Md S
The star rating is a representation of the overall rating, calculated as the mean of the client satisfaction rating, the average client interview rating, and internal interview scores.
The client satisfaction rating is the weighted average of client ratings, with weights based on reviewed work hours. When no client rating exists, the approval fraction (approved vs. reviewed work hours) determines it.
If the client satisfaction rating exceeds the overall rating, it becomes the star rating. In the absence of client ratings, if the average client interview rating is higher than the overall rating, it becomes the star rating. If no data is available, the star rating defaults to the internal interview score.
The client satisfaction rating is the weighted average of client ratings, with weights based on reviewed work hours. When no client rating exists, the approval fraction (approved vs. reviewed work hours) determines it.
If the client satisfaction rating exceeds the overall rating, it becomes the star rating. In the absence of client ratings, if the average client interview rating is higher than the overall rating, it becomes the star rating. If no data is available, the star rating defaults to the internal interview score.
Data Scientist Preferred Title
$20.00 /hr $ 50.0K /yr Hourly Rate and Yearly Salary
Overview
Basic Summary
LD Talent History - Average Response Time 12.0 hours
- Average Count of Messages/Day 0.3
- Project Completion Rate 2/4
- Interview Acceptance Rate 4/6
- Timezone Overlap 18h PST, 30h UTC
- Code Quality 60%
- Soft Skill Attributes 60%
- Expertise 2/3
- Coding Challenges 60%
- No. of Lifelong Learning Projects 2
- No. of Coding Challenges Completed 2 More details
- Technical Breadth 3.0/5
- Algorithmic Thinking 4.0/5
- Technical Strength 4.0/5
- Teamwork 3.0/5
- Intellectual Merit 4.0/5
- English Communication 4.0/5
- Desktop Windows
- Phone Android
- Member Since Apr 01, 2024
- Profile Last Updated Mar 07, 2024
- Last Activity April 21, 2024, 3:30 p.m. UTC
- Location India
Profile Summary
As an aspiring data scientist, I possess a strong foundation in data analysis and machine learning, utilizing tools such as Python, SQL, and Excel to extract, manipulate, and analyze data. With proficiency in Power BI, I effectively visualize and communicate complex data insights to facilitate informed decision-making. Combining my technical skills with a passion for problem-solving and statistical modeling, I am well-equipped to leverage these tools to drive data-informed business solutions.
Weekly Availability
Timezone Overlap with 06 - 21 per Week: 18h PST, 30h UTC
Day
Monday
Tuesday
Wednesday
Thursday
Friday
Saturday
UTC
11 - 16
11 - 16
11 - 16
11 - 16
11 - 16
11 - 16
PST
04 - 09
04 - 09
04 - 09
04 - 09
04 - 09
04 - 09
Vetting
- Interview Data
- Agile Development Process
- Productivity and Responsiveness
- Teamwork
- Software Engineering
- Logical Thinking
- Technical Strength
- Intellectual Merit
- English Communication
- Documentation
- System Design
- Coding Challenges60%
- Algorithms Score60%
- General Score60%
- Easy Algorithm
- Correctness60%
- Performance60%
- Medium Algorithm
- Correctness60%
- Performance60%
- Hard Algorithm
- Correctness60%
- Performance60%
- Expertise2/3
- Design Patterns and Architectures2/3
- Debugging2/3
- Stack Traces2/3
- Testing2/3
- System Administration2/3
- Soft Skill Attributes60%
- Entrepreneurial60%
- Whole Brained60%
- Divergent Thinking / Creativity60%
- Design Ability60%
- Empathy60%
- Project Management Ability60%
- Security60%
- Code Quality60%
- Complex Logic60%
- Models60%
- Controllers60%
- Templates60%
- APIs60%
- Training/Testing Data Models60%
- Code Readability60%
- Ongoing Evaluation
- Number of Lifelong Learning Project2
- Number of Coding Challenge Completed3
Experience
Data Scientist
Course Project
Apr 2023 - Jun 2024
Praxis Business School Company
Finance Industry
Project: Credit Risk Analysis
- Developed and implemented a supervised machine learning classification model using Python, incorporating KNN classifier, Logistic Regression and Decision Tree classifier to predict credit default.
- Conducted thorough data preprocessing and data cleaning along with feature engineering, optimizing predictor variables for enhanced model performance in real-world credit risk scenarios.
Data Scientist
Course Project
Apr 2023 - Jun 2023
Praxis Business School Company
Finance Industry
Project: Stock and Portfolio Analysis
- Utilized Python for comprehensive stock and portfolio analysis, employing various statistical metrics to compare individual stocks and assess portfolio performance.
- Applied descriptive and inferential statistics to evaluate risk and return characteristics, providing valuable insights for data-driven investment decisions.
Qualifications
Education
Praxis Business School
Feb 2023 - Nov 2024
Post Graduate Program (Data Science)
NMIMS Global School of Continuing Education
Jun 2022 - Jul 2022
PGDBM (Finance)
Courses
Praxis Business School