Mohammed
Pune, Pune Division, Maharashtra, India
Experience: 1 years
Open to: Fractional, Full-Time, Part-Time
Education: Bachelors
Availability: Immediate
Skills: AWS, Azure, Cosmos DB, Data Warehouse, Docker, GCP, Git, LLMs/ChatGPT, Matplotlib, MongoDB, MySQL, NumPy, pandas, PostgreSQL, Postman, Power BI, PySpark, Python, Python3, PyTorch, R, scikit-learn, Tableau, TensorFlow
Previously worked at: Startups
Assessment Score: 50
- Emerging Data Scientist with a Solid Academic Foundation: Currently pursuing a B.Sc. in Computer Science from Vishwakarma University with a strong CGPA of 8.39, specializing in NLP, machine learning, and generative AI, and equipped with technical certifications in AI, MLOps, and big data analytics.
- Technical Expertise and Project Development: Proficient in Python, TensorFlow, PyTorch, Hugging Face, SQL, and cloud platforms (Google Cloud, AWS), with hands-on project experience in building predictive models (87% accuracy for churn prediction) and developing TensorFlow-based image classifiers with enhanced accessibility via GUI interfaces.
- Industry Experience in Data Science and NLP: Completed internships at TCS iON, The Spark Foundation, and Oasis Infobyte, gaining expertise in NLP, sentiment analysis, spam detection, and regression models, achieving high accuracy (up to 96%) in predictive and classification tasks.
- Versatile in Analytical and Visualization Tools: Experienced in exploratory data analysis, implementing advanced data preprocessing, and applying neural network architectures such as bidirectional LSTMs and Naive Bayes for real-world problem-solving.
- Recognized Achievements and Active Engagement: Achieved 2nd place in Tech Trivia 2023 and contributed significantly to team-oriented activities, showcasing adaptability, problem-solving, and collaboration skills.
- Passionate Learner and Innovator: Driven by a strong interest in reading research papers and leveraging AI to create impactful solutions, committed to continuous learning and application of advanced machine learning techniques in practical domains.