156 Seaborn Jobs - Page 6

We are seeking a talented and motivated Data Scientist with 1-3 years of experience to join our Data Science team. If you have a strong passion for data science, expertise in machine learning, and experience working with large-scale datasets, we want to hear from you. As a Data Scientist at RevX, you will play a crucial role in developing and implementing machine learning models to drive business impact. You will work closely with teams across data science, engineering, product, and campaign management to build predictive models, optimize algorithms, and deliver actionable insights. Your work will directly influence business strategy, product development, and campaign optimization. Major Responsibilities: Develop and implement machine learning models, particularly neural networks, decision trees, random forests, and XGBoost, to solve complex business problems. Work on deep learning models and other advanced techniques to enhance predictive accuracy and model performance. Analyze and interpret large, complex datasets using Python, SQL, and big data technologies to derive meaningful insights. Collaborate with cross-functional teams to design, build, and deploy end-to-end data science solutions, including data pipelines and model deployment frameworks. Utilize advanced statistical techniques and machine learning methodologies to optimize business strategies and outcomes. Evaluate and improve model performance, calibration, and deployment strategies for real-time applications. Perform clustering, segmentation, and other unsupervised learning techniques to discover patterns in large datasets. Conduct A/B testing and other experimental designs to validate model performance and business strategies. Create and maintain data visualizations and dashboards using tools such as matplotlib, seaborn, Grafana, and Looker to communicate findings. Provide technical expertise in handling big data, data warehousing, and cloud-based platforms like Google Cloud Platform (GCP). Required Experience/Skills: Bachelors or Masters degree in Data Science, Computer Science, Statistics, Mathematics, or a related field. 1-3 years of experience in data science or machine learning roles. Strong proficiency in Python for machine learning, data analysis, and deep learning applications. Experience in developing, deploying, and monitoring machine learning models, particularly neural networks, and other advanced algorithms. Expertise in handling big data technologies, with experience in tools such as BigQuery and cloud platforms (GCP preferred). Advanced SQL skills for data querying and manipulation from large datasets. Experience in data visualization tools like matplotlib, seaborn, Grafana, and Looker. Strong understanding of A/B testing, statistical tests, experimental design, and methodologies. Experience in clustering, segmentation, and other unsupervised learning techniques. Strong problem-solving skills and the ability to work with complex datasets and machine learning pipelines. Excellent communication skills, with the ability to explain complex technical concepts to non-technical stakeholders. Preferred Skills: Experience with deep learning frameworks such as TensorFlow or PyTorch. Familiarity with data warehousing concepts and big data tools. Knowledge of MLOps practices, including model deployment, monitoring, and management. Experience with business intelligence tools and creating data-driven dashboards. Understanding of reinforcement learning, natural language processing (NLP), or other advanced AI techniques. Education: Bachelor of Engineering or similar degree from any reputed University.

Research and Problem-Solving: Identify and frame business problems, conduct exploratory data analysis, and propose innovative data science solutions tailored to business needs. Leadership & Communication: Serve as a technical referent for the research team, driving high-impact, high-visibility initiatives. Effectively communicate complex scientific concepts to senior stakeholders, ensuring insights are actionable for both technical and non-technical audiences. Mentor and develop scientists within the team, fostering growth and technical excellence. Algorithm Development: Design, optimize, and implement advanced machine learning algorithms, including neural networks, ensemble models (XGBoost, random forests), and clustering techniques. End-to-End Project Ownership: Lead the development, deployment, and monitoring of machine learning models and data pipelines for large-scale applications. Model Optimization and Scalability: Focus on optimizing algorithms for performance and scalability, ensuring robust, well-calibrated models suitable for real-time environments. A/B Testing and Validation: Design and execute experiments, including A/B testing, to validate model effectiveness and business impat. Big Data Handling: Leverage tools like BigQuery, advanced SQL, and cloud platforms (e.g., GCP) to process and analyze large datasets. Collaboration and Mentorship: Work closely with engineering, product, and campaign management teams, while mentoring junior data scientists in best practices and advanced techniques. Data Visualization: Create impactful visualizations using tools like matplotlib, seaborn, Looker, and Grafana to communicate insights effectively to stakeholders. Required Experience/Skills 5–8 years of hands-on experience in data science or machine learning roles. 2+ years leading data science projects in AdTech Strong hands-on skills in Advanced Statistics, Machine Learning, and Deep Learning. Demonstrated ability to implement and optimize neural networks and other advanced ML models. Proficiency in Python for developing machine learning models, with a strong grasp of TensorFlow or PyTorch. Expertise handling large datasets using advanced SQL and big data tools like BigQuery In-depth knowledge of MLOps pipelines, from data preprocessing to deployment and monitoring. Strong background in A/B testing, statistical analysis, and experimental design. Proven capability in clustering, segmentation, and unsupervised learning methods. Strong problem-solving and analytical skills with a focus on delivering business value. Education: A Master’s in Data Science, Computer Science, Mathematics, Statistics, or a related field is preferred. A Bachelor's degree with exceptional experience will also be considered.

REF69967Q_2025151745 - Deputy Manager - Operations - Data science Roles & Responsibilities: Data Analysis: Analyse large datasets to extract meaningful insights and trends Model Development: Develop and implement predictive models and machine learning algorithms to solve business problems Data Cleaning: Ensure data quality by cleaning and pre-processing data Visualization: Create visualizations to present data insights using tools like Power BI or Python libraries (eg, Matplotlib, Seaborn) Collaboration: Work closely with data engineers, software developers, and business stakeholders to understand requirements and deliver solutions Reporting: Generate automated reports and dashboards to provide actionable insights Research: Stay updated with the latest trends and technologies in data science and machine learning Technical Skills Required: Programming Languages: Proficiency in Python and SQL Machine Learning: Experience with machine learning frameworks such as Scikit-learn, TensorFlow, or PyTorch Data Visualization: Skills in data visualization tools like Power BI, Matplotlib, Seaborn, or Plotly Statistical Analysis: Strong understanding of statistical methods and techniques Data Wrangling: Expertise in data wrangling and pre-processing using libraries like Pandas and NumPy Platforms like Power BI, Power Automate, Apps are good to have

Oversees development and implementation of data mining protocols, architectures, and models as well as data analysis methodologies, used to identify trends in large data sets. Implements new data mining and data analysis processes Required Candidate profile 2 or more years with relational or NoSQL databases (Oracle,Teradata,SQL Server,Hadoop,ELK) 3 or more years working with languages such as R,Python,Java 2 or more years skilled at data visualization

Job Posting TitleBUSINESS INTELLIGENCE ANALYST I Band/Level5-4-S Education ExperienceBachelors Degree (High School +4 years) Employment ExperienceLess than 1 year At TE, you will unleash your potential working with people from diverse backgrounds and industries to create a safer, sustainable and more connected world. Job Overview TE Connectivity s Business Intelligence Teams are responsible for the processing, mining and delivery of data to their customer community through repositories, tools and services. Roles & Responsibilities Tasks & Responsibilities Assist in the development and deployment of Digital Factory solutions and Machine Learning models across Manufacturing, Quality, and Supply Chain functions. Support data collection, cleaning, preparation, and transformation from multiple sources, ensuring data consistency and readiness. Contribute to the creation of dashboards and reports using tools such as Power BI or Tableau. Work on basic analytics and visualization tasks to derive insights and identify improvement areas. Assist in maintaining existing ML models, including data monitoring and model retraining processes. Participate in small-scale PoCs (proof of concepts) and pilot projects with senior team members. Document use cases, write clean code with guidance, and contribute to knowledge-sharing sessions Support integration of models into production environments and perform basic testing. Desired Candidate Proficiency in Python and/or R for data analysis, along with libraries like Pandas, NumPy, Matplotlib, Seaborn. Basic understanding of statistical concepts such as distributions, correlation, regression, and hypothesis testing. Familiarity with SQL or other database querying tools; e.g., pyodbc, sqlite3, PostgreSQL. Exposure to ML algorithms like linear/logistic regression, decision trees, k-NN, or SVM. Basic knowledge of Jupyter Notebooks and version control using Git/GitHub. Good communication skills in English (written and verbal), able to explain technical topics simply Collaborative, eager to learn, and adaptable in a fast-paced and multicultural environment. Exposure to or interest in manufacturing technologies (e.g., stamping, molding, assembly). Exposure to cloud platforms (AWS/Azure) or services like S3, SageMaker, Redshift is an advantage. Hands-on experience in image data preprocessing (resizing, Gaussian blur, PCA) or computer vision projects. Interest in AutoML tools and transfer learning techniques. Competencies ABOUT TE CONNECTIVITY TE Connectivity plc (NYSETEL) is a global industrial technology leader creating a safer, sustainable, productive, and connected future. Our broad range of connectivity and sensor solutions enable the distribution of power, signal and data to advance next-generation transportation, energy networks, automated factories, data centers, medical technology and more. With more than 85,000 employees, including 9,000 engineers, working alongside customers in approximately 130 countries, TE ensures that EVERY CONNECTION COUNTS. Learn more at www.te.com and on LinkedIn , Facebook , WeChat, Instagram and X (formerly Twitter). WHAT TE CONNECTIVITY OFFERS: We are pleased to offer you an exciting total package that can also be flexibly adapted to changing life situations - the well-being of our employees is our top priority! Competitive Salary Package Performance-Based Bonus Plans Health and Wellness Incentives Employee Stock Purchase Program Community Outreach Programs / Charity Events IMPORTANT NOTICE REGARDING RECRUITMENT FRAUD TE Connectivity has become aware of fraudulent recruitment activities being conducted by individuals or organizations falsely claiming to represent TE Connectivity. Please be advised that TE Connectivity never requests payment or fees from job applicants at any stage of the recruitment process. All legitimate job openings are posted exclusively on our official careers website at te.com/careers, and all email communications from our recruitment team will come only from actual email addresses ending in @te.com . If you receive any suspicious communications, we strongly advise you not to engage or provide any personal information, and to report the incident to your local authorities. Across our global sites and business units, we put together packages of benefits that are either supported by TE itself or provided by external service providers. In principle, the benefits offered can vary from site to site. Location

Project Role : AI / ML Engineer Project Role Description : Develops applications and systems that utilize AI tools, Cloud AI services, with proper cloud or on-prem application pipeline with production ready quality. Be able to apply GenAI models as part of the solution. Could also include but not limited to deep learning, neural networks, chatbots, image processing. Must have skills : Machine Learning Good to have skills : NA Minimum 12 year(s) of experience is required Educational Qualification : 15 years full time education Summary :These roles have many overlapping skills with GENAI Engineers and architects. Description may scaleup/scale down based on expected seniority. Roles & Responsibilities:-Implement generative AI models, identify insights that can be used to drive business decisions. Work closely with multi-functional teams to understand business problems, develop hypotheses, and test those hypotheses with data, collaborating with cross-functional teams to define AI project requirements and objectives, ensuring alignment with overall business goals.-Conducting research to stay up-to-date with the latest advancements in generative AI, machine learning, and deep learning techniques and identify opportunities to integrate them into our products and services.-Optimizing existing generative AI models for improved performance, scalability, and efficiency.-Ensure data quality and accuracy-Leading the design and development of prompt engineering strategies and techniques to optimize the performance and output of our GenAI models.-Implementing cutting-edge NLP techniques and prompt engineering methodologies to enhance the capabilities and efficiency of our GenAI models.-Determining the most effective prompt generation processes and approaches to drive innovation and excellence in the field of AI technology, collaborating with AI researchers and developers-Experience working with cloud based platforms (example:AWS, Azure or related)-Strong problem-solving and analytical skills-Proficiency in handling various data formats and sources through Omni Channel for Speech and voice applications, part of conversational AI-Prior statistical modelling experience-Demonstrable experience with deep learning algorithms and neural networks-Developing clear and concise documentation, including technical specifications, user guides, and presentations, to communicate complex AI concepts to both technical and non-technical stakeholders.-Contributing to the establishment of best practices and standards for generative AI development within the organization. Professional & Technical Skills:-Must have solid experience developing and implementing generative AI models, with a strong understanding of deep learning techniques such as GPT, VAE, and GANs.-Must be proficient in Python and have experience with machine learning libraries and frameworks such as TensorFlow, PyTorch, or Keras.-Must have strong knowledge of data structures, algorithms, and software engineering principles.-Must be familiar with cloud-based platforms and services, such as AWS, GCP, or Azure.-Need to have experience with natural language processing (NLP) techniques and tools, such as SpaCy, NLTK, or Hugging Face.-Must be familiar with data visualization tools and libraries, such as Matplotlib, Seaborn, or Plotly.-Need to have knowledge of software development methodologies, such as Agile or Scrum.-Possess excellent problem-solving skills, with the ability to think critically and creatively to develop innovative AI solutions. Additional Information:-Must have a degree in Computer Science, Artificial Intelligence, Machine Learning, or a related field. A Ph.D. is highly desirable.-strong communication skills, with the ability to effectively convey complex technical concepts to a diverse audience.-You possess a proactive mindset, with the ability to work independently and collaboratively in a fast-paced, dynamic environment. Additional Information: The candidate should have a minimum of 5 years of real time experience in Machine Learning. A 15 years full time education is required. Qualifications 15 years full time education

Project Role : AI / ML Engineer Project Role Description : Develops applications and systems that utilize AI tools, Cloud AI services, with proper cloud or on-prem application pipeline with production ready quality. Be able to apply GenAI models as part of the solution. Could also include but not limited to deep learning, neural networks, chatbots, image processing. Must have skills : Machine Learning Good to have skills : NA Minimum 5 year(s) of experience is required Educational Qualification : 15 years full time education Summary :These roles have many overlapping skills with GENAI Engineers and architects. Description may scaleup/scale down based on expected seniority. Roles & Responsibilities:-Implement generative AI models, identify insights that can be used to drive business decisions. Work closely with multi-functional teams to understand business problems, develop hypotheses, and test those hypotheses with data, collaborating with cross-functional teams to define AI project requirements and objectives, ensuring alignment with overall business goals.-Conducting research to stay up-to-date with the latest advancements in generative AI, machine learning, and deep learning techniques and identify opportunities to integrate them into our products and services.-Optimizing existing generative AI models for improved performance, scalability, and efficiency.-Ensure data quality and accuracy-Leading the design and development of prompt engineering strategies and techniques to optimize the performance and output of our GenAI models.-Implementing cutting-edge NLP techniques and prompt engineering methodologies to enhance the capabilities and efficiency of our GenAI models.-Determining the most effective prompt generation processes and approaches to drive innovation and excellence in the field of AI technology, collaborating with AI researchers and developers-Experience working with cloud based platforms (example:AWS, Azure or related)-Strong problem-solving and analytical skills-Proficiency in handling various data formats and sources through Omni Channel for Speech and voice applications, part of conversational AI-Prior statistical modelling experience-Demonstrable experience with deep learning algorithms and neural networks-Developing clear and concise documentation, including technical specifications, user guides, and presentations, to communicate complex AI concepts to both technical and non-technical stakeholders.-Contributing to the establishment of best practices and standards for generative AI development within the organization. Professional & Technical Skills:-Must have solid experience developing and implementing generative AI models, with a strong understanding of deep learning techniques such as GPT, VAE, and GANs.-Must be proficient in Python and have experience with machine learning libraries and frameworks such as TensorFlow, PyTorch, or Keras.-Must have strong knowledge of data structures, algorithms, and software engineering principles.-Must be familiar with cloud-based platforms and services, such as AWS, GCP, or Azure.-Need to have experience with natural language processing (NLP) techniques and tools, such as SpaCy, NLTK, or Hugging Face.-Must be familiar with data visualization tools and libraries, such as Matplotlib, Seaborn, or Plotly.-Need to have knowledge of software development methodologies, such as Agile or Scrum.-Possess excellent problem-solving skills, with the ability to think critically and creatively to develop innovative AI solutions. Additional Information:-Must have a degree in Computer Science, Artificial Intelligence, Machine Learning, or a related field. A Ph.D. is highly desirable.-strong communication skills, with the ability to effectively convey complex technical concepts to a diverse audience.-You possess a proactive mindset, with the ability to work independently and collaboratively in a fast-paced, dynamic environment. Additional Information: The candidate should have a minimum of 5 years of real time experience in Machine Learning. A 15 years full time education is required. Qualifications 15 years full time education

We are looking for an experienced and passionate Data Science Trainer who can deliver high-quality training to students, working professionals, and corporate clients. The ideal candidate should be proficient in the latest tools and technologies in the data science field and have a passion for teaching and mentoring. Key Responsibilities: Deliver Engaging Training Sessions: Conduct in-depth, interactive training sessions (online/offline) on core Data Science topics, including Python programming, statistics, machine learning, and data visualization. Curriculum Development: Design, structure, and regularly update course content, projects, and assessments based on current industry standards and student needs. Hands-On Project Guidance: Mentor students on capstone and real-time projects using real-world datasets to strengthen their practical skills and portfolio. Technical Evaluation: Develop and assess assignments, quizzes, and case studies to measure students progress and provide constructive feedback. Interview Preparation: Conduct mock interviews, technical tests, and soft skills sessions to prepare students for job placements in data-related roles. Technology Upgradation: Stay updated with evolving tools and technologies like TensorFlow, Power BI, Tableau, Spark, and integrate them into training modules as needed. Mentorship & Support: Provide personalized mentorship and career guidance to help learners overcome challenges and reach their goals. Corporate & Workshop Training (Optional): Conduct specialized workshops, webinars, and corporate training sessions based on demand. Key Skills Required: Strong knowledge of Python , NumPy , Pandas , Matplotlib , Seaborn Proficiency in Machine Learning (Supervised & Unsupervised algorithms) Hands-on experience with Scikit-learn , TensorFlow , or Keras Familiarity with SQL , Statistics , Data Wrangling , and Data Visualization Exposure to Deep Learning , NLP , and Big Data Tools is a plus Experience with platforms like Jupyter Notebook , Google Colab Strong communication and presentation skills Why Join Uncodemy? Work with a passionate and skilled team of trainers. Opportunity to shape the careers of aspiring professionals. Flexible working hours and a positive work environment.

Job Type Full time Job Description Key Responsibilities: Analyze large datasets to extract actionable insights and drive data-driven decision-making. Develop predictive models and machine learning algorithms to solve business problems. Design and implement data preprocessing, feature engineering, and model training pipelines. Collaborate with cross-functional teams to understand business requirements and translate them into analytical solutions. Communicate findings and recommendations to stakeholders through data visualization and storytelling. Stay abreast of the latest developments in data science, machine learning, and AI technologies. Required Skills: 3-4 years of hands-on experience in data analysis and machine learning. Proficiency in programming languages such as Python or R for data manipulation and analysis. Experience with machine learning libraries/frameworks such as scikit-learn, TensorFlow, or PyTorch. Strong understanding of statistical concepts and techniques. Experience with data visualization tools such as Matplotlib, Seaborn, or Tableau. Familiarity with SQL and relational databases for data querying and manipulation. Excellent problem-solving and analytical skills, with attention to detail. Good communication and collaboration skills, with the ability to work effectively in a team environment.

Sr.Analyst Instructional Designer (Tech Content Strategist) – Data Job Overview Are you a certified Data professional with a creative flair and a passion for content design? Join us to create impactful, learner-centered content that blends real-world expertise with engaging storytelling. As a Sr. Analyst – Tech Content Strategist, you will lead the end-to-end development of engaging, instructionally sound learning experiences in the Data domain. Acting as a subject matter expert (SME), you’ll translate complex frameworks into clear, outcome-focused content across digital formats. This role demands strong instructional design expertise, a deep understanding of learner needs, and the ability to creatively script and plan high-impact learning assets—from video courses to assessments. Job Responsibilities Own the content development lifecycle—plan, research, script, storyboard review, strategic video review and iterate—for Data Design creative and effective learning experiences grounded in instructional design principles, addressing diverse learner personas and real-world scenarios. Author and script engaging digital content, including on-demand videos, interactive walkthroughs/lessons, assessments, and job aids. Collaborate with visual designers, editors, and technical experts to bring content to life in a compelling and accessible format. Align content with industry certification frameworks (e.g., Microsoft Certified, CAP, Azure, Oracle, AWS, CompTIA) and learner performance outcomes. Apply learner-centered design by identifying learning gaps and tailoring content that improves retention, engagement, and job readiness. Utilize Generative AI tools to accelerate and enhance content ideation, scripting, and personalization while maintaining content quality. Ensure instructional consistency, voice, and quality across all course deliverables and formats. Optionally support bootcamps (virtual training delivery) and mentor junior content developers. Skills Required Minimum 5+ years of hands-on experience in data analytics, data visualization, or other data fields. Demonstrated experience in instructional design, especially in developing digital learning products from concept to delivery. Excellent scripting, writing, and communication skills; able to distill complex concepts into concise, engaging narratives. Strong creativity and storytelling ability with an understanding of how to structure content for different learning styles. Fluency with and experience in programming such as Python and SQL. Fluency and experience with data libraries such as NumPy, Pandas, Sci-kit Learn, Seaborn. Experience working with data technology and topics such as Tableau, PowerBI, Excel, Natural Language Processing, and Reinforcement Learning. Relevant certifications in Data. Preferred/Additional Skills: Familiarity with Generative AI tools like ChatGPT, Claude, or similar for content creation and enhancement. Training delivery experience (live/ virtual/ hybrid formats) is an added advantage. Understanding of instructional design models such as ADDIE, SAM, or Bloom’s Taxonomy. Experience in analyzing learner feedback and improving content based on performance and engagement data.

Python Developer Location: Bengaluru, Karnataka, India Experience Level: 3–5 Years Employment Type: Full-Time Role Overview We are seeking a skilled Python Developer with a strong background in data manipulation and analysis using NumPy and Pandas, coupled with proficiency in SQL. The ideal candidate will have experience in building and optimizing data pipelines, ensuring efficient data processing and integration. Key Responsibilities Develop and maintain robust data pipelines and ETL processes using Python, NumPy, and Pandas. Write efficient SQL queries for data extraction, transformation, and loading. Collaborate with cross-functional teams to understand data requirements and deliver solutions. Implement data validation and quality checks to ensure data integrity. Optimize existing codebases for performance and scalability. Document processes and maintain clear records of data workflows. Required Qualifications Bachelor’s degree in Computer Science, Engineering, or a related field. 2–5 years of professional experience in Python development. Proficiency in NumPy and Pandas for data manipulation and analysis. Strong command of SQL and experience with relational databases like MySQL, PostgreSQL, or SQL Server. Familiarity with version control systems, particularly Git. Experience with data visualization tools and libraries is a plus. Preferred Skills Experience with data visualization libraries such as Matplotlib or Seaborn. Familiarity with cloud platforms like AWS, Azure, or GCP. Knowledge of big data tools and frameworks like Spark or Hadoop. Understanding of machine learning concepts and libraries. Why Join Enterprise Minds Enterprise Minds is a forward-thinking technology consulting firm dedicated to delivering next-generation solutions. By joining our team, you'll work on impactful projects, collaborate with industry experts, and contribute to innovative solutions that drive business transformation.

Entity :- Accenture Strategy & Consulting Team :- Strategy & Consulting Global Network Practice :- Communications & Media - AI & Data Architectures Title :- Ind & Func AI Value Strategy Manager Job location :- Bangalore, Hyderabad About S&C - Global Network:- Accenture Strategy & Consulting Global Network - Data & AI practice help our clients grow their business in entirely new ways. Analytics enables our clients to achieve high performance through insights from data - insights that inform better decisions and strengthen customer relationships. From strategy to execution, Accenture works with organizations to develop analytic capabilities - from accessing and reporting on data to predictive modelling - to outperform the competition. WHAT'S IN IT FOR YOU? Accenture has committed to invest USD 3Billion into GenAI in the next 3 years. We will continually invest in your learning and growth. Youll work with Accenture's highly skilled and experienced practitioners, and Accenture will support you in growing your own career path and interests. You'll be part of a diverse, vibrant, global Accenture Data and AI community, continually pushing the boundaries of business capabilities. What you would do in this role ML Maturity Assessment: Conduct comprehensive assessments of the organizations ML maturity, identifying strengths, weaknesses, and areas for improvement. Provide strategic recommendations to enhance the overall ML capability and align it with business objectives. ML Ops Roadmap & Processes: Develop ML Ops roadmaps and establish robust processes for the end-to-end machine learning lifecycle, including data preparation, model training, deployment, and monitoring. Implement best practices in ML Ops to ensure efficiency, scalability, and reliability of ML systems. Implementation of Gen AI Solutions: Lead the design and implementation of state-of-the-art Generative AI solutions, leveraging deep learning frameworks such as TensorFlow and PyTorch. Drive innovation in Gen AI, staying abreast of the latest advancements and incorporating cutting-edge technologies into solutions. Incubating and Designing: Proactively identify opportunities for ML and Gen AI applications within the organization. Work closely with cross-functional teams to incubate and design bespoke ML solutions tailored to business requirements. Technical Leadership: Provide technical leadership and mentorship to data scientists, engineers, and other team members. Collaborate with stakeholders to ensure alignment between technical solutions and business objectives. Collaboration and Communication: Collaborate with business stakeholders to understand their needs and translate them into ML and Gen AI requirements. Effectively communicate complex technical concepts to non-technical audiences. Qualifications Who we are looking for? Bachelors or advanced degree in Computer Science, Data Science, or a related field. Over 12 years of hands-on experience in machine learning, with a focus on architecting end-to-end solutions. Proven expertise in conducting ML maturity assessments and developing ML Ops roadmaps. Demonstrable hands-on experience in designing & flawlessly operationalizing the Machine learning system on a cloud and / or an On-Prem platform. Extensive experience in implementing Generative AI solutions, including incubation, design, and deployment. Strong proficiency in deep learning frameworks such as TensorFlow and PyTorch. In-depth knowledge of ML Ops best practices and processes. Excellent problem-solving skills and ability to design scalable and reliable ML architectures. Strong leadership and communication skills, with a track record of leading successful ML initiatives. Experience in Telecom or Hi Tech or Software and platform industry desirable Tools & Techniques: TensorFlow, PyTorch, Scikit-learn, Keras NumPy, Pandas Matplotlib, Seaborn TensorFlow Serving, Docker and Kubernetes Good software engineering practices, including code modularization, documentation, and testing. Experience with API , Integration architecture , microservices If you are a visionary Machine Learning Architect with a passion for advancing ML maturity, implementing cutting-edge Gen AI solutions, and driving innovation, we invite you to apply and contribute to our organizations success. Accenture is an equal opportunities employer and welcomes applications from all sections of society and does not discriminate on grounds of race, religion or belief, ethnic or national origin, disability, age, citizenship, marital, domestic or civil partnership status, sexual orientation, gender identity, or any other basis as protected by applicable law.

Project Role : AI / ML Engineer Project Role Description : Develops applications and systems that utilize AI tools, Cloud AI services, with proper cloud or on-prem application pipeline with production ready quality. Be able to apply GenAI models as part of the solution. Could also include but not limited to deep learning, neural networks, chatbots, image processing. Must have skills : Machine Learning Good to have skills : NA Minimum 3 year(s) of experience is required Educational Qualification : 15 years full time education Summary :These roles have many overlapping skills with GENAI Engineers and architects. Description may scaleup/scale down based on expected seniority. Roles & Responsibilities:-Implement generative AI models, identify insights that can be used to drive business decisions. Work closely with multi-functional teams to understand business problems, develop hypotheses, and test those hypotheses with data, collaborating with cross-functional teams to define AI project requirements and objectives, ensuring alignment with overall business goals.-Conducting research to stay up-to-date with the latest advancements in generative AI, machine learning, and deep learning techniques and identify opportunities to integrate them into our products and services.-Optimizing existing generative AI models for improved performance, scalability, and efficiency.-Ensure data quality and accuracy-Leading the design and development of prompt engineering strategies and techniques to optimize the performance and output of our GenAI models.-Implementing cutting-edge NLP techniques and prompt engineering methodologies to enhance the capabilities and efficiency of our GenAI models.-Determining the most effective prompt generation processes and approaches to drive innovation and excellence in the field of AI technology, collaborating with AI researchers and developers-Experience working with cloud based platforms (example:AWS, Azure or related)-Strong problem-solving and analytical skills-Proficiency in handling various data formats and sources through Omni Channel for Speech and voice applications, part of conversational AI-Prior statistical modelling experience-Demonstrable experience with deep learning algorithms and neural networks-Developing clear and concise documentation, including technical specifications, user guides, and presentations, to communicate complex AI concepts to both technical and non-technical stakeholders.-Contributing to the establishment of best practices and standards for generative AI development within the organization. Professional & Technical Skills:-Must have solid experience developing and implementing generative AI models, with a strong understanding of deep learning techniques such as GPT, VAE, and GANs.-Must be proficient in Python and have experience with machine learning libraries and frameworks such as TensorFlow, PyTorch, or Keras.-Must have strong knowledge of data structures, algorithms, and software engineering principles.-Must be familiar with cloud-based platforms and services, such as AWS, GCP, or Azure.-Need to have experience with natural language processing (NLP) techniques and tools, such as SpaCy, NLTK, or Hugging Face.-Must be familiar with data visualization tools and libraries, such as Matplotlib, Seaborn, or Plotly.-Need to have knowledge of software development methodologies, such as Agile or Scrum.-Possess excellent problem-solving skills, with the ability to think critically and creatively to develop innovative AI solutions. Additional Information:-Must have a degree in Computer Science, Artificial Intelligence, Machine Learning, or a related field. A Ph.D. is highly desirable.-strong communication skills, with the ability to effectively convey complex technical concepts to a diverse audience.-You possess a proactive mindset, with the ability to work independently and collaboratively in a fast-paced, dynamic environment. Qualifications 15 years full time education

Responsibilities: 1. Data Mining & Predictive Analytics Analyze large-scale healthcare datasets, including EHRs, claims data, and operational databases. Apply machine learning algorithms and statistical methods to identify trends, anomalies, and patterns related to patient outcomes and healthcare delivery. Develop predictive models to forecast health risks and treatment responses for proactive care planning. Use tools such as Python (Pandas, NumPy, Scikit-learn, TensorFlow) , SQL , Hadoop , Spark , and NoSQL databases . 2. Data Slicing, Dicing & OLAP Analysis Perform data segmentation based on demographics, conditions, or treatment histories to support targeted analysis. Conduct OLAP operations like drill-down, slicing and dicing to explore multi-dimensional views of healthcare data. Utilize tools such as SQL , Excel , Power BI , Tableau , and Python libraries ( Matplotlib , Seaborn ). 3. Data Visualization & Reporting Create intuitive dashboards and reports that communicate KPIs, patient outcomes, and performance metrics to various stakeholders. Design and develop visual representations (bar charts, heatmaps, flow diagrams) to make complex data accessible and actionable. Ensure clarity, accuracy, and transparency in all visual communications using tools like Power BI , Tableau , D3.js , Matplotlib , and Seaborn . Example Datasets Youll Work With: Clinical Data : EHRs, medication records, patient history. Operational Data : Facility management, staff allocation. Financial Data : Insurance claims, billing, cost metrics. Outcome Data : Patient satisfaction, readmission rates, treatment efficacy. Qualifications: Bachelors or Masters in Computer Science, Data Science, Health Informatics, Biostatistics, or a related field. 3–6 years of experience in healthcare data analytics or a related domain. Proficiency in SQL, Python, and data visualization platforms (Power BI, Tableau). Experience working with large healthcare datasets and machine learning models. Strong understanding of healthcare operations and data privacy standards (e.g., HIPAA).

#ONSITE We are looking for a highly experienced NLP Analyst with deep expertise in linguistic data analysis, annotation design, and production-scale NLP model evaluation. This role requires a blend of linguistic acumen, analytical rigor, and real-world application experience. You will drive the design and execution of NLP initiatives across diverse domains and guide cross-functional teams on best practices in language data handling and annotation quality. Key Responsibilities Manage large-scale text annotation and labeling pipelines for supervised and semi-supervised learning. Conduct advanced linguistic analysis of unstructured content (e.g., clinical notes, legal contracts, customer communications, claim documents) to identify patterns, gaps, and modeling opportunities. Define and enforce annotation schemas and QA protocols for complex NLP tasks (e.g., NER, relation extraction, coreference resolution, sentiment/intent classification). Evaluate and improve the performance of NLP models through rigorous error analysis and metric-driven feedback loops. Collaborate with ML/NLP engineers, data scientists, and domain experts to build robust NLP pipelines that scale across use cases. Lead internal research efforts on emerging NLP methodologies, including LLM prompt engineering, hybrid rule-learning approaches, and few-shot learning. Provide mentorship to junior analysts and contribute to developing internal NLP knowledge repositories and annotation standards. Required Qualifications Master’s in computational Linguistics, NLP, Data Science, Computer Science, or a related field. 5+ years of professional experience in NLP, with a strong track record of hands-on work in data annotation, language model evaluation, and NLP pipeline development. Expertise in Python and key NLP libraries (spaCy, NLTK, Scikit-learn, Hugging Face Transformers, etc.). Advanced proficiency in building and managing annotation workflows using tools like Prodigy, doccano, Brat, or in-house platforms. Deep understanding of linguistic structures (syntax, semantics, pragmatics) and their application to real-world NLP challenges. Experience evaluating ML/NLP models using metrics like F1, ROUGE, BLEU, precision/recall, and embedding-based similarity. Solid grasp of vectorization methods (TF-IDF, embeddings, transformer-based encodings) and modern language models (e.g., BERT, GPT, LLaMA). Preferred Qualifications Experience with domain-specific NLP (e.g., clinical/biomedical, legal, fintech). Knowledge of knowledge graph construction, relation extraction, and entity linking. Experience integrating structured/unstructured data for downstream AI/ML applications. Familiarity with prompt engineering for LLMs and tuning foundation models. Strong data querying and visualization skills (SQL, pandas, seaborn, Power BI/Tableau). Perficient is always looking for the best and brightest talent and we need you! We’re a quickly-growing, global digital consulting leader, and we’re transforming the world’s largest enterprises and biggest brands. You’ll work with the latest technologies, expand your skills, and become a part of our global community of talented, diverse, and knowledgeable colleagues.

Role & responsibilities Strong knowledge of Probability Theory, Statistics, and a deep understanding of the Mathematics behind Machine Learning Proficiency with CRISP-ML(Q) or TDSP methodologies for addressing commercial problems through data science solutions Proficiency in Python for developing machine learning models and conducting statistical analyses Strong understanding of data visualization tools and techniques (e.g., Python libraries such as Matplotlib, Seaborn, Plotly, etc.) and the ability to present data effectively Specific technical requirements: Proficiency in SQL for data processing, data manipulation, sampling, and reporting Experience working with imbalanced datasets and applying appropriate techniques Experience with time series data, including preprocessing, feature engineering, and forecasting Experience with outlier detection and anomaly detection Experience working with various data types: text, image, and video data Familiarity with AI/ML cloud implementations (AWS, Azure, GCP) and cloud-based AI/ML services (e.g., Amazon SageMaker, Azure ML) Domain experience: Experience with analyzing medical signals and images Expertise in building predictive models for patient outcomes, disease progression, readmissions, and population health risks Experience in extracting insights from clinical notes, medical literature, and patient-reported data using NLP and text mining techniques Familiarity with survival or time-to-event analysis Expertise in designing and analyzing data from clinical trials or research studies Experience in identifying causal relationships between treatments and outcomes, such as propensity score matching or instrumental variable techniques Understanding of healthcare regulations and standards like HIPAA, GDPR (for healthcare data), and FDA regulations for medical devices and AI in healthcare Expertise in handling sensitive healthcare data in a secure, compliant way, understanding the complexities of patient consent, de-identification, and data sharing Familiarity with decentralized data models such as federated learning to build models without transferring patient data across institutions Knowledge of interoperability standards such as HL7, SNOMED, FHIR, or DICOM Ability to work with clinicians, researchers, health administrators, and policy makers to understand problems and translate data into actionable healthcare insights Preferred candidate profile Experience with MLOps, including integration of machine learning pipelines into production environments, Docker, and containerization/orchestration (e.g., Kubernetes) Experience in deep learning development using TensorFlow or PyTorch libraries Experience with Large Language Models (LLMs) and Generative AI applications Advanced SQL proficiency, with experience in MS SQL Server or PostgreSQL Familiarity with platforms like Databricks and Snowflake for data engineering and analytics Experience working with Big Data technologies (e.g., Hadoop, Apache Spark) Familiarity with NoSQL databases (e.g., columnar or graph databases like Cassandra, Neo4j)

What you'll be doing Lead development of advanced machine learning and statistical models Design scalable data pipelines using PySpark Perform data transformation and exploratory analysis using Pandas, Numpy and SQL Build, train and fine tune machine learning and deep learning models using TensorFlow and PyTorch Mentor junior engineers and lead code reviews, best practices and documentation. Designing and implementing big data, streaming AI/ML training and prediction pipelines. Translate complex business problems into data driven solutions. Promote best practices in data science, and model governance . Stay ahead with evolving technologies and guide strategic data initiatives. What we're looking for You'll need to have: Bachelor's degree or four or more years of work experience. Experience in Python, PySpark and SQL. Strong proficiency in Pandas, Numpy, Excel, Plotly, Matplotlib, Seaborn, ETL, AWS and Sagemaker Experience in Supervised learning models: Regression, Classification and Unsupervised learning models: Anomaly detection, clustering. Extensive experience with AWS analytics services, including Redshift, Glue, Athena, Lambda, and Kinesis. Knowledge in Deep Learning Autoencoders, CNN. RNN, LSTM, hybrid models Experience in Model evaluation, cross validation, hyper parameters tuning Familiarity with data visualization tools and techniques. Even better if you have one or more of the following: Experience with machine learning and statistical analysis. Experience in Hypothesis testing. Excellent communication skills with the ability to translate complex technical concepts to non-technical stakeholders.

Responsibilities: - Interpret data, analyze results using statistical techniques, and provide ongoing reports. - Develop and implement reporting infrastructure, interactive dashboards, and other analytical tools to provide insight into the data. - Acquire data from primary or secondary data sources and highlight any issues in the existing databases/data systems. - Identify, analyze, and interpret trends or patterns in complex data sets. - Develop regression and forecasting models using historical data to predict the future performance of the portfolio. - Work with management to prioritize business and information needs. - Locate and define new process improvement opportunities. Requirements : - Bachelor's or Master's degree in statistics/mathematics/engineering. - 2+ years of experience as a Data Analyst or Business Data Analyst. - Technical Expertise in data models, database design, development, data mining, and segmentation techniques. - Strong knowledge of and experience with Excel, SQL, Python, and dashboarding tools such as Metabase, Tableau, etc. - Develop regression and forecasting models using historical data to predict the future performance of the portfolio. - Knowledge of statistics and experience using statistical packages for analyzing and visualizing datasets (Pandas, NumPy, sci-kit-learn, Seaborn). - Strong analytical skills with the ability to collect, organize, analyze, and disseminate significant amounts of information with attention to detail and accuracy. - Keen interest in solving problems using data and providing a new perspective to stakeholders.

Collect, analyze, and visualize data to uncover insights and guide business decisions. Use SQL and analytical tools to identify trends, create reports, and collaborate with teams to drive data-informed strategies.

Must have skills required : Machine Learning, Data Visualization, Model evaluation, coding skills, Statistical Data Analysis Good to have skills :LLMs We are looking for a Data Scientist 2 to join our Bangalore team and work on problems in areas like product matching, product tagging, etc. Roles and responsibilities: Understand the business problem and provide data science solutions. Carry out proof of concept for data science problems. Collaborate with product and engineering teams to build data science solutions ( end to end ) Do exploratory data analysis to support existing and future data science projects. Build dashboards to monitor the data science project's performance and communicate the metrics to the business team. Preferred Qualifications: Work Experience : 3+ Years of data science experience Machine Learning Knowledge: Well versed with machine learning concepts and have built ML projects end to end. Understanding of mathematical concepts behind ML models. Statistical Data Analysis: Proficiency in applying statistical techniques to analyze data and generate useful business insights. Data Visualization: Skill in creating meaningful visualizations of complex data sets using tools like Tableau, PowerBI, or Python libraries (e.g., Matplotlib, Seaborn). Model Evaluation and Tuning: Knowledge of techniques for evaluating and improving the performance of machine learning models. Coding Skills: Strong coding skills in Python. Able to write modular and reusable code. Good to have experience of using LLMs for data science solutions .

Role Python Developer Location Bangalore Experience4 - 7 Yrs Employment Type Full Time, Working mode Regular Notice Period Immediate - 15 Days About the Role : We are seeking a skilled Python Developer to join our dynamic team and contribute to the development of innovative data-driven solutions. The ideal candidate will have a strong foundation in Python programming, data analysis, and data processing techniques. This role will involve working with various data sources, including Redis, MongoDB, SQL, and Linux, to extract, transform, and analyze data for valuable insights. You will also be responsible for developing and maintaining efficient and scalable data pipelines and visualizations using tools like matplotlib and seaborn. Additionally, experience with web development frameworks such as Flask, FastAPI, or Django, as well as microservices architecture, will be a significant advantage. Key Responsibilities : - Design, develop, and maintain efficient and scalable data pipelines to extract, transform, and load (ETL) data from various sources, including Redis, MongoDB, SQL, and Linux. - Conduct in-depth data analysis and processing using Python libraries and tools to uncover valuable insights and trends. - Develop and maintain data visualizations using matplotlib, seaborn, or other relevant tools to effectively communicate findings to stakeholders. - Collaborate with cross-functional teams to understand business requirements and translate them into technical solutions. - Develop and maintain web applications using Python frameworks like Flask, FastAPI, or Django, adhering to best practices and coding standards. - Design and implement microservices architecture to build scalable and modular systems. - Troubleshoot and resolve technical issues related to data pipelines, applications, and infrastructure. - Stay updated with the latest trends and technologies in the data engineering and Python development landscape. Required Skills and Qualifications : - Strong proficiency in Python programming, including object-oriented programming and functional programming concepts. - Experience with data analysis and processing libraries such as pandas, NumPy, and scikit-learn. - Familiarity with data storage and retrieval technologies, including Redis, MongoDB, SQL, and Linux. - Knowledge of data visualization tools like matplotlib and seaborn. - Experience with web development frameworks such as Flask, FastAPI, or Django. - Understanding of microservices architecture and principles. - Excellent problem-solving and analytical skills. - Ability to work independently and as part of a team. - Strong communication and interpersonal skills. Preferred Skills and Qualifications : - Experience with cloud platforms (AWS, GCP, Azure). - Knowledge of containerization technologies (Docker, Kubernetes). - Familiarity with data warehousing and data lake concepts. - Experience with machine learning and deep learning frameworks (TensorFlow, PyTorch). Apply Insights Follow-up Save this job for future reference Did you find something suspiciousReport Here! Hide This Job Click here to hide this job for you. You can also choose to hide all the jobs from the recruiter.

Responsibilities : - Gather data from various sources (databases, spreadsheets, APIs, etc. - Identify, clean, and transform data to ensure accuracy, consistency, and integrity. - Develop and maintain data pipelines and processes for efficient data handling. - Conduct exploratory data analysis to identify trends, patterns, correlations, and anomalies. - Apply statistical techniques and data visualization tools to analyze datasets. - Interpret data and provide meaningful insights and recommendations. - Develop and maintain reports, dashboards, and other data visualizations to communicate findings effectively. - Work closely with stakeholders from different departments to understand their data needs and business questions. - Present data findings and insights in a clear and concise manner to both technical and non-technical audiences. - Participate in discussions and contribute to data-driven decision-making processes. - Document data sources, methodologies, and analysis processes. - Utilize data analysis tools and software such as Excel, SQL, and data visualization platforms (i.e. Tableau, Power BI). - Learn and adapt to new data analysis tools and technologies as needed. - May involve basic scripting or programming for data manipulation (i.e. Python). - Identify opportunities to improve data collection, analysis, and reporting processes. - Stay updated on the latest trends and best practices in data analysis. - Contribute to the development of data governance and quality standards. Qualifications - Bachelor's degree in a quantitative field such as Statistics, Mathematics, Economics, Computer Science, or a related discipline. - 1-3 years of professional experience in a data analysis role. - Strong understanding of statistical concepts and data analysis techniques. - Proficiency in SQL for querying and manipulating data from databases. - Excellent skills in Microsoft Excel, including advanced formulas and data manipulation techniques. - Experience with at least one data visualization tool such as Tableau, Power BI, or similar. - Ability to interpret data, identify patterns, and draw meaningful conclusions. - Strong analytical and problem-solving skills. - Excellent communication and presentation skills, with the ability to explain technical findings to non-technical audiences. - Strong attention to detail and a commitment to data accuracy. - Ability to work independently and as part of a team. Preferred Skills - Experience with programming languages such as Python (especially libraries like Pandas, NumPy, Matplotlib, Seaborn). - Familiarity with cloud-based data platforms (i.e., AWS, Azure, GCP). - Experience with data warehousing concepts. - Knowledge of statistical software packages (i.e., R, SPSS). - Experience with different data modeling techniques. - Exposure to machine learning concepts. - Experience working with specific industry data (i.e., marketing, sales, finance) Apply Insights Follow-up Save this job for future reference Did you find something suspiciousReport Here! Hide This Job Click here to hide this job for you. You can also choose to hide all the jobs from the recruiter.

We are looking for a skilled Data Analyst with 3 to 6 years of experience to join our team in Bengaluru. The ideal candidate will be responsible for transforming data into actionable insights and supporting decision-making in a global organization focused on pricing and commercial strategy. ### Roles and Responsibility Analyze and interpret structured and unstructured data using statistical and quantitative methods to generate actionable insights and ongoing reports. Design and implement data pipelines and processes for data cleaning, transformation, modeling, and visualization using tools such as Power BI, SQL, and Python. Collaborate with stakeholders to define requirements, prioritize business needs, and translate problems into analytical solutions. Develop, maintain, and enhance scalable analytics solutions and dashboards that support pricing strategy and commercial decision-making. Identify opportunities for process improvement and operational efficiency through data-driven recommendations. Communicate complex findings clearly and concisely to both technical and non-technical audiences. ### Job Requirements Proven experience as a data analyst, business analyst, data engineer, or similar role. Strong analytical skills with the ability to collect, organize, analyze, and present large datasets accurately. Foundational knowledge of statistics, including concepts like distributions, variance, and correlation. Skilled in documenting processes and presenting findings to both technical and non-technical audiences. Hands-on experience with Power BI for designing, developing, and maintaining analytics solutions. Proficient in both Python and SQL, with strong programming and scripting skills. Skilled in using Pandas, T-SQL, and Power Query M for querying, transforming, and cleaning data. Hands-on experience in data modeling for both transactional (OLTP) and analytical (OLAP) database systems. Strong visualization skills using Power BI and Python libraries such as Matplotlib and Seaborn. Experience with defining and designing KPIs and aligning data insights with business goals. A bachelor’s degree in a STEM field relevant to data analysis, data engineering, or data science is required. 3–6 years of experience in data analysis, data engineering, or a closely related field, ideally within a professional services environment. ### Additional Info The company offers a dynamic work environment and opportunities for growth and development.

We are looking for a highly skilled and experienced professional with 3 to 6 years of experience to join our team as an Analyst in the TAX-TAX-Other department, located in Bangalore. The ideal candidate will have a strong background in tax and transaction services. ### Roles and Responsibility Develop complex, consumer-facing desktop and web applications using Excel automation with Python. Utilize Pandas, Numpy, Tkinter, FlaskAPI, SQL, xLwriter, ModinPandas, Sklearn, Pyodbc, Pymongo, and matplotlib/seaborn libraries for data re-engineering, wrangling, and manipulation in Excel. Design window interfaces using tkinter/Pyautogui and automate email processes using Python. Collaborate with cross-functional teams to provide services across multiple client departments while adhering to commercial and legal requirements. Deliver insightful and practical solutions to complex problems with a practical approach. Work on big-data equivalent datasets and leverage machine learning models/training/plotting techniques. ### Job Requirements Minimum 3 years of experience in developing complex, consumer-facing desktop and web applications using Excel automation with Python. Strong knowledge of Pandas, Numpy, Tkinter, FlaskAPI, SQL, xLwriter, ModinPandas, Sklearn, Pyodbc, Pymongo, and matplotlib/seaborn libraries. Experience with Web Scraping and Selenium automation using Python. Ability to work collaboratively to provide services across multiple client departments. Practical approach to solving issues and complex problems. Exposure to Machine Learning Models/Training/Plotting is an added advantage. Qualification: Engineering, MCA, or equivalent.

Strong programming skills in Python or R, with good knowledge in data manipulation, analysis, and visualization libraries (pandas, numpy, matplotlib, seaborn) Knowledge of machine learning techniques algorithms. FMCG industry will be preferable. Required Candidate profile Hands-on knowledge on machine learning frameworks (e.g., scikit-learn, TensorFlow, PyTorch) Proficiency in SQL for data extraction, integration, and manipulation to analyze large datasets. Perks and benefits To be disclosed post interview