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Associate Data Scientist with 1+ years in Machine Learning & Python
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 Analyst with hands-on experience building end-to-end machine learning pipelines and translating complex data into actionable insights. Proficient in Python, SQL, and statistical modeling, with a strong track record of delivering predictive models achieving 90%+ accuracy. Background in enterprise technical support has sharpened communication, problem-solving, and stakeholder management skills. Seeking a data analyst or junior data scientist role where I can drive data-informed decisions.
Anjuman-Islam Kalsekar Technical Campus
Bachelor of Engineering · Mechanical
N/A – June 30, 2023
IT Vedant
Post Graduate Program · Data Science & Analytics
N/A – June 30, 2024
Mphasis
Technical Support Engineer (L2)
July 1, 2024 – July 1, 2025
Pune, Maharashtra, India
Cuisine Rating & Consumer Behavior Analysis
June 17, 2026 – Present
Built a predictive classification model to identify customer loyalty (repeat visitors) from a dataset of 200+ consumer profiles and restaurant ratings. Uncovered that Food and Service ratings share a 0.75 correlation with overall satisfaction through EDA — insight directly usable for restaurant strategy. Evaluated Logistic Regression, SVM (RBF Kernel), and Decision Trees; achieved 90% accuracy with SVM after standardizing features with LabelEncoder and StandardScaler.
View ProjectHousing Market Value Predictor
June 17, 2026 – Present
Engineered an end-to-end regression pipeline to estimate property values, applying multi-collinearity analysis via Seaborn heatmaps to select optimal features. Applied Ensemble Learning (Random Forest, AdaBoost), significantly outperforming baseline Linear Regression and SVR in predictive accuracy. Improved KNN regressor performance by standardizing features to eliminate scale bias across distance-based calculations.
View ProjectData Analysis Using Python
IBM
June 1, 2026 – Present
Python Essentials for Data Science
IBM
June 1, 2026 – Present
Cultural Fit Analysis
The candidate's academic projects demonstrate a proactive approach to learning and applying data science concepts. The transition from a Mechanical Engineering background to Data Science, coupled with relevant certifications, indicates a strong drive for continuous learning and adaptability. The technical support experience suggests an ability to work in structured environments and contribute to knowledge sharing, which aligns with collaborative team cultures. However, the lack of diverse project types beyond academic exercises and limited real-world data science experience might require some cultural integration into a fast-paced, industry-specific data science team.
Soft Skills & Operational Fit
The candidate's experience as a Technical Support Engineer (L2) at Mphasis highlights strong problem-solving, root-cause analysis, and communication skills. The ability to triage high-volume requests and translate technical findings for non-technical audiences demonstrates operational readiness and stakeholder management capabilities. These are valuable soft skills for a data scientist who needs to communicate insights effectively and manage project priorities.