Dhanshree is a Backend Developer with 8+ years of experience in backend development, specializing in data-driven solutions and machine learning algorithms. She has a proven track record in deploying applications using Docker and Kubernetes, and excels in collaborating with cross-functional teams.
Engineered algorithms for the Vriti Portal, enhancing backend functionality.
Orchestrated deployments using Docker and Kubernetes, ensuring smooth application management.
Developed real-time algorithms for Schlumberger, optimizing drilling tool performance.
Transformed raw data into actionable insights, improving marketing strategies at Tiger Analytics.
Collaborated with cross-functional teams to deliver data-driven solutions in Agile environments.
Engineered algorithms that improved backend performance by 30%.
Successfully orchestrated deployments that reduced downtime by 20%.
Developed algorithms that enhanced predictive maintenance, reducing costs by 15%.
Transformed data analysis processes, increasing efficiency by 25%.
Led a team of 5 developers, mentoring them in best practices and technologies.
Overview: A portal focused on backend development for data-driven solutions, incorporating quantitative analysis and predictive modeling. Responsibilities: Engineered algorithms for backend development using Python, TypeScript, Pandas, NumPy, and Django DRF. Orchestrated deployments utilizing Docker and Kubernetes for the website. Developed various Python algorithms for web applications, including data extraction and prediction models. Built APIs using Django DRF architecture, including APIview and Viewset APIs. Analyzed and managed MongoDB databases, gathering project requirements from scratch.
Key outcomes:
Engineered backend algorithms, contributing to data-driven solutions.
Successfully orchestrated deployments with Docker and Kubernetes.
Developed APIs using Django DRF, enhancing system functionality.
Overview: Developed real-time algorithms and systems for monitoring and analyzing drilling tools (CLink, PowerDrive) and components (O-rings) to predict failures and identify damage. Responsibilities: Developed a real-time algorithm for CLink, a drilling tool, to analyze temperature, voltage, and transmission/reception to identify system damage. Utilized Python, Bokeh, Node.js, TypeScript, C++, Angular CLI, and Dataiku for monitoring health analysers. Developed an algorithm for the Overall Status of PowerDrive Health Analyzer to evaluate parts status and raise service requests. Implemented an algorithm to monitor the quality of O-rings in health analysers, including real-time evaluation of remaining life. Developed an algorithm to automate the upload of files into a MySQL server.
Key outcomes:
Developed algorithms enabling real-time monitoring of drilling tools, enhancing operational safety and efficiency.
Created an algorithm to evaluate PowerDrive parts, facilitating timely service requests for component replacement.
Implemented O-ring monitoring algorithms that predict remaining life, reducing damage and total tool costs.
Overview: A project focused on enhancing promotional effectiveness through advanced analytics, including customer segmentation and social network analysis. Responsibilities: Engineered features for customer segmentation, purchase frequency, and product affinity to better understand consumer behavior and predict promotional response rates using Python, Pandas, NumPy, ORM, DRF, and PostgreSQL. Transformed raw transactional data into actionable insights to inform targeted marketing campaigns. Utilized network science to analyze the influence of social networks and customer relationships. Identified key influencers and opinion leaders within social networks using graph-based algorithms.
Key outcomes:
Engineered customer segmentation features, leading to better understanding of consumer behavior and prediction of promotional response rates.
Transformed raw data into actionable insights, improving targeted marketing campaigns.
Identified key influencers using graph-based algorithms, enabling viral marketing strategies.
Overview: Developed solutions to minimize manual effort in mapping unstructured insurance data into various tools and generate reports. Responsibilities: Developed Python crawlers to extract required information from unstructured data using Pandas. Standardized processes to minimize effort in mapping unstructured data into different tools. Developed services to generate excel reports using Angular endpoints. Developed an algorithm based on logistic regression classification to visualize company's offered promotions and its impact.
Key outcomes:
Minimized manual effort in unstructured data mapping by developing Python crawlers.
Developed services for generating Excel reports, improving data accessibility.
Created a logistic regression classification algorithm to visualize promotional impact.
Overview: Involved in upgrading and maintaining critical internal tracking, account, marketing, and payment tools for e-commerce operations. Responsibilities: Upgraded tracking tools, RODEO and HitchRep, over 6 months, using Java, HTML, MySQL, and Python to provide visibility into outbound workflows. Contributed to Kaizen projects for Account tools (AWS Web Operational Tool, Nautilus C++, HTML), Gift card escalation (Python, PHP), Marketing & Promotion (Java, CSS), and Amazon Payment tools (C++). Developed required algorithms, designed, and implemented user interfaces for Amazon analytics/delivery tools. Collected requirements and codified information for periodic views.
Key outcomes:
Upgraded RODEO and HitchRep tools, enhancing visibility into outbound workflows for Amazon's e-commerce operations.
Contributed to Kaizen projects across various internal tools, demonstrating adaptability across different technology stacks.
Developed algorithms and user interfaces for Amazon analytics/delivery tools based on collected requirements.
Dhanshree
Backend Typescript