Jun 2022 – Apr 2023 · 10 mos · Gurugram, Haryana, India

• As part of the analytics team, developed an automated physical-fault-detection notification system for ~300MW solar assets using python. Increased 2MW production in less than 5 days of implementation and coordination with the site team.
• Developed power production forecast of a 250 MW solar plant with the weather parameters as input, using Deep Learning algorithm in python. Achieved 6% MAPE over the prediction period of 7 days.

Dec 2021 – Apr 2022 · 4 mos · Gurugram, Haryana, India

• Extraction of data using SQL and partnering with business leads to drive the performance.
• Worked on Profit & Loss for a region, understanding financial data spanning across from procurement
• stage to operations and delivery (of goods to the end consumer).

Dec 2020 – Dec 2021 · 1 yr · Delhi, India

• Leading a sub-team of 3, responsible for managing timelines, documentation and delivery
• of key customer/business data requests .
• Main POC for two programs, responsible for performing analysis as per business
• requirements, assisting key client support initiatives.
• Working in collaboration with various teams to enhance data platform’s features -
• automated QA process in Python reducing time from 4 hours to 10 minutes.

Jul 2018 – Oct 2019 · 1 yr 3 mos · San Francisco Bay Area

• Worked on key components of a major Ecommerce’s data platform including deployment and maintenance of complex extract transform and load scripts, and custom code.
• Built a new data model for business analytics team (in partnership with stakeholders), for ~1M customers and ~ 6M similar data points.
• Automated processes to transform datasets into efficient structure for reporting and ensured live data, daily in reporting tools.
• Assisted with data-related technical issues and supported data infrastructure needs.
• Developed scalable data solutions using SQL, AWS technologies S3, Redshift and Python.
• Built a data transformation script, with Python to extract 230K customer reviews from the vendor's XML file, and convert to inhouse consumable CSV file . Automated the process with AWS for deployment.
• Designed and developed a new monitoring framework,(specifically) a dashboard to display status of automatic execution of AWS data pipelines, which processed data-feeds of about 200 to 500 orders daily.
• Managed Segment IO integration with inhouse technology. Read documentation for flawless data flow and troubleshooted bugs in partnership with Segment’s team.

Oct 2017 – May 2018 · 7 mos · Buffalo-Niagara Falls Area

• Developed a data parsing and curation infrastructure to extract, transform, and load operational data (SCADA) from 20,000 wind turbines distributed over 200 wind farms into a single homogenized internal data set.
• Infrastructure was built using AWS data lake and warehouse (S3, Redshift), AWS Glue, and Python
• (Pandas, Boto3).
• Transformed data was used to detect and predict failure of individual parts ahead of time, resulting in an average cost savings of 13% (of revenue) across all the wind farms.
• Applied machine learning (SciKit Learn) to help calculate probability of failure of nearly 40,000 bearings and 10,000 gears across 2,000 wind turbine units.
• Probability data used by the data scientist team to estimate the remaining useful life of the wind turbine parts.
• Defined data quality standards to homogenize the inbound customer data. Led interactions with the customer success team to uphold the established data standards.
• The new data standard helped streamline data handling and terminology within the company and outside, while interfacing with customers.

May 2017 – Sep 2017 · 4 mos · Greater Charlottesville Area

• Built an automated data preprocessing system, using machine learning (linear regression, decision tree) to process ~320 million data points, collected from ~250 meteorological towers across the United States.
• Applied neural networks (keras in python) in the aforementioned automated system to achieve an accuracy of 90% in flagging unreliable data.
• Augmented the energy assessment process with a new data cleanup component/program to
• improve the overall fidelity/accuracy.
• New component led to an improvement of 2% in the accuracy of estimated energy (i.e. a possible
• delta of ~$30 M in energy revenue over the lifespan of wind farm).

Mar 2016 – Dec 2016 · 9 mos · State College, PA

• Worked in department of Aerospace Engineering at the Research Wind Turbine Facility which consists of small scale, 3 KW rated-Whisper 175 turbine.
• My initial work involved understanding the working of various systems in the facility where I also examined the data acquisition system consisting of sensors, signal conditioners, NI data acquisition modules and computer Labview code. Additionally I analyzed the electrical systems which involves measurement of power generated from turbine and solar panels, rectification of current for storage into batteries, charge controller to prevent overcharging and brake circuit for emergency stop.
• Conducted test campaigns and acquired meteorological and power generation data, to compute the power coefficient of the turbine.

Jul 2013 – Mar 2014 · 8 mos · India

• Led a team of 11 members, comprising of sophomores and juniors of Mechanical Engineering at VIT University for participating in SAE Aero Design West competition held in Fort Worth, Texas in March, 2014. We designed and fabricated two RC airplanes in a span of seven months.
• I specifically delegated work assignment to all team members, organized the documentation, handled the finances, supply chain and project time line.
• For more details, check https://sites.psu.edu/lakshitchawla/projects/43-2/ .

Jun 2013 – Jul 2013 · 1 mo · IGI Airport, New Delhi

• Worked onsite at the Engineering Services Department of flag carrier airline, Air India at the IGI Airport.
• This facility is one of the biggest Maintenance, Repair and Overhaul (MRO) unit of the country for passenger airplanes. It caters to customers worldwide including Cathay Pacific, Qatar Airways, Etihad, Jet Airways. It has capabilities for Major Checks, Components Overhaul for A320 family & B737 and provides engine overhaul servicing for turbofan engines specifically CFM 56-5B, IAE V2500.
• In a brief I inspected component systems of turbofan engines and hydraulic systems of an airplane during their overhaul servicing. I learned the basic operating of each of these systems and how they need to be serviced to ensure safe flights.