DEEPANSHU SHARMA

 Develop an automated property valuation tool using Python and R, analysing sales data across more than 250 London postcodes to reduce valuation time by 13% and improve pricing accuracy.  Conduct user research with 18 property buyers to identify pain points in the purchasing journey, translating qualitative insights into actionable service improvements that reduce enquiry response time from six hours to 90 minutes.

 Built a three-year revenue model projecting £3.5M for a London-based client by analysing unit economics, conducting market research, and segmenting revenue streams between B2B and direct-to-consumer channels (60/40) to establish realistic monthly targets.  Conducted downside scenario analysis, including a 25% increase in customer acquisition costs, shipping delays, and slower client onboarding, identifying a potential £180K downside risk and enabling pricing adjustments prior to launch.

 Consolidated data from more than ten sources, including fleet maintenance records, repair logs, and breakdown reports, to evaluate the reliability of ageing naval vessels and support replacement planning decisions.  Analysed breakdown patterns across operating conditions and identified that vessels over 25 years old experienced 35% more mechanical failures than newer vessels, providing evidence for accelerated replacement scheduling. s.

 Supported eight small and medium-sized businesses by identifying operational inefficiencies and implementing improvements that enhanced workflows and business performance.  Applied Lean and Six Sigma methodologies to redesign order management and documentation processes, reducing order-todelivery cycle time by 25% and improving operational performance by 12%.