NARESH REDDY BOREDDY
HYDERABAD
Summary
Experienced Artificial Intelligence (AI) Specialist with seven years of expertise in designing, developing, and deploying AI-driven solutions to solve complex business problems. Proficient in machine learning, deep learning, natural language processing (NLP), and computer vision, with hands-on experience in leveraging frameworks like TensorFlow, PyTorch, and Scikit-learn. Adept at building end-to-end AI pipelines, from data preprocessing and feature engineering to model deployment and monitoring.
Strong background in statistical analysis, algorithm optimization, and scalable system design, with proven success in implementing AI systems in [specific industries, e.g., healthcare, finance, or retail]. Skilled in cloud platforms (AWS, Azure,) and containerization technologies (Docker, Kubernetes) for deploying production-grade models. Passionate about staying at the forefront of AI advancements and applying ethical AI practices to ensure fairness, transparency, and compliance.
Overview
9
9
years of professional experience
1
1
Certification
Work History
AI/ML Engineer
Infosys Technologies (Australia) Pty. Limited
HYDERABAD
11.2021 - 10.2023
- Collect, clean, and preprocess raw data from various sources.
- Design and manage data pipelines to handle large volumes of structured and unstructured data efficiently.
- Ensure data quality, integrity, and consistency for machine learning models.
- Design, build, and train machine learning models tailored to business needs.
- Experiment with various machine learning algorithms and techniques, including supervised, unsupervised, and reinforcement learning.
- Optimize model performance using techniques like feature engineering, hyperparameter tuning, and regularization.
- Package and deploy models into production environments.
- Develop APIs, microservices, or applications to integrate models into end-user systems.
- Implement scalable solutions to handle real-time and batch predictions.
- Set up and manage machine learning frameworks (e.g., TensorFlow, PyTorch, Scikit-learn).
- Utilize cloud platforms (AWS, Google Cloud, Azure) for training, deployment, and monitoring.
- Work with containerization and orchestration tools, like Docker and Kubernetes, to scale models.
Data Scientist
HCL Australia
Sydney
02.2020 - 10.2021
- Gather data from various structured and unstructured sources, such as databases, APIs, web scraping, or third-party vendors.
- Clean, preprocess, and transform raw data into formats suitable for analysis.
- Handle missing data, outliers, and ensure data quality and integrity.
- Perform exploratory data analysis (EDA) to uncover patterns, trends, and relationships in the data.
- Generate meaningful insights using statistical and data visualization techniques.
- Identify key business metrics, and create actionable reports.
- Develop predictive and prescriptive models using machine learning algorithms.
- Implement statistical methods, regression analysis, clustering, classification, and deep learning techniques.
- Perform feature engineering to improve model accuracy and performance.
- Design and conduct A/B testing, and other experiments, to validate hypotheses.
- Optimize algorithms for efficiency, accuracy, and scalability.
- Use hyperparameter tuning and model evaluation techniques to improve performance.
Data Analyst
Renata solutions
HYDERABAD
02.2015 - 09.2017
- Gather data from various internal and external sources, including databases, APIs, and spreadsheets.
- Work with data engineers and IT teams to access and retrieve relevant datasets.
- Verify data accuracy and integrity during collection.
- Clean and preprocess raw data by handling missing values, duplicates, and inconsistencies.
- Transform data into usable formats for analysis, including normalizing, aggregating, or converting data types.
- Ensure data quality through validation techniques.
- Perform exploratory data analysis (EDA) to identify trends, patterns, and correlations.
- Analyze data using statistical techniques such as regression, hypothesis testing, and descriptive statistics.
- Break down large datasets to provide actionable insights for decision-making.
- Create clear and impactful visualizations using tools like Tableau, Power BI, Excel, or Python (Matplotlib, Seaborn).
- Develop dashboards and interactive reports to communicate key findings.
- Present insights and recommendations to stakeholders in a digestible format.
Education
High School Diploma -
University of Southernqueensland
Sydney11-2019
Skills
- python
- MySQL
- PostgreSQL
- Oracle Database
- Statistical modeling
- Neural networks
- Deep learning
- Model evaluation
- Machine learning
- TensorFlow
- PyTorch
- Keras
- Docker
- Kubernetes
Certification
- AWS solution architect assosiate
Languages
Telugu
First Language
English
Upper Intermediate (B2)
B2
Timeline
AI/ML Engineer
Infosys Technologies (Australia) Pty. Limited
11.2021 - 10.2023
Data Scientist
HCL Australia
02.2020 - 10.2021
Data Analyst
Renata solutions
02.2015 - 09.2017
- AWS solution architect assosiate
High School Diploma -
University of Southernqueensland
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