Apurv Jain

Apurv Jain Business & Data Analyst C-/--https://www.linkedin.com/in/apurvdataanalytics-/ Data Analyst having 3+ years of experience in the Marketing Analytics/ Retail Analytics domain. Skilled in leveraging Python, SQL , AI, Machine Learning, Data Science concepts and MS Excel to extract valuable insights from data and enhance marketing strategies. Proven expertise in analyzing market trends, consumer behavior, and campaign optimization. Passionate about contributing to the success of a dynamic company that values talent and offers good benefits. Professional Experience Business Analyst | Lenovo (E-commerce) - Contractual Jan’23 https://github.com/appu03   Education   Executive Management in Strategic Innovation, Digital Transformation and Business Analytics - IIT Delhi  PG Diploma in Data Science – IIIT Bangalore  B.E. Marine Engineering – M.E.R.I Kolkata    Technical Skills lls             Predictive & Market Analytics Business Intelligence Customer Analytics Market Basket Analysis Market Research & Market Trends RFM Analysis & Competitive Analysis User Acceptance Testing Requirements Gathering User story Social Media Analytics Decision Tree and CART Adobe Analytics Soft Skills lls        Problem-Solving Communication Critical Thinking & Attention to detail Adaptability Time Management Critical Thinking  )    lls Built Statistical model for Customer segmentation using RFM scoring analysis to develop insights to drive marketing strategies, in an 8.5user % increase in conversion rates. Conducted in-depth analysis of web resulting traffic patterns, behavior, and conversion Built Sentiment Analysis model using NLTK in Python to identify emerging trends and funnels to identify areas for optimization. opportunities for product improvement, resulting in an increased average customer rating to 2.5 from 4. Developed price optimization model using PULP, considering factors like demand elasticity, competitor pricing, and inventory constraints. Contributed to a 6.5% year-overyear increase in incremental margin. Generated business intelligence reports through the Power BI dashboard showing different metrics for the event, assisting stakeholders in strategic and critical decisionmaking. Aug’22- Nov’22 Designed and implemented Market Mix Model using statistical techniques to analyze the impact of marketing channels, such as digital media, TV, print, and promotions to capture the most significant drivers of sales. Further used Market Mix Model to allocate credit to various marketing channels, resulting in greater budget allocation to digital media which increased sales by 16%. Applied topic modelling algorithms using LDA to discover hidden trends helping customer to understand sentiments and preferences and increase market share by 12%. Project Engineer | Alpha Ori Technology (Shipping and Logistics)   Certiications Meta Marketing Analytics – Coursera Google Analytics – Great Learning Tableau Visual Best Practices – Analytics Vidya Jan’23--Aug23 Sr Data Analyst | Zigna Analytics (Marketing Analytics) - Contractual Aug’22- Nov ‘22     Conducted in-depth web Analytics of traffic patterns, user behavior, and conversion funnels to identify areas for optimization, leading to a 10% increase in average session duration as a scrum Team member. Collaborated with the marketing team to implement targeted optimization strategies, resulting in a 8% decrease in bounce rate Conducted hyper-parameter tuning and cross-validation to optimize demand forecasting model, achieving a reduction in MAPE by 6%. Generated insightful visualizations with Matplotlib and Seaborn to analyze sales data to compare performance across multiple markets against last year’s metrics. Business Analyst | Landmark Group (Retail Analytics) Jan’23 Nov’23— Developed predictive models using Random Forest to anticipate maintenance needs and optimize ship schedules, resulting in a 10% reduction in maintenance costs Conducted market research to identify emerging trends and opportunities in the maritime industry, enabling the company to seize new business prospects Used SQL to collect ship data, including vessel tracking, weather conditions, fuel & consumption, increasing operational efficiencies and cost-saving opportunities by 9%. Application Developer | V.G.T Tech (Education)    Dec’20 – Aug’22 Nov’18 - Jul’20 Supported students in building models in Regression and classification using Numpy, Pandas, Matplotlib, Scikit-learn and Neural Network, Taught students about Statistics and ML algorithms such as Linear/ Logistic Regression, XG Boost, SVM and Clustering and other unsupervised Learnings. Helped students to conduct qualitative and quantitative research and leverage mathematical techniques to develop scientific solutions.