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Schedule Interview NowAt Softaims, I have been fortunate to work in an environment that values creativity, precision, and long-term thinking. Each project presents a unique opportunity to transform abstract ideas into meaningful digital experiences that create real impact. I approach every challenge with curiosity and commitment, ensuring that every solution I design aligns not just with technical requirements, but also with human needs and business objectives. One of the most rewarding aspects of my journey here has been learning how to bridge the gap between innovation and practicality. I believe technology should simplify complexity, enhance efficiency, and empower people to do more with less friction. Whether building internal systems, optimizing workflows, or helping bring client visions to life, my focus remains on developing solutions that stand the test of time. Softaims has encouraged me to grow beyond coding—to think about design, communication, and sustainability in technology. I see every project as part of a larger ecosystem, where small details contribute to long-lasting results. My daily motivation comes from collaborating with people who share the same passion for doing meaningful work, and from seeing the tangible difference our efforts make for clients around the world. More than anything, I value the culture of learning and improvement that defines Softaims. It’s a place where ideas evolve through teamwork and constructive feedback. My goal is to continue refining my craft, exploring new approaches, and contributing to solutions that are not only efficient but also elegant in their simplicity.
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Developed a ChatGPT-like chatbot using Llama.cpp, Chroma, and Streamlit with Retrieval-Augmented Generation (RAG). The system ingests Markdown files and answers user queries based on their context, enabling accurate, conversation-aware responses. Delivered an interactive UI, efficient embeddings storage/retrieval, and smooth conversational flow.
Built a Python solution using reinforcement learning and dynamic programming to select a single buy–sell pair that maximizes profit. Ingested six feature sets and price series across timeframes, framed the task as an MDP, and implemented value/Q-learning with backtesting under the 1-buy/1-sell constraint. Delivered notebook, visualizations, and a step-by-step client walkthrough. Output: best buy day, best sell day, and cumulative P&L.
Partnered with client to interpret and visualize survey data on relationship topics. Conducted exploratory data analysis (EDA), identified meaningful insights, and transformed complex survey responses into clear, compelling visualizations. Delivered interactive dashboards and charts during live Zoom collaboration sessions, ensuring real-time feedback and refinement. Final results provided the client with actionable insights and a presentation-ready dataset.
Developed a bespoke statistical framework to formalize a novel cost concept for a client’s whitepaper. Translated requirements into a closed-form formula with clear assumptions, built a parametric model, and delivered sample calculations to validate the concept. Provided sensitivity analysis and scenario testing to show robustness and limits. Results were documented in a publication-ready format aligned with the client’s desired whitepaper quality.
Performed advanced statistical analysis to study the impact of weight-loss drug use (Ozempic) on IVF outcomes across multiple patient groups. Cleaned and structured demographic and clinical data, including BMI, egg retrieval, embryo ploidy, and pregnancy results. Applied generalized estimating equations (GEE) to handle repeated cycles and outcomes per patient, ensuring robust modeling. Delivered actionable insights supporting research in reproductive medicine.
Master's degree in Data Science
2019-01-01-2021-01-01
in Data Analytics
2018-01-01-2019-01-01