RISHIKA LEKKALA

Atlanta, GA | lekkalarishika06@gmail.com | +1 (659) 8955878 | www.linkedin.com/in/rishikareddylekkala/

Experienced Data Scientist with over 3 years in deploying AI models, optimizing large-scale data processing, and implementing robust ML
pipelines. Specialized in LLMs, NLP, and cloud platforms, driving project efficiency and system performance improvements across healthcare
and gaming industries.
PROFESSIONAL EXPERIENCE
Data Scientist Oct 2023 – Jan 2024
Radical AI
• Spearheaded the development and deployment of AI-powered chatbots using Python with TensorFlow/PyTorch for NLP
models, achieving an average F1 score of 0.85 in real-time player intent classification.
• Facilitated the implementation of dynamic dialogue systems using Python, driving a 30% increase in player engagement
measured by daily active users (DAU).
• Teamed up on player profiling and personalization using Python and NLTK, resulting in a 25% improvement in player
retention measured by churn rate reduction.
• Contributed to developing AI-driven tools using Python and GPT-3 to generate over 1,000 unique storyline variations,
enriching content diversity and boosting average session length by 15%.
• Assisted in applying sentiment analysis techniques with Python and VADER, achieving a sentiment polarity score
improvement from 0.5 to 0.7.
• Supported the visualization of insights using Tableau for effective communication and decision-making, accelerating the
implementation of gameplay improvements by 20% based on player feedback.
Data Scientist Aug 2022 – Oct 2023
University of Alabama at Birmingham
• Pioneered advanced data-driven solutions for clinical decision support using Python, TensorFlow and Big Data, resulting in
improved diagnostic accuracy and better patient outcomes, aiding over 5,000 clinical decisions monthly.
• Engineered and deployed algorithms in Python with scikit-learn and XGBoost to identify patients at high risk for diabetes,
heart disease, and sepsis, reducing adverse events from 50 to 40 events per month.
• Developed models leveraging TensorFlow and Keras to analyze symptoms, lab results, and medical history, reducing
diagnostic time from 1 hour to 42 minutes annually for over 10,000 cases.
• Implemented Power BI to monitor patient outcomes, gathering feedback that enhanced predictive accuracy from 85% to
93% over a year.
• Orchestrated model monitoring and retraining using AWS and Apache Spark, adapting to new data streams of 100,000
records monthly to maintain and improve accuracy.
• Collaborated with healthcare professionals to integrate predictive models into clinical workflows, providing actionable
insights to over 200 clinicians.
• Utilized SQL and Apache Spark for ETL processes, integrating EHR data from multiple sources, improving model accuracy
from 70% to 85% over 12 months.
Data Associate Aug 2021 – Jun 2022
Accenture
• Conducted in-depth financial data analysis using advanced mathematics, statistics, Excel functions and statistical modeling
tools, identifying key market risks and recommending strategic adjustments that resulted in a $1.5 million reduction in
operational costs.
• Engineered and deployed automated ETL workflows with Informatica, enhancing data accuracy by 25 basis points and
accelerating financial reporting cycles by 30%.
• Leveraged Python for data manipulation and data analytics and Tableau for dashboard creation and data visualization,
delivering actionable insights that optimized resource allocation and contributed to a 15% increase in ROI on strategic
investments.
• Led interdisciplinary teams in developing predictive and data models incorporating regression analysis and machine learning
algorithms, achieving 90% accuracy in forecasting market trends and reducing potential financial risks by $2 million annually.
• Presented comprehensive reports to senior management, translating complex financial analyses into actionable
recommendations that facilitated business analytics and improved capital efficiency by 20%.
Associate Developer Jan 2021 – Jul 2021
Void Main Technologies
• Designed and implemented an automated ETL pipeline using Python and SQL, increasing data processing efficiency by
40% and handling millions of data points daily with a 20% reduction in latency, enhancing service delivery.
• Conducted extensive performance testing and optimization, ensuring the ETL pipeline's scalability and reliability, supporting
a 50% increase in data throughput and reducing operational delays by 30%.
• Utilized Django and FastAPI frameworks for building robust and scalable web applications, improving development
efficiency and reducing time-to-market, increasing client satisfaction and improved performance management.
EDUCATION
Masters in Computer Science | University of Alabama at Birmingham Aug 2022 – May 2024
 • Coursework: Machine learning, Deep Learning, Data Mining, Foundations of Data Science, Database Systems, Software
Engineering, Cloud Security, Computer Security, Cyber risk Management, Database App Development, Data structures.
SKILLS
• Programming Languages: Python, Java, R • ML: Neural Network Training, Fine-Tuning, and Deployment
• Data Wrangling: Pandas, NumPy, SciPy • Deep Learning: TensorFlow, PyTorch, Distributed
• Database: MySQL, PostgreSQL, SQL Server, MongoDB Inference/Tuning for LLMs, Diffusion Models
• Cloud: AWS Sage maker, Lambda, S3, Glue, Redshift, • Optimization: ML Performance Profiling, Graph-level
Athena, EC2, GCP, Azure • Web Services: RESTful APIs, SOAP web services
• Visualization: Tableau, MS Power BI, Matplotlib, Seaborn, • IDE’s: Jupyter Lab, PyCharm, VS Code
Quick sight • Project Management: Agile, JIRA, SDLC, Waterfall
• Machine Learning: KNN, Linear & Logistic Regression • Version Control: GitHub, GitLab, SVN, Docker.