- Working with Rajkrishna is a privilege. His data expertise and dedication make him a driving force for success.Arjun Sharma, Data Analyst
- His data prowess is exceptional. He turns complexity into clarity effortlessly. A true asset to any team!Kavita Das
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About me
Hi, I'm Raj, and I'm a seasoned Data Scientist with over 2.5 years of hands-on experience and has a strong foundation in Computational Mathematics, holding a PhD from MNNIT Allahabad, India. My journey in data science has involved leading teams, collaborating with key stakeholders, and applying mathematical principles to transform data into actionable insights. I'm also passionate about mentoring and guiding emerging talents in the data science field.
Here's a glimpse of my toolkit:
🛠️ Programming Languages: Proficient in C, C++, Python, R, and SQL.
🧰 Tools/Packages: Skilled in the Python ecosystem for data analysis (Scikit-Learn, Numpy, Pandas, Statsmodels, Seaborn, Plotly, Matplotlib, TensorFlow, Keras, Spacy, NLTK, RegEx, PySpark, PyTorch), FastAPI, Flask, Git, MySQL, AWS, MATLAB, Excel, Tableau, Power BI, Langchain, Llama Index.
📊 Analysis: Experienced in modeling large datasets with Machine Learning and Deep Learning, Natural Language Processing, Prompt Engineering for LLM, time series analysis, numerical integration of complex systems (ODEs/PDEs, CFD), Big Data, Complex Decision Making, Medical Diagnostic, and Qualitative Research.
🤝 Interpersonal: A natural problem-solver with a passion for tackling new challenges and technologies. I possess the ability to rapidly learn and absorb unfamiliar concepts, work autonomously or within a group, coordinate small teams, and communicate and present with finesse.
Here's how I can assist you:
📋 Prompt Engineering: Designing effective prompts for Large Language models.
🤖 Artificial Intelligence: Harnessing AI to tackle complex problems.
📜 Natural Language Processing: Unraveling data's linguistic nuances for deeper insights.
📐 Mathematics for Data Science: Applying mathematical principles for robust analysis and modeling.
📊 Decision Science: Turning raw data into valuable insights for informed decision-making.
📚 Qualitative Research: Uncovering profound insights through qualitative data.
🧐 Complex Decision Making: Solving intricate problems with data-driven precision.
🔬 Soft Computing: Applying fuzzy logic and neural networks for smarter decisions.