code for faster turnaround time to business problem solving Explain the Machine Learning model implementation to business stakeholders in a way that they can understand and appreciate the solution Build storytelling dashboards to make all insights and model output available to end users in a form which is highly helpful for decision making Manage relationship with business stakeholders acting as embedded data scientist constantly thinking about data science solutions to make business better Key Skills Required: Python, Pytorch, Tensorflow, OpenCV, Scikit Learn, Pandas and Numpy, Flask, Django, AWS, Deep Learning including CNNs, Transformers, and RNNs, and Statistical Modelling. About Company: Soulpage IT Solutions Pvt. Ltd. SOULPAGE is a Data Science Technology company based in Hyderabad, India. A simple organization with a strong commitment to customer service. We are committed to helping enterprises explore unventured technical avenues to tap unprecedented value creation. Our effort is to provide innovative software solutions using the latest technological advancements in the areas of automation, Data Science, AI, and application development for our clients to stay relevant and adapt to changing times.

Newton School of Technology is on a mission to transform technology education and bridge the employability gap. As India s first impact university, we are committed to revolutionizing learning, empowering students, and shaping the future of the tech industry. Backed by renowned professionals and industry leaders, we aim to solve the employability challenge and create a lasting impact on society. We are currently looking for a Data Engineer + Subject Matter Expert - Data Mining to join our Computer Science Department. This is a full-time academic role focused on data mining, analytics, and teaching/mentoring students in core data science and engineering topics. Key Responsibilities: Develop and deliver comprehensive and engaging lectures for the undergraduate "Data Mining", BigData and Data Analytics courses, covering the full syllabus from foundational concepts to advanced techniques. Instruct students on the complete data lifecycle, including data preprocessing, cleaning, transformation, and feature engineering. Teach the theory, implementation, and evaluation of a wide range of algorithms for Classification, Association rules mining, Clustering and Anomaly Detections. Design and facilitate practical lab sessions and assignments that provide students with hands-on experience using modern data tools and software. Develop and grade assessments, including assignments, projects, and examinations, that effectively measure the Course Learning Objectives (CLOs). Mentor and guide students on projects, encouraging them to work with real-world or benchmark datasets (e.g., from Kaggle). Stay current with the latest advancements, research, and industry trends in data engineering and machine learning to ensure the curriculum remains relevant and cutting-edge. Contribute to the academic and research environment of the department and the university. Required Qualifications: A Ph.D. (or a Masters degree with significant, relevant industry experience) in Computer Science, Data Science, Artificial Intelligence, or a closely related field. Demonstrable expertise in the core concepts of data engineering and machine learning as outlined in the syllabus. Strong practical proficiency in Python and its data science ecosystem, specifically Scikit-learn, Pandas, NumPy, and visualization libraries (e.g., Matplotlib, Seaborn). Proven experience in teaching, preferably at the undergraduate level, with an ability to make complex topics accessible and engaging. Excellent communication and interpersonal skills. Preferred Qualifications: A strong record of academic publications in reputable data mining, machine learning, or AI conferences/journals. Prior industry experience as a Data Scientist, Big Data Engineer, Machine Learning Engineer, or in a similar role. Experience with big data technologies (e.g., Spark, Hadoop) and/or deep learning frameworks (e.g., TensorFlow, PyTorch). Experience in mentoring student teams for data science competitions or hackathons. Perks & Benefits: Competitive salary packages aligned with industry standards. Access to state-of-the-art labs and classroom facilities. To know more about us, feel free to explore our website: Newton School of Technology We look forward to the possibility of having you join our academic team and help shape the future of tech education! Newton School of Technology is on a mission to transform technology education and bridge the employability gap. As India s first impact university, ...

Who We Are & Why Join Us Avathon is revolutionizing industrial AI with a powerful platform that enables businesses to harness the full potential of their operational data. Our technology seamlessly integrates and contextualizes siloed datasets, providing a 360-degree operational view that enhances decision-making and efficiency. With advanced capabilities like digital twins, natural language processing, normal behavior modeling, and machine vision, we create real-time virtual replicas of physical assets, enabling predictive maintenance, performance simulation, and operational optimization. Our AI-driven models empower companies with scalable solutions for anomaly detection, performance forecasting, and asset lifetime extension all tailored to the complexities of industrial environments. Cutting-Edge AI Innovation - Join a team at the forefront of AI, developing groundbreaking solutions that shape the future. High-Growth Environment - Thrive in a fast-scaling startup where agility, collaboration, and rapid professional growth are the norm. Meaningful Impact - Work on AI-driven projects that drive real change across industries and improve lives. Learn more at: Avathon The Applied Research team addresses hard, novel challenges that arise in product development or customer engagements. As a Data Scientist, Supply Chain , youll bring your knowledge and proven data science expertise to conduct research in machine learning-based solutions that improve our products and help our customers. Qualified candidates are deeply analytical with a keen understanding of artificial intelligence, machine learning, and data science. They are experienced researchers who know how to design worthwhile experiments and empirically derive conclusions. They have the ability, inclination, and experience to conduct research that solves practical problems. They have the communication skills to work closely with both research colleagues and customers. You will: Independently and effectively engage with internal product developers, external customers, and subject matter experts to understand and solve critical technical challenges through the application of cutting-edge artificial intelligence Conduct research and design technical solutions that improve models for commercial and industrial applications, such as forecasting stochastic demand, economics based inventory optimization, manufacturing and network planning, transportation routing and resource scheduling, anomaly detection and prescriptive maintenance based on IOT data, and fraud detection Conduct research across artificial intelligence areas including reinforcement learning, foundation models, graph neural networks, causal modeling, transferability and continuous learning Pioneer procedures and/or automated toolsets to more efficiently and effectively perform data science activities Contribute to AI product development and key data science research areas, internally and externally Propose new projects or initiatives that will yield business benefits and evaluate project plans and proposals Evaluate and respond to RFPs related to artificial intelligence Conduct research and write patent applications and technical publications You ll Have: Experience with research-level innovation in Data Science and ML, preferably with an advanced degree. 5+ years of experience in one or more of Forecasting, Optimisation ( Inventory/ Supply chain/ Network/ Transportation),Procurement, experience on economic and Probabilistic modeling is a plus. Strong understanding of Data Science, including machine learning, statistics, probability, and modeling. Significant experience with Data Science programming languages, such as Python, R, Matlab Significant experience with machine learning frameworks, such as PyTorch, TensorFlow, Theano, and Keras. Applied knowledge of ML techniques/algorithms including linear models, neural networks, decision trees, Bayesian techniques, clustering, and anomaly detection Significant experience managing large volumes of data (terabytes or more) Experience with leading project teams, specifically data science teams Strong written and verbal communications, ability to translate complex technical topics to internal and external stakeholders. Avathon is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, age, pregnancy, genetic information, disability, status as a protected veteran, or any other protected category under applicable federal, state, and local laws. Avathon is committed to providing reasonable accommodations throughout the recruiting process. If you need a reasonable accommodation, please contact us to discuss how we can assist you.

The Catalog Data Science Team at Walmart Global Tech is focused on using the latest research in generative AI (GenAI), artificial intelligence (AI), machine learning (ML), statistics, deep learning, computer vision and optimization to implement solutions that ensure Walmart s product catalog is accurate, complete, and optimized for customer experience. Our team tackles complex data science and ML engineering challenges related to product classification, attribute extraction, trust & safety, and catalog optimization, empowering next-generation retail use cases. The Data Science and ML Engineering community at Walmart Global Tech is active in most of the Hack events, utilizing the petabytes of data at our disposal, to build some of the coolest ideas. All the work we do at Walmart Global Tech will eventually benefit our operations & our associates, helping Customers Save Money to Live Better. What youll do: As a Senior Data Scientist - ML Engineer, you ll have the opportunity to: Drive research initiatives and proof-of-concepts that push the state of the art in generative AI and large-scale machine learning. Design and implement high-throughput, low-latency AI/ML pipelines and microservices that operate at global scale. Oversee data ingestion, model training, evaluation, deployment and monitoring-ensuring performance, quality and reliability. Customize and optimize LLMs for specific business use cases, balancing accuracy, latency and cost. Prototype novel generative AI solutions, integrate advancements into production, and collaborate with research partners. Champion best practices in data quality, lineage, governance and cost optimization across ML pipelines. Mentor a team of ML engineers, establish coding standards, conduct design reviews, and foster a culture of continuous improvement. Present your team s work at top-tier AI/ML conferences, publish scientific papers, and cultivate partnerships with universities and research labs. What youll bring PhD in Computer Science, Statistics, Applied Mathematics or related field with 3+ years experience in ML engineering-or Master s with 6+ years or Bachelor s with 8+ years. Proven track record of leading and scaling AI/ML products in production environments. Deep expertise in generative AI, large-scale model deployment, and fine-tuning of transformer-based architectures. Strong programming skills in Python, or equivalent, and experience with big data frameworks (Spark, Hadoop) and ML platforms (TensorFlow, PyTorch). Demonstrated history of scientific publications or patents in AI/ML. Excellent communication skills, a growth mindset, and the ability to drive cross-functional collaboration

Position Summary... What youll do... About Team The Catalog Data Science Team at Walmart Global Tech is focused on using the latest research in generative AI (GenAI), artificial intelligence (AI), machine learning (ML), statistics, deep learning, computer vision and optimization to implement solutions that ensure Walmart s product catalog is accurate, complete, and optimized for customer experience. Our team tackles complex data science and ML engineering challenges related to product classification, attribute extraction, trust & safety, and catalog optimization, empowering next-generation retail use cases. The Data Science and ML Engineering community at Walmart Global Tech is active in most of the Hack events, utilizing the petabytes of data at our disposal, to build some of the coolest ideas. All the work we do at Walmart Global Tech will eventually benefit our operations & our associates, helping Customers Save Money to Live Better. What youll do: As a Senior Data Scientist for Walmart Global Tech, you ll have the opportunity to Design, develop, and deploy AI/ML, NLP, LLM models into production environments with a focus on reliability and scalability Integrate data science solutions into current business processes. Develop and recommend process standards and best practices in Machine Learning as applicable to the retail industry. Spearhead collaborations with other senior team members and stakeholders, leveraging your data science expertise to drive strategic decision-making and optimize business operations Promote and support company policies, procedures, mission, values, and standards of ethics and integrity. What youll bring: Qualifications PhD with >3 years of relevant experience / 4-year bachelor s degree with > 8 years of experience / Master s degree with > 6 years of experience. Educational qualifications should be preferably in Computer Science or a strongly quantitative discipline. Demonstrated history of strong hands-on experience in AI/ML modelling Prior Experience in building Vision-based models Proven records of scientific publications or intellectual property generation Prior Experience in programming skills across data science, statistical analysis, big data and ML stack Strong communication skills with inclination to high ownership and commitment Proven track record of delivering high-impact AI/ML solutions to Production Mandatory Skills: Machine Learning, NLP, Computer Vision , Python, R Additional Qualifications: Good to have experience in areas such as Graph Neural Networks, LLM Optimization About Walmart Global Tech . . Flexible, hybrid work . Benefits . Belonging . . Equal Opportunity Employer Walmart, Inc., is an Equal Opportunities Employer - By Choice. We believe we are best equipped to help our associates, customers and the communities we serve live better when we really know them. That means understanding, respecting and valuing unique styles, experiences, identities, ideas and opinions - while being inclusive of all people. Minimum Qualifications... Minimum Qualifications:Option 1- Bachelors degree in Statistics, Economics, Analytics, Mathematics, Computer Science, Information Technology, or related field and 3 years experience in an analytics related field. Option 2- Masters degree in Statistics, Economics, Analytics, Mathematics, Computer Science, Information Technology, or related field and 1 years experience in an analytics related field. Option 3 - 5 years experience in an analytics or related field. Preferred Qualifications... Primary Location...

Senior Data Scientist - Enterprise Analytics Want to be part of the Data & Analytics organization, whose strategic goal is to create a world-class Data & Analytics company by building, embedding, and maturing a data-driven culture across Thomson Reuters. We are looking for a highly motivated individual with strong organizational and technical skills for the position of Senior Data Scientist. You will play a critical role working on cutting edge of analytics, leveraging predictive models, machine learning and generative AI to drive business insights and facilitating informed decision-making and help Thomson Reuters rapidly scale data-driven initiatives. About the Role In this opportunity as Senior Data Scientist, you will: Engage with stakeholders, business analysts and project team to understand the data requirements. Work in multiple business domain areas including Customer Service, Finance, Sales and Marketing. Design analytical frameworks to provide insights into a business problem. Explore and visualize multiple data sets to understand data available and prepare data for problem solving. Build machine learning models and/or statistical solutions. Build predictive models, generative AI solutions. Use Natural Language Processing to extract insight from text. Design database models (if a data mart or operational data store is required to aggregate data for modeling). Design visualizations and build dashboards in Tableau and/or PowerBI. Extract business insights from the data and models. Present results to stakeholders (and tell stories using data) using power point and/or dashboards. About You Youre a fit for the role of Senior Data Scientist if your background includes: Experience- 6-8 Years in the field of Machine Learning & AI Must have a minimum of 3 years of experience working in the data science domain Degree preferred in a quantitative field (Computer Science, Statistics, etc.) Both technical and business acumen is required Technical skills Proficient in machine learning, statistical modelling, data science and generative AI techniques Highly proficient in Python and SQL Experience with Tableau and/or PowerBI Has worked with Amazon Web Services and Sagemaker Ability to build data pipelines for data movement using tools such as Alteryx, GLUE Experience Predictive analytics for customer retention, upsell/cross sell products and new customer acquisition, Customer Segmentation, Recommendation engines (customer and AWS Personalize), POC s in building Generative AI solutions (GPT, Llama etc.,) Hands on with Prompt Engineering Experience in Customer Service, Finance, Sales and Marketing Additional Technical skills include Familiarity with Natural Language Processing including Feature Extraction techniques, Word Embeddings, Topic Modeling, Sentiment Analysis, Classification, Sequence Models and Transfer Learning Knowledgeable of AWS APIs for Machine Learning Has worked with Snowflake extensively. Good presentation skills and the ability to tell stories using data and Powerpoint/Dashboard Visualizations. Ability to communicate complex results in a simple and concise manner at all levels within the organization. Consulting Experience with a premier consulting firm. #LI-SS5 What s in it For You? Hybrid Work Model: We ve adopted a flexible hybrid working environment (2-3 days a week in the office depending on the role) for our office-based roles while delivering a seamless experience that is digitally and physically connected. Flexibility & Work-Life Balance: Flex My Way is a set of supportive workplace policies designed to help manage personal and professional responsibilities, whether caring for family, giving back to the community, or finding time to refresh and reset. This builds upon our flexible work arrangements, including work from anywhere for up to 8 weeks per year, empowering employees to achieve a better work-life balance. Career Development and Growth: By fostering a culture of continuous learning and skill development, we prepare our talent to tackle tomorrow s challenges and deliver real-world solutions. Our Grow My Way programming and skills-first approach ensures you have the tools and knowledge to grow, lead, and thrive in an AI-enabled future. Industry Competitive Benefits: We offer comprehensive benefit plans to include flexible vacation, two company-wide Mental Health Days off, access to the Headspace app, retirement savings, tuition reimbursement, employee incentive programs, and resources for mental, physical, and financial wellbeing. Culture: Globally recognized, award-winning reputation for inclusion and belonging, flexibility, work-life balance, and more. We live by our values: Obsess over our Customers, Compete to Win, Challenge (Y)our Thinking, Act Fast / Learn Fast, and Stronger Together. Social Impact: Make an impact in your community with our Social Impact Institute. We offer employees two paid volunteer days off annually and opportunities to get involved with pro-bono consulting projects and Environmental, Social, and Governance (ESG) initiatives. Making a Real-World Impact: We are one of the few companies globally that helps its customers pursue justice, truth, and transparency. Together, with the professionals and institutions we serve, we help uphold the rule of law, turn the wheels of commerce, catch bad actors, report the facts, and provide trusted, unbiased information to people all over the world. About Us Thomson Reuters informs the way forward by bringing together the trusted content and technology that people and organizations need to make the right decisions. We serve professionals across legal, tax, accounting, compliance, government, and media. Our products combine highly specialized software and insights to empower professionals with the data, intelligence, and solutions needed to make informed decisions, and to help institutions in their pursuit of justice, truth, and transparency. Reuters, part of Thomson Reuters, is a world leading provider of trusted journalism and news. We are powered by the talents of 26,000 employees across more than 70 countries, where everyone has a chance to contribute and grow professionally in flexible work environments. At a time when objectivity, accuracy, fairness, and transparency are under attack, we consider it our duty to pursue them. Sound exciting? Join us and help shape the industries that move society forward. As a global business, we rely on the unique backgrounds, perspectives, and experiences of all employees to deliver on our business goals. To ensure we can do that, we seek talented, qualified employees in all our operations around the world regardless of race, color, sex/gender, including pregnancy, gender identity and expression, national origin, religion, sexual orientation, disability, age, marital status, citizen status, veteran status, or any other protected classification under applicable law. Thomson Reuters is proud to be an Equal Employment Opportunity Employer providing a drug-free workplace. We also make reasonable accommodations for qualified individuals with disabilities and for sincerely held religious beliefs in accordance with applicable law. More information on requesting an accommodation here . Learn more on how to protect yourself from fraudulent job postings here . More information about Thomson Reuters can be found on thomsonreuters.com.

Strong in Python and experience with Jupyter notebooks, Python packages like polars, pandas, numpy, scikit-learn, matplotlib, etc. Must have: Experience with machine learning lifecycle, including data preparation, training, evaluation, and deployment Must have: Hands-on experience with GCP services for ML & data science Must have: Experience with Vector Search and Hybrid Search techniques Must have: Experience with embeddings generation using models like BERT, Sentence Transformers, or custom models Must have: Experience in embedding indexing and retrieval (e.g., Elastic, FAISS, ScaNN, Annoy) Must have: Experience with LLMs and use cases like RAG (Retrieval-Augmented Generation) Must have: Understanding of semantic vs lexical search paradigms Must have: Experience with Learning to Rank (LTR) techniques and libraries (e.g., XGBoost, LightGBM with LTR support) Should be proficient in SQL and BigQuery for analytics and feature generation Should have experience with Dataproc clusters for distributed data processing using Apache Spark or PySpark Should have experience deploying models and services using Vertex AI, Cloud Run, or Cloud Functions Should be comfortable working with BM25 ranking (via Elasticsearch or OpenSearch) and blending with vector-based approaches Good to have: Familiarity with Vertex AI Matching Engine for scalable vector retrieval Good to have: Familiarity with TensorFlow Hub, Hugging Face, or other model repositories Good to have: Experience with prompt engineering, context windowing, and embedding optimization for LLM-based systems Should understand how to build end-to-end ML pipelines for search and ranking applications Must have: Awareness of evaluation metrics for search relevance (e.g., precision@k, recall, nDCG, MRR) Should have exposure to CI/CD pipelines and model versioning practices GCP Tools Experience: ML & AI: Vertex AI, Vertex AI Matching Engine, AutoML, AI Platform Storage: BigQuery, Cloud Storage, Firestore Ingestion: Pub/Sub, Cloud Functions, Cloud Run Search: Vector Databases (e.g., Matching Engine, Qdrant on GKE), Elasticsearch/OpenSearch Compute: Cloud Run, Cloud Functions, Vertex Pipelines, Cloud Dataproc (Spark/PySpark) CI/CD & IaC: GitLab/GitHub Actions Location: Remote- Bengaluru,Hyderabad,Delhi / NCR,Chennai,Pune,Kolkata,Ahmedabad,Mumbai

We are seeking a skilled and experienced Machine Learning Engineer specialized in Natural Language Processing (NLP) and Computer Vision to join our team. The candidate should have a strong foundation in ML and AI principles, coupled with a proven track record of developing and deploying a minimum of 20+ models in these domains. Responsibilities: Develop and implement state-of-the-art machine learning algorithms and models for NLP and computer vision applications. Collaborate with cross-functional teams to understand business requirements and translate them into technical solutions. Conduct thorough data analysis, pre-processing, and feature engineering to extract meaningful insights from structured and unstructured data. Design and implement scalable and efficient machine learning pipelines for training, evaluation, and inference. Experiment with various deep learning architectures, hyper parameters, and optimization techniques to improve model performance. Stay updated with the latest advancements in ML and AI research and evaluate their potential applications in our domain. Work closely with software engineers to integrate ML models into production systems and ensure their robustness and scalability. Perform rigorous testing and validation of models to ensure their accuracy, reliability, and generalization capability. Continuously monitor and maintain deployed models, and implement necessary updates and enhancements as required. Document code, methodologies, and findings effectively, and contribute to internal knowledge sharing initiatives. Bachelor's/Masters/Ph.D. degree in Computer Science, Engineering, Mathematics, or a related field. Strong theoretical understanding of machine learning algorithms, deep learning frameworks, and statistical modeling techniques. Proficiency in programming languages such as Python, along with experience in popular ML libraries such as TensorFlow, PyTorch, or scikit-learn. Hands-on experience in developing and deploying machine learning models for NLP and computer vision tasks, with a demonstrable portfolio of projects. Solid understanding of natural language processing techniques, including text classification, sentiment analysis, named entity recognition, etc. Familiarity with computer vision concepts such as image classification, object detection, image segmentation, etc., and experience with frameworks like OpenCV or TensorFlow. Experience with cloud platforms (e.g., AWS, Azure, Google Cloud) and containerization technologies (e.g., Docker, Kubernetes) is a plus. Excellent problem-solving skills, attention to detail, and ability to work independently as well as part of a team. Strong communication and interpersonal skills, with the ability to effectively collaborate with stakeholders across different functional areas. We need only Data Scientist Candidates. For More Information Kindly call on 7701968943(Sanchit) Share your updated cv on sanchit@mounttalent.com

We are seeking a Senior Data Scientist Engineer with experience bringing highly scalable enterprise SaaS applications to market. This is a uniquely impactful opportunity to help drive our business forward and directly contribute to long-term growth at Virtana. If you thrive in a fast-paced environment, take initiative, embrace proactivity and collaboration, and you re seeking an environment for continuous learning and improvement, we d love to hear from you! Virtana is a remote first work environment so you ll be able to work from the comfort of your home while collaborating with teammates on a variety of connectivity tools and technologies. Role Responsibilities: Research and test machine learning approaches for analyzing large-scale distributed computing applications. Develop production-ready implementations of proposed solutions across different models AI and ML algorithms, including testing on live customer data to improve accuracy, efficacy, and robustness Work closely with other functional teams to integrate implemented systems into the SaaS platform Suggest innovative and creative concepts and ideas that would improve the overall platform. Job Location - Pune, Chennai or Remote Qualifications: The ideal candidate must have the following qualifications: 6 + years experience in practical implementation and deployment of large customer-facing ML based systems. MS or M Tech (preferred) in applied mathematics/statistics; CS or Engineering disciplines are acceptable but must have with strong quantitative and applied mathematical skills In-depth working, beyond coursework, familiarity with classical and current ML techniques, both supervised and unsupervised learning techniques and algorithms Implementation experiences and deep knowledge of Classification, Time Series Analysis, Pattern Recognition, Reinforcement Learning, Deep Learning, Dynamic Programming and Optimization Experience in working on modeling graph structures related to spatiotemporal systems Programming skills in Python is a must Experience in understanding and usage of LLM models and Prompt engineering is preferred. Experience in developing and deploying on cloud (AWS or Google or Azure) Good verbal and written communication skills Familiarity with well-known ML frameworks such as Pandas, Keras, TensorFlow

Key Responsibilities: Demonstrates proficiency in at least one of the four areas: Computer Vision, Natural Language Processing, Machine Learning, and Forecasting. Expected to deepen this expertise further. Translates data-related client requirements into project tasks and deliverables, with an understanding of complex problems and solutions. Drives data solutions within projects, with a focus on innovation and value creation. Provides technical guidance and support to team members on data science methodologies, tools, and algorithms. Acts as a point of escalation for data science-related issues within the project, working towards efficient resolution. Reviews and ensures adherence to performance parameters for data science tasks, with a focus on data quality and model performance. Balances data science workload within the team, considering the skills and capacities of team members. Champions learning initiatives for upskilling and cross-skilling in data science within the team, including knowledge sharing sessions and promoting best practices. Contributes to the development of new data science solution offerings, leveraging insights from project work. Encourages team members to build technical expertise and innovate within the realm of data science. Begins to build and nurture client relationships with a focus on identifying opportunities to add value through data science. Starts to develop proficiency in at least one of data engineering, MLOps, product engineering, and cloud services, and applies this knowledge within projects. Begins to contribute to the organizations thought leadership in data science, such as writing articles, giving presentations, or contributing to internal forums. Actively identifies and communicates opportunities for the organization to enhance its data science capabilities, including new tools, methodologies, or service offerings. Keeps an eye on industry trends in data science to ensure personal growth and the competitive advantage of the organization

Job Summary As a Data Scientist at Bluphlux, you will play a pivotal role in leveraging advanced data analytics and machine learning techniques to enhance our AI-driven recruitment solutions. You will work closely with our engineering and product teams to develop and implement models that improve the accuracy and efficiency of our resume ranking system. Key Responsibilities Develop and implement machine learning models to enhance our recruitment platform. Analyze large datasets to extract meaningful insights and improve our algorithms. Collaborate with cross-functional teams to integrate data-driven solutions into our products. Continuously monitor and refine models to ensure optimal performance. Stay updated with the latest advancements in data science and machine learning to drive innovation. Required Qualifications Bachelors or Masters degree in Data Science, Computer Science, Statistics, or a related field. Proven experience as a Data Scientist or similar role. Strong knowledge of machine learning algorithms and data analysis techniques. Proficiency in programming languages such as Python or R. Experience with data visualization tools and techniques. Preferred Skills Experience with natural language processing (NLP) and language models. Familiarity with cloud platforms such as AWS or Azure. Strong problem-solving skills and attention to detail. Excellent communication and teamwork abilities. Also important: If the candidate says his notice period is more than 2 months then try to negotiate.

Job Title: Data Scientist Location: Chennai Experience: 4-8 Years Skills Required: 4 + years of hands-on experience in using machine learning/text mining tools and techniques such as Clustering /classification/ decision trees, Random forests, Support vector machines, Deep Learning, Neural networks, Reinforcement learning, and other numerical algorithms. Looking for qualified Data Scientists who can develop scalable solutions to complex real-world problems using Machine Learning, Big Data, Statistics, and Optimization. Potential candidates should have hands-on experience in applying first principles methods, machine learning, data mining, and text mining techniques to build analytics prototypes that work on massive datasets. Candidates should have experience in manipulating both structured and unstructured data in various formats, sizes, and storage-mechanisms. Candidates should have excellent problem-solving skills with an inquisitive mind to challenge existing practices. Candidates should have exposure to multiple programming languages and analytical tools and be flexible to using the requisite tools/languages for the problem at-hand.

Work Location: Chennai Please share your updated profile to sugantha.krishnan@acldigital.com Role & responsibilities Responsibilities: - Collecting, cleaning, and preprocessing data from various sources - Developing and applying machine learning algorithms and statistical models to solve business problems - Conducting exploratory data analysis and data visualization - Collaborating with cross-functional teams to identify business opportunities and develop data-driven solutions - Developing and deploying data pipelines and ETL processes - Communicating insights and findings to technical and non-technical stakeholders - Evaluating the effectiveness and accuracy of models and recommending improvements - Keeping up-to-date with the latest trends and technologies in the field of data science Qualifications - Minimum of 3 years' Relevant experience with Bachelors' or Masters' degree in STEM (Science, Technology, Engineering, and Mathematics) - Work experience where data science, data engineering and application development was a major part of your work in automating software deployments and following a continuous delivery and deployment model - Experience with mathematical & statistical modeling, Cloud environment, APIs, Kubernetes - Solid experience in program coding with Python, SQL,or R Programming - Experience in visualization tools like Power BI - Experience in data science, machine learning or artificial intelligence technologies