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I am a Data Scientist with a Master's degree in Statistics and professional experience delivering data-driven solutions through statistical modeling, machine learning, and advanced analytics. I help businesses, researchers, and organizations transform complex data into actionable insights that support informed decision-making. My expertise includes statistical analysis, predictive modeling, machine learning, data visualization, and interactive application development. I have worked on projects across business analytics, healthcare, biostatistics, transportation, and academic research, developing solutions that are both technically robust and practically useful. I specialize in building end-to-end analytical workflows, from data collection and preprocessing to modeling, visualization, and reporting. I also develop interactive applications using R Shiny and other Posit products to help stakeholders explore data and automate decision-making processes. Areas of Expertise • Statistical Modeling and Data Analysis • Machine Learning and Predictive Analytics • Hypothesis Testing and Experimental Design • Regression Analysis and Multivariate Methods • Data Cleaning, Preprocessing, and Feature Engineering • Exploratory Data Analysis (EDA) • R Shiny Application Development • Interactive Dashboards and Data Visualization • Business Analytics and Decision Support • Research and Biostatistical Analysis Technical Skills • Python (Pandas, NumPy, Scikit-learn, XGBoost) • R (Shiny, tidyverse, ggplot2, caret) • SQL • Posit Products (Shiny, Quarto, R Markdown) • Excel and Power BI • Statistical and Machine Learning Techniques • Master's Degree in Statistics • Top Rated Freelancer with 100% Job Success • Experience delivering machine learning, analytics, and statistical solutions • Strong communication with both technical and non-technical stakeholders • Commitment to producing accurate, reproducible, and well-documented work Whether you need advanced statistical analysis, predictive models, interactive R Shiny applications, or comprehensive data solutions, I am committed to delivering high-quality results that create measurable value.

Hi, I am Dev 🚀 Senior Data Analyst with over a decade of expertise in Data Science, Machine Learning, Tableau, KNIME, Alteryx, and R Programming Language, I specialize in analyzing user data and big data sets to derive insightful statistical analysis and craft robust business strategies. 🔍 As a seasoned professional, I offer consulting sessions to clients seeking guidance in leveraging their data effectively. 📊 My proficiency extends to developing high-calibre dashboards using Tableau and Power BI, ensuring the delivery of professional-grade visualizations that drive actionable insights. 🌟 Let's connect and explore how my skills and experience can contribute to maximizing your data potential! #DataScience #MachineLearning #Tableau #PowerBI #ConsultingExpertise 💡

I am a Lead Data Scientist and Data Engineer with over 10 years of experience turning messy, complex datasets into scalable, high-accuracy predictive systems and automated data pipelines. I specialize in the Retail/FMCG and Healthcare/Pharmaceutical sectors, bridging the gap between advanced technical architecture and actionable business strategy. Backed by an Executive PG in Data Science & AI from IIT Roorkee and holding Microsoft Certifications in Python and Azure (AZ-900 & DP-100), I build the "intelligence layers" that drive enterprise decision-making. My Core Technical Expertise: Data Engineering & ETL: GCP (BigQuery), SQL, dbt, Parquet, Batch Processing, Multiprocessing Programming & AI/ML: Python (Pandas, Scikit-learn, Regex, Flask, Streamlit), R, SAS, Predictive Modeling, GenAI Business Intelligence & Viz: Power BI, Looker, Clinical Dashboards Proven Domain Impact: Retail & FMCG: Engineered automated POS data pipelines (36-month initiative), improving loading efficiency by 30%. Led a 24-month product harmonization project using predictive modeling to resolve discrepancies across millions of records. Designed GCP/BigQuery demand forecasting pipelines to optimize supply chain inventory. Healthcare & Clinical Analytics: Deep experience integrating open-source tools (Python, R, SAS) for clinical trial data visualization. Proficient in building interactive clinical dashboards utilizing Pharmaverse, SDTM, and ADaM datasets. Cloud Architecture & Metrics: Migrated massive datasets to modern cloud environments and developed robust DAU/MAU tracking structures inside BigQuery and Looker. Why Work With Me? I do not just execute code; I solve business problems. Alongside my technical career, I manage my own coworking space business, meaning I inherently understand the commercial urgency, stakeholder management, and extreme ownership required to deliver ROI. Whether you need to deploy an AI model, untangle enterprise ERP data, or build an interactive dashboard from scratch, I write clean, maintainable, and production-ready code. Let’s connect to discuss how we can scale your data infrastructure and build models that actually impact your bottom line.

I am passionate about transforming raw data into actionable insights and architecting robust data infrastructures. Let's collaborate to elevate your data strategy to unprecedented heights! Profile : public.tableau.com/app/profile/hardik.pansuriya/vizzes Salesforce : salesforce.com/trailblazer/hardikpansuriya Are you searching for a skilled Data Analyst proficient in Python, Tableau, and SQL? Look no further! With a keen eye for detail and expertise in data manipulation, I bring a comprehensive understanding of Python's analytical capabilities, Tableau's visualization prowess, and SQL's querying power. My experience ensures that data-driven insights are both accurate and impactful, helping you make informed decisions with confidence. Collect data by using a scripting language such as SQL - Perform SQL queries - Sort and filter data using SQL queries - Convert data types using SQL functions Visualize data insights and communicate your findings to teams in other organizations - Create data visualizations using Tableau - Create visuals in spreadsheets - Create presentations from data analysis results Build and train users of new dashboards - Identify the data needs of users - Create dashboards using Tableau - Use design thinking to improve dashboards Create comprehensive reports - Create data cleaning reports - Create and maintain change logs - Create reports in R Markdown Explore and analyze datasets with spreadsheets - Clean data in spreadsheets - Sort and filter data in spreadsheets - Create pivot tables in spreadsheets Knowledge of some programming languages and an organized and methodical approach to work - Install and use the tidyverse package in R - Run scripts in RStudio - Create data visualizations in RStudio

I am an Applied AI & Machine Learning Consultant with a strong background in data analytics, predictive modeling, statistical analysis, and decision support systems. My experience spans finance, lending, capital markets, marine analytics, retail, and business intelligence, where I have developed data-driven solutions that improve forecasting accuracy, automate analytical workflows, and support strategic decision-making. My core expertise lies in transforming raw data into actionable insights through data preparation, feature engineering, statistical modeling, machine learning, and interactive analytics. I enjoy working on challenging analytical problems, particularly those involving predictive modeling, time-series forecasting, risk assessment, and large-scale structured datasets. My focus is always on building practical, production-ready solutions rather than purely theoretical models. I have hands-on experience developing regression, classification, ensemble learning, and forecasting models using Python and R. My work includes model selection, hyperparameter optimization, feature engineering, model validation, explainability, performance monitoring, and deployment-ready analytics pipelines. I am comfortable working with algorithms such as XGBoost, LightGBM, CatBoost, Random Forest, Gradient Boosting, Logistic Regression, Elastic Net, Support Vector Machines, Neural Networks, and time-series techniques including ARIMA and GARCH, while selecting the most appropriate approach based on business objectives and data characteristics. My experience also includes financial and quantitative analytics, where I have built predictive models and analytical dashboards for mortgage-backed securities, probability of default, options analytics, stock market analysis, foreign exchange research, and market intelligence. These projects strengthened my understanding of financial datasets, feature engineering for market data, risk modeling, and the importance of robust validation techniques for real-world decision making. Beyond predictive modeling, I develop interactive analytical applications and dashboards using Streamlit and R Shiny, enabling stakeholders to visualize complex datasets, monitor model outputs, and interact with analytics through intuitive web-based interfaces. My technical toolkit includes Python (Pandas, NumPy, Scikit-learn, XGBoost, LightGBM, CatBoost, TensorFlow, PyTorch, SciPy, Statsmodels, Plotly, Streamlit, FastAPI), R (tidyverse, caret, glmnet, forecast, Shiny), SQL, Power BI, Tableau, Git, Jupyter Notebook, Google Colab, and cloud-based analytics environments. I also recently expanded my expertise into modern AI applications, prompt engineering, AI workflow automation, agentic AI, AI productivity systems, and practical enterprise adoption of Generative AI technologies. This complements my existing machine learning experience by helping organizations combine traditional predictive analytics with modern AI-powered workflows. I believe AI should be applied thoughtfully. I use classical statistical and machine learning methods when they provide the best predictive performance, and leverage Generative AI where it genuinely improves productivity, automation, knowledge extraction, or decision support. My approach emphasizes explainability, reproducibility, robust validation, and solutions that deliver measurable business value. Whether the objective is predictive analytics, statistical modeling, machine learning, AI-assisted automation, financial analytics, business intelligence, or interactive dashboards, I enjoy collaborating with clients to build scalable, reliable, and data-driven solutions that solve real business problems.

As a freelance professional with a Master's in Science in Statistics, I bring a unique blend of academic knowledge and practical expertise to every project I undertake. With a strong foundation in statistical theory, advanced data analysis techniques and the ability to effectively communicate complex statistical concepts, I am equipped to provide valuable insights and solutions to clients across various industries. My academic journey in pursuing a Master's of Science in Statistics has provided me with a solid understanding of statistical principles and their applications. Through coursework in probability theory, statistical inference, regression analysis, experimental design, and multivariate analysis, I have gained a comprehensive skill set that enables me to tackle diverse data analysis challenges. One of the key aspects of my academic training has been the emphasis on statistical software and programming languages. I have developed proficiency in utilizing tools such as R and Excel to manipulate, analyze, and visualize large datasets. This technical expertise allows me to efficiently process and extract meaningful information from complex data, facilitating evidence-based decision-making for my clients.