Help & Supportcareers@gravityer.com
Data Science with 1+ years in Machine Learning & Data Analytics
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
Data Scientist with 1+ years of experience in SQL, Python, Machine Learning, and Data Analytics. Skilled in developing predictive models, customer segmentation, fraud detection, and data-driven decision-making. Strong experience in SQL-based data extraction, transformation, and analytical reporting. Familiar with risk analytics, customer behavior analysis, and large-scale data processing. Proficient in Power BI, ETL pipelines, and statistical modeling to support business and operational decisions.
Mahatma Gandhi University
M.Sc · Data Science & Analytics
August 1, 2021 – June 30, 2023
Calicut University
B.Sc · Mathematics
August 1, 2018 – June 30, 2021
KForce
QA Automation Engineer (Backend & API Testing)
January 1, 2025 – November 1, 2025
Pune, Maharashtra, India
Live Local (LILO)
Data Analyst
May 1, 2024 – December 1, 2024
Thiruvananthapuram, Kerala, India
Customer Risk Segmentation
June 25, 2026 – Present
Applied K-Means and DBSCAN clustering to segment customers based on transaction behavior, generating risk-based customer groups for targeted monitoring, analysis, and business decision-making.
Fraud Detection Model
June 25, 2026 – Present
Built and optimized XGBoost and Random Forest classification models to identify suspicious transactions, improving detection accuracy through feature engineering, hyperparameter tuning, and performance evaluation using Precision, Recall, F1-Score, and ROC-AUC.
Cultural Fit Analysis
The candidate's background includes both data analysis/science and QA automation, showing adaptability and a willingness to learn diverse technical areas. The personal projects demonstrate initiative and a passion for data science beyond formal employment. The target role of Data Science aligns well with the candidate's educational background and project experience. The breadth of skills across data analysis, machine learning, and data engineering tools suggests a versatile individual who could integrate well into a dynamic technical team.
Soft Skills & Operational Fit
The candidate's project descriptions and experience indicate an ability to work in Agile Scrum teams and track defects, suggesting good operational fit. The detailed descriptions of model evaluation and data pipeline orchestration imply a methodical and quality-oriented approach. However, direct evidence of specific soft skills like leadership, conflict resolution, or advanced communication in team settings is not explicitly provided.