Ankit Lamba

Developed, Managed, and Optimized a Shopify E-commerce store with a focus on hype and drop culture. Leveraged SEO, top-notch design, and user-friendly UI/UX, resulting in a 30% organic traffic boost. Optimized product content, reducing bounce rate by 20% and boosting sales by 25%. Implemented A/B testing, improving conversion rates by 15% and average order value by 10%. Implemented web analytics pipeline by integrating GA4, Hotjar, GTM, and various pixel tags (Meta Pixel, TikTok Pixel, Google Ads Conversion Tracking Pixel) for robust data collection. Achieved a 20% enhancement in B2B and B2C user personalization and overall user experience. Created and Implemented Data Strategy after Data Exploration, Analyzed data with Google Sheets, Shopify Analytics, and Python, Looker Studio and crafted data dashboards aligned with KPIs covering Website Performance, User Experience, Finance, Sales, Products, Users, Operations, Logistics, Social Media, and Marketing. These insights bolstered decision-making and boosted conversion rates. Additionally, integrated Google Search Console with Namecheap, optimizing Google's organic channel visibility and driving a 20% surge in organic search traffic. Streamlined user communication by integrating Zendesk CRM, Orderlyemails, and Klaviyo across channels. Enhanced social media marketing via Hootsuite and Buffer, reducing digital marketing costs by 30% without compromising engagement. Conducted market research for operational enhancements. Collaborated across teams to overcome launch challenges, ensuring on-time platform delivery.

Performed ad-hoc analysis to unveil business insights and trends, elevating company KPIs. Leveraged big data analytics to empower business users and enhance overall company performance. Consistently provided data-driven support for informed decision-making, leading to streamlined and more efficient operations. Harvested data from HubSpot CRM, Google Analytics 4, Hotjar, BigQuery, SEA, SMA, and other sources. Conducted data transformation, cleaning, and analysis using SQL, spreadsheets, and Python. Translated this data into actionable insights, yielding a 10% efficiency boost. Crafted data-driven narratives, reports, and dashboards with tools such as Google Sheets, Google Slides, MS PowerBI, and Looker Studio, aiding cross-functional decision-making across Sales, Finance, Marketing, Operations, Product, Social Media, and Customer Support. Pioneered and executed novel data collection initiatives, incorporating cutting-edge software tools, data libraries, and inventories. Established a robust web analytics pipeline integrating GA4, Google Ads conversion tracking, Hotjar, Axeptio, Meta pixel, LinkedIn insight tag, TikTok pixel, and more through GTM. Enhanced the company's monthly KPIs tracker with meticulously researched metrics relevant to the Tree Planting/Carbon Offset industry. Achieved a remarkable 40% efficiency boost by introducing an innovative data collection method. Created A/B testing & QA pipelines to boost engagement and CRO. Launched bug-free website versions. Leveraged data for sustainability efforts. Enhanced UX/UI through user testing, resulting in a smoother experience.

Researched and pioneered multimodal machine learning models. Employed data analysis, cleansing, manipulation, visualization, and exploratory data analysis (EDA) to optimize multimodal datasets. Achieved a 15% accuracy improvement using machine and deep learning techniques. Created research prototype in Python with Scikit-learn, Pandas, NumPy, Matplotlib, Seaborn, and Keras to predict movie ratings from multimodal features. Employed models including Linear Regression, XGBoost, Decision Trees, SVR, and Keras Regressor, assessing performance with MAE & MSE metrics.

Developed a Python-based system using Artificial Neural Networks (ANN) to recognize handwritten digits from the MNIST dataset, achieving over 90% accuracy. Built a contextual chatbot with Tensorflow, Python, and NLP, enabling context-aware responses to user inputs.

Developed a PQC system for streamlined product and quality control, achieving a 50% reduction in errors. Utilized JSP, Java, HTML, CSS, JavaScript, and SQL for system development, overseeing a team of four throughout the project. Designed and implemented the real-time PQC system, replacing a manual process and increasing work efficiency by 75%. This system reduced time and costs by 50%. Collaborated with stakeholders to gather requirements, creating wireframes and prototypes for the new design.

Coursework included Semantic Knowledge Representation, Probabilistic Graphical Models, Classification and Representation Learning, Clustering Analysis and Indexing, Text and Sequential Pattern Mining, Pattern Mining and Social Network Analysis, Visual Analytics, Data Dependencies and Data Integration, Data Economics, Law, and Ethics, Research Methodology, and Case Study. Award: Charpak Master BCS Scholarship - Embassy of France in India.

Coursework included UML, Python, C/C++, Data Structures and Algorithms, MySQL, Linux, Cloud Computing, Web Development, Telecommunication, Software Engineering, Advanced DBMS.