Unlock the power of data science with Featured.com's curated directory of top experts in machine learning, big data analytics, and artificial intelligence. Our platform connects leading data scientists—professionals who transform raw information into actionable insights—with premier publishers and media outlets. These experts have been featured in prestigious publications, sharing cutting-edge techniques and real-world applications across industries. For publishers, our directory offers instant access to authoritative voices in data science, ensuring your content is backed by credible insights. Data scientists can leverage this platform to amplify their visibility and establish themselves as go-to sources in the rapidly evolving field of analytics. Whether you're seeking expert commentary on AI trends or looking to showcase your data science expertise, Featured.com is your gateway to impactful connections. Explore our directory to discover data science experts who can elevate your content or expand your professional network.
Connect directly with our network of vetted data science experts for interviews, quotes, or in-depth analysis.
Many experts respond within hours to media requests
All experts undergo background and credential verification
No fees to connect with experts for legitimate media requests
Join our network of professionals and connect with journalists and publishers looking for your expertise.
Showing 20 of 3,163 experts
Data Science Manager at Kapitus
I am a statistician and data science leader with a Ph.D. in Statistics from Stony Brook University and extensive scientific contributions in machine learning, predictive modeling, and advanced statistical methods, including publications on accelerated failure time models in XGBoost and network elastic net frameworks. Currently in senior analytics and data science roles within FinTech at Kapitus, I combine rigorous academic research with practical experience developing data-driven solutions to enable better financing for small businesses across financial services.
Featured In:
Data Science Lead at Amazon Ads
Data science and AI leader with 12+ years in ad tech, ML, audience intelligence, and marketing analytics.
Featured In:
Principal Data Scientist|Podcast Host|Community Builder at Boomi
My focus areas are Health informatics, Machine Learning, and Design-led engineering. I bring 7+ years of experience in Data Science, Software Engineering and Risk analytics from the United States and India.Currently working as a Data Science Lead with extensive experience in platform integration using advanced data mining and machine learning in Python, SQL, R and data engineering in Snowflake, Apache Spark and Hadoop.Technical Skills:‣ Programming languages- Python, R, Java, C/C++,SAS‣ Advanced Analytics‣ Statistics & Probability‣ Big Data - Apache spark , Hadoop‣ Machine Learning -Specialties: Time Series Modeling, Anomaly Detection,Data Modeling,Data Mining, Feature Engineering and Natural Language Processing‣ Database Management - Teradata SQL, Amazon Redshift, Snowflake‣ Data Visualization - Tableau, Power BI‣ Web Applications - RShiny and Flask‣ Tools - AWS, Google Analytics, Git, BitBucket, MS OfficeI am interested in innovation-driven engineering. I look forward to connecting with you.
Featured In:
Sr Manager Consumer Decision Science at Glassdoor
Data Science Leader driving scalable analytics solutions | I specialize in transforming complex business challenges into actionable data solutions. Currently leading Glassdoor's data science initiatives across Jobs and Notifications verticals, where we develop sophisticated models and analytics frameworks to enhance user experience and drive business growth.Key Focus Areas:Building & scaling high-performing data science teamsStatistical modeling & predictive analyticsProduct analytics & experimentationData pipeline optimizationCross-functional strategy developmentPublished researcher in Data Science and AI | Expertise in turning data insights into business impact | Passionate about mentoring next-gen data scientists
Principal Data Scientist at Boomi
My focus areas are Health informatics, Machine Learning, and Design-led engineering. I bring 7+ years of experience in Data Science, Software Engineering and Risk analytics from the United States and India.Currently working as a Data Science Lead with extensive experience in platform integration using advanced data mining and machine learning in Python, SQL, R and data engineering in Snowflake, Apache Spark and Hadoop.Technical Skills:‣ Programming languages- Python, R, Java, C/C++,SAS‣ Advanced Analytics‣ Statistics & Probability‣ Big Data - Apache spark , Hadoop‣ Machine Learning -Specialties: Time Series Modeling, Anomaly Detection,Data Modeling,Data Mining, Feature Engineering and Natural Language Processing‣ Database Management - Teradata SQL, Amazon Redshift, Snowflake‣ Data Visualization - Tableau, Power BI‣ Web Applications - RShiny and Flask‣ Tools - AWS, Google Analytics, Git, BitBucket, MS OfficeI am interested in innovation-driven engineering. I look forward to connecting with you.
Featured In:
Data Scientist
Data scientist with experience in machine learning, large language models, clustering, search algorithms, and analytics with proven expertise in leveraging the latest AI breakthrough for enterprise use cases
Data Scientist
Data Scientist with 6+ years of experience implementing ML algorithms to drive business decisions. Expertise in production code, algorithm development, and cross-functional collaboration. Proficient in Python, SQL, and cloud platforms. MS in Statistics from UIUC and proven track record of applying advanced analytics to solve complex business challenges.
Data Scientist at Cognizant Technology Solutions
In me, you'll find a dedicated, persevering leader with a passion for learning and an eye for detail seeking growth, experience and opportunities to solve novel and challenging machine learning problems. I am a fluent coder in Python, R and SQL. I'm trained in GenerativeAI/Large Language models and cloud computing. In addition to statistical modelling & data analysis, I've 4+ YOE working on popular Machine Learning algorithms for image and natural language processing. I've developed and delivered high-efficiency, high-accuracy end-to-end data science solutions in my 6+ years in the Life Sciences industry. I've experience managing stakeholders and gathering requirements from teams/peers located in the US, Europe and APAC. In most projects, I've directly collaborated with our client partners from major pharmaceutical companies across the globe. My goal is to forge ahead full-throttle – constantly learning, incrementally growing – in pursuit of holistic success.
Featured In:
Senior Data Scientist at Striveworks
Mathematician turned AI-researcher using the world's largest supercomputer(s) to build, validate, and deploy AI models to areas of national interest including fundamental science, energy, health, and security.
Senior Manager Data Science at Capital One
Shesh Narayan Gupta is a Senior Manager in a Financial Services organization and holds a Master’s Degree in Data Science. With a strong foundation in artificial intelligence and years of professional experience in data-driven problem-solving, he brings a unique perspective to intersection of technology, creativity, and storytelling. His expertise spans machine learning, Generative AI, and practical applications of AI in various industries, including finance, marketing, and education. As a seasoned data science leader who is also featured in Times New Square for his contributions in data science, Shesh Narayan has been at the forefront of leveraging AI technologies to drive innovation and efficiency in real-world scenarios. Beyond his corporate career, he has a deep passion for storytelling, mentoring, and game design, which has led him to explore how Generative AI can revolutionize narrative creation, game development, and interactive media.
Featured In:
Principal Research Scientist at Oracle
My primary research interest is in data-driven decision making under uncertainty for retail, supply chain, transportation, logistics, and service operations applications. The methodologies employed in my research range from data analytics and statistical machine learning to data-driven optimization. My Erdös Number is 3 since Aug 2020.
Featured In:
Founder & Editor at WhatAreTheBest.com comparison data
Albert Richer is the Founder & Editor of WhatAreTheBest.com, a large-scale research platform analyzing more than 20,000 structured categories across software, consumer products, and niche industry verticals. He specializes in product evaluation, comparative market analysis, long-tail category research, and data-driven ranking methodologies that help businesses and consumers make confident purchasing decisions. At WhatAreTheBest.com, Albert oversees the full architecture behind the platform—from data collection and review standards to automated scoring frameworks and industry taxonomy design. His work blends large-scale content engineering with real-world buyer insights to identify the best products and tools across thousands of industries.
Featured In:
Co-Founder and Data Science Mentor at codegnan Destination
Engaging, understanding, and knowledgeable technical trainer with over 7 years of experience educating students, seasoned employees and new hires in the software industry. Certified as an Azure AI Engineer and a Microsoft Certified Trainer. Also adept at teaching users a variety of software programs and technologies. Dynamic communicator with excellent presentation skills, able to translate complex concepts into understandable terms using creative teaching methods.Proven track record of more than 10,000 students with industry jobs in emerging technologiesI like to be innovative and do special things which brings smile to other people's face. I always believe in a phrase " Don't work hard just work with heart.."'As I believe Technology has the power to transform educationWe at Codegnan make every passionate learner realize what they are and pursue their passion to make their dreams come true. We strongly believe “Nothing is Impossible with persistent practice and effort”.
Featured In:
Machine Learning Engineer at Microsoft Corporation
My professional journey started at the age of 17 when I moved 10,000 miles away from everyone I knew to the opposite end of the planet at UC San Diego, and became a part of their inaugural Data Science major. Working on ML Systems Research for 2.5 years, including a Data Platform for scalable Deep Learning, Transfer Learning with CNNs, and scalable systems for GCNs was my introduction to Deep Learning and unlocked publications and recognition at CIDR & ACM SIGMOD. My first professional experiences with some of the leaders in the Financial, Consulting, Pricing, and Enterprise Software domains involved: 📄 Inventing a tool with a novel ML workflow to parse US Companies' Filings 🤖 Developed a chatbot for a $200,000 client proposal 🚩 Formulating a preprocessing framework to automatically flag warnings for bad ML feature combinations for 50+ global pricing models ⚙️ Implementing 4 hyperparameter optimization algorithms in Apache MADlib for petabyte-scale Massively Parallel Postgres (MPP) databases such as GreenplumDB. Upon joining the Microsoft AI Development Acceleration Program (MAIDAP), I worked with 4 orgs across Microsoft for 6 months each, working on projects around: 🎮 AIOps tooling for contrast analysis, enabling 6+ teams in Azure, M365, & Xbox with upto 6x TTM reduction for VM perf issues, Container Faults, and video-game cheating detection 🏆 Tensor Query Processor (TQP) & AI-centric DB System (executing SQL queries on a GPU), winning Best Demo Paper at VLDB and 1st place at Microsoft’s Global Hackathon Cloud Executive Challenge ⚖️ Responsible AI tooling for CV models in Azure ML, announced by Microsoft’s CEO for Public Preview at Microsoft Build 2023, gaining 500+ stars for the RAI Toolbox GitHub repo 📉 Resource Profiling plug-in for Azure saving >100k/year More recently, my work involved: 🚀 Release Computer Vision model support in Azure ML's Responsible AI Dashboard announced at Microsoft Build 🚀 Implementing and shipping Azure OpenAI Evaluations for Public Preview release announced at Microsoft Ignite ⚡ Leading telemetry efforts for Microsoft Foundry Evaluation tooling, involving query optimizations to reduce memory overhead by 40x and improve data refresh latency by 60% 🔀 LLM Fine-tuning & Evaluations for AI-powered Merge Conflict Resolutions in the planet’s largest codebase (the Windows OS repo) Feel free to get in touch! 📅 Appointments: calendly.com/agemawat 🎤 Speaking Request: bit.ly/AdvityaGemawatSpeaker Disclaimer: All opinions provided are my own and do not reflect or represent my employer or any other entity.
Featured In:
Senior Data Scientist at Fractal Analytics
Vinothkumar Kolluru is a Senior Data Scientist at Fractal Analytics with 9+ years of experience in NLP, Machine Learning, and Deep Learning. He builds AI-driven solutions that improve customer experience and decision-making, with a focus on customer segmentation, friction detection, and digital journey optimization for large-scale web platforms. He has delivered end-to-end models across tech, healthcare, and marketing—ranging from NLP-based document summarization and topic categorization to predictive analytics—using transformer architectures (e.g., BERT), sequence models, and classical ML. Vinoth has also led analytics initiatives such as call categorization for healthcare contact centers and relevance modeling to improve campaign targeting and performance. A passionate researcher and contributor to the AI community, Vinoth has 50+ publications and 246 citations (h-index 9). He is recognized with the Dr. Abdul Kalam Young Achiever National Award and holds an MS in Data Science from Stevens Institute of Technology, along with a Gold Medal in Engineering from Anna University. His core toolkit includes Python, SQL, AWS, and Azure, and he enjoys translating complex data into practical, measurable business impact.
Featured In:
Artificial Intelligence and Machine Learning Engineer
Diversity is my strength. As a data scientist, I worked with subject matter experts across many industries: energy, electronics, manufacturing, sustainability, education, marketing, and database infrastructure: and in many countries: USA, Finland, and Sweden. This keeps fresh, alert, and it is what I enjoy most about data science. Companies typically hire me to solve a particular problem or more broadly improve their processes. Sometimes, this involves building products (or incorporating into internal processes) machine learning or AI. Other times, I use data science to make design recommendations to engineers or enable managers to make data-based business decisions. Either way, I see these products and decisions through to their implementation, which has given me some experience in management as well.
Founder at BestAIFor
With over 15 years of hands-on experience in affiliate marketing, e-commerce, and digital growth strategy, I’ve helped brands scale profitable online partnerships and build high-performing affiliate ecosystems. As the founder of BestAIFor.com - a fast-growing AI tools directory, benchmark platform, and independent review hub - I now combine my performance marketing background with deep expertise in the AI landscape. I personally evaluate and benchmark hundreds of AI tools every month, tracking real-world metrics like speed, accuracy, pricing shifts, ROI, and usability across productivity, content, marketing, and creative workflows. My work focuses on cutting through the hype to deliver actionable, data-backed insights that help solopreneurs, marketers, and businesses choose the right AI stack for 2026 and beyond. Whether I'm setting up affiliate programs for AI tool makers, optimizing campaign performance with AI-powered automation, or identifying emerging trends through original benchmarks, I’m driven by one goal: turning complex technology into practical growth advantages. I’m passionate about sharing transparent, no-BS analysis and helping the industry move faster with better information. You’ll often find me publishing fresh benchmarks, “State of AI Tools” micro-reports, and strategic guides on BestAIFor.com.
Featured In:
Head of Data and AI at Creative Fabrica
With over 10 years of experience in the tech industry and academic research, I am a passionate and effective leader in Data Science and Engineering. I have a strong background in machine learning and statistics, and I have applied my skills and knowledge in various domains, such as fintech, commercial real estate, and productivity software.Currently, I am the Director of Data Science and Engineering at Miro, the online collaborative whiteboard platform for teams. I lead a team of 50+ Data professionals, who are responsible for delivering intelligent features in the Miro app, such as Miro Assist, sticky note clustering, and template recommendation. We also cater for all data delivery and management within Miro, ensuring high-quality, scalable, and reliable data services and infrastructure. My mission is to enable Miro to become "as intelligent as a teammate" and to empower data-driven decision making across the organization.
Featured In:
Scientific Director at Tekkare
With a PhD in molecular genetics and as a specialist in data science, Céline Chantry-Darmon has over twenty years of experience in biomedical research and complex data analysis. As Scientific Director at Tekkare, she works on developing trustworthy artificial intelligence for healthcare. She is also committed to promoting inclusive and responsible artificial intelligence, and to advancing women in science and technology.
Featured In:
Senior Data Scientist at Accushield
Ability to synthesize data insights and present clear, compelling visuals and narratives to drive business action. Passionate about generating meaningful impacts through data. Adept at distilling data into actionable insights to optimize business performance. Technical expertise in statistical modeling, machine learning, and predictive analytics to solve challenges around growth, marketing effectiveness, operational efficiency, and customer experience. Combining technical skills with modern business concepts to streamline crucial decision-making processes.
Featured In:
Showing 20 of 3163 experts
Data science experts can boost their visibility by creating a comprehensive profile on expert directories like Featured.com. Showcase your expertise in areas such as machine learning, data analytics, and statistical modeling. Regularly update your profile with recent projects, publications, and insights. Engage with industry discussions online and at conferences to build your reputation. These steps can help attract publishers looking for authoritative voices in data science.
Data scientists should create a compelling expert profile by highlighting their specific areas of expertise, such as machine learning, statistical analysis, or big data processing. Include relevant academic qualifications, industry certifications, and notable projects or research. Showcase any previous media appearances or published works. Provide concise, quotable insights on current trends in data science to demonstrate your ability to communicate complex ideas. A well-crafted profile helps publishers quickly assess your expertise and relevance for their articles.
Publishers seek diverse data science insights, including trend analysis, predictive modeling results, and interpretations of complex datasets. They're often interested in how data science impacts various industries, from healthcare to finance. Experts who can explain machine learning algorithms, big data challenges, or AI ethics in accessible terms are in high demand. Publishers also value unique perspectives on emerging technologies like quantum computing or edge AI and their potential applications.
Publishers can find the right data science expert by using specialized platforms like Featured.com. Start by defining your article's focus—whether it's machine learning, data visualization, or predictive analytics. Use filters to narrow down experts based on their specific areas of expertise, industry experience, and previous media appearances. Review expert profiles, which typically include their background, notable projects, and sample quotes. This approach helps ensure you connect with a data scientist who can provide relevant, authoritative insights for your piece.