Best Data Science Experts

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.

Abhijit Choudhary is a seasoned data scientist and AI practitioner with more than 15 years of experience spanning enterprise analytics, machine learning, natural language processing, intelligent automation, and Generative AI across the United States, Singapore, and India. His career has evolved through successive technology waves, from information management and digital transformation to modern AI systems. He holds dual master's degrees from Georgia Tech (M.S. Analytics) and IIT Guwahati (M.S. Mathematics & Computing) and is an IEEE Senior Member. Abhijit has led and contributed to enterprise AI initiatives across financial services, technology, and large-scale business operations, with expertise in Generative AI, large language models, intelligent document processing, information retrieval, AI governance, and the practical challenges of deploying trusted AI systems in production environments. He has presented technical research at Princeton University and NJIT and has been recognized through multiple international industry awards, including the AI Excellence Awards, Stevie Awards, and Globee Awards. Topics available for commentary include Generative AI, enterprise AI adoption, machine learning, natural language processing, AI governance, responsible AI, intelligent automation, and the future impact of AI on business and society. Comments, interviews, and expert opinions are provided in an independent professional capacity and reflect my personal views and experience. They do not represent the views, positions, or policies of my current employer. Additional background, media coverage, presentations, and speaking engagements are available at: https://abhijit-seasoned-ai-data-scientist.netlify.app/

Data science and AI leader with 12+ years in ad tech, ML, audience intelligence, and marketing analytics.

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.

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

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.

I began my journey with mathematics, drawn to the way numbers could reveal patterns, structure, and meaning. That foundation led me to pursue a master’s in data science at Johns Hopkins University, where I learned how to turn analytical thinking into practical tools for solving real-world problems. Over time, my path became more focused: I found purpose in applying data science to healthcare. Today, as a Data Scientist at Lucem Health, I work on clinical AI solutions that help healthcare organizations identify disease risk earlier and support more proactive care. My work focuses on building machine learning models and longitudinal EHR pipelines for early disease detection and risk stratification across a range of chronic and rare diseases. What drives me is the belief that healthcare AI should not only be technically strong, but also practical, trustworthy, and responsible. I work across data science, clinical context, product strategy, and responsible AI evaluation to help turn complex healthcare data into early risk signals that care teams can actually use. My story is about connecting mathematical rigor, data science, and human impact: using AI not just to predict outcomes, but to help people act sooner, make better decisions, and improve care.

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 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.

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.

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.

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.

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.

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.

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”.

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.

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.

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.

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.

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.