User details
AT
AT
Anika Tasnim
@anika_tasnim_1r5zv093m
AI Data Scientist
Detroit, MI, United States
0Follower0Following0Mutual0Post
Member since: Jan 22, 2025Experienced Data Scientist and Machine Learning Engineer with a strong background in mathematical modeling and data analysis. Skilled in Python, SQL, and advanced techniques to process large datasets and deliver insights. Proven track record of building and deploying predictive models and recommendation systems, with a deep understanding of machine learning algorithms.
• Conceptualized and engineered an end-to-end machine learning recommendation system, employing fine-tuned large language models (LLMs) to generate personalized meal suggestions aligned with user preferences and dietary needs, addressing the startup's mission to enhance user satisfaction.
• Harvested and curated large-scale datasets from diverse web sources using advanced web scraping techniques, ensuring high-quality data for training robust and scalable machine learning models while tackling challenges of data variability and completeness.
• Orchestrated cross-functional collaboration with engineering and product teams to design and implement a data ingestion and deployment pipeline, enabling seamless integration of machine learning workflows into product development and establishing a foundation for data-driven innovation.
• Developed an end-to-end Python-based CAN bus decoder for commercial vehicles, achieving a 70% acceleration in data analysis by completing the project in under one week, ahead of the 3-month timeline.
• Engineered a Python tool with RESTful APIs and MongoDB, enhancing fault detection speed by 60% through real-time analysis of Ford vehicle data and improving data-driven decision-making across the team.
• Conducted a comprehensive analysis of the 2021 Vehicle Inventory Use Survey dataset for 180M trucks, providing insights that aligned data interpretation with business needs and optimized strategies for 10+ stakeholders.
• Led the development of an online shopping application using Angular, NodeJS, and MongoDB, analyzing user behavior data to implement features that achieved a 30% increase in user engagement and supported over 10,000 transactions per month.
• Collaborated with a team of 5 engineers to create a web application for bank employees, utilizing Java, HTML, CSS, and Oracle SQL, which enhanced customer management efficiency by 25% and reduced processing time by 15%.
• Executed machine learning and computer vision tasks by preparing and annotating over 2,000 images, significantly improving model accuracy by 20% and contributing to successful project outcomes.