Harshit Malik
@harshitmalik
Harshit Malik
@harshitmalik
Passionate about building intelligent systems and crafting seamless user experiences. Skilled in MERN stack, machine learning, and deep learning, with hands-on experience in AI projects like domain-sp
Passionate about building intelligent systems and crafting seamless user experiences. Skilled in MERN stack, machine learning, and deep learning, with hands-on experience in AI projects like domain-sp
New Delhi, India
HARSHIT MALIK
+91 9667480134 | [email protected] | linkedin.com/in/harshitmalik22/| github.com/HarshitMalik22
Proffesional Summary
Data Scientist with 1+ years of experience in machine learning, predictive modeling, and cloud-based solutions.
Improved customer retention by 20% and automated data pipelines (30% faster processing) at SEO-DNA. Skilled
in Python, SQL, AWS, and NLP. Pursuing IBM Data Science Professional Certificate. Education
B.Tech in Computer Science (AIML)
Jagannath University, New Delhi | Aug 2022 – Present | CGPA: 8.5
Relevant Coursework: Machine Learning, Deep Learning, Big Data Analytics, Distributed Systems
Certifications
IBM Data Science Professional Certificate(In Progress)
Skills
Programming Languages: Python, SQL, R
ML/DL Frameworks: TensorFlow, PyTorch, scikit-learn, spaCy
Cloud & Big Data: AWS (S3, EC2, Lambda), Google Cloud, Hadoop, Apache Spark
Data Tools: Pandas, NumPy, Tableau, Matplotlib, Power BI
Data Engineering: EDA, Data Pipelines, Model Deployment (Flask), A/B Testing
Other: Git, OpenCV, MediaPipe, Problem-Solving
Experience
Data Science Intern – SEO-DNA, Ottawa, ON | July 2024 – December 2024
Boosted customer retention by 20% via EDA-driven insights and targeted retention strategies. Built predictive churn models (XGBoost, scikit-learn) with 15% higher accuracy than baseline. Automated data pipelines using Python and AWS Lambda, reducing processing time by 30%. Designed Tableau dashboards for real-time executive decision-making (adopted company-wide). Collaborated with engineers to deploy fraud detection models (TensorFlow, Flask) into production. Projects
Stock Sentiment Analysis
Scraped financial news using Python/BeautifulSoup and classified sentiment via LSTM models (TensorFlow). Reduced analysis time by 40%; achieved 89% F1-score on Financial PhraseBank dataset. Bicep Curl Counter:
Developed real-time exercise tracker with OpenCV/MediaPipe, achieving 95% accuracy in rep counting. Provided real-time feedback for users to monitor their performance, achieving a 95% accuracy rate. Awards
Best Data Science Intern, SEO-DNA (2024): Recognized for implementing predictive analytics. Hackathon Winner, Jagannath University