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I was interviewed in Jan 2025.
A typical case interview.
I applied via LinkedIn and was interviewed in Oct 2024. There were 2 interview rounds.
Banking industry related case
I currently hold the role of Senior Consultant in my organization.
Lead client engagements and provide strategic guidance
Manage project timelines and deliverables
Mentor junior team members and provide training
Collaborate with cross-functional teams to drive results
Guesstimate on number of cars sold
Growth case on growing a cobranding card
I am passionate about helping others achieve their full potential and making a positive impact in their lives.
I enjoy mentoring and coaching individuals to help them reach their goals
I find fulfillment in volunteering and giving back to the community
I am dedicated to continuous learning and personal development
I strive to create a supportive and inclusive environment for those around me
I am passionate about problem-solving, enjoy working with diverse clients, and thrive in fast-paced environments.
Enjoy problem-solving and finding innovative solutions
Excited about working with diverse clients and industries
Thrives in fast-paced and challenging environments
I applied via campus placement at Indian Institute of Management (IIM), Kolkatta and was interviewed before Apr 2023. There was 1 interview round.
DBSCAN is a density-based clustering algorithm that groups together points that are closely packed.
DBSCAN stands for Density-Based Spatial Clustering of Applications with Noise.
It groups together points that are closely packed based on two parameters - epsilon (eps) and minimum points (minPts).
Points are classified as core points, border points, or noise points.
Core points have at least minPts points within eps distanc...
KNN models are used for classification and regression tasks based on similarity to nearest neighbors, while K-means is a clustering algorithm based on distance to centroids.
KNN models assign a class label to a new data point based on majority class of its k-nearest neighbors
K-means clusters data points into k clusters based on distance to centroids
KNN is a supervised learning algorithm, while K-means is an unsupervised
Features to consider in designing a time series model
Identifying seasonality and trends in the data
Selecting appropriate lag values for autoregressive components
Choosing the right forecasting method (e.g. ARIMA, Exponential Smoothing)
Evaluating model performance using metrics like RMSE and MAE
I won a Kaggle competition by applying a combination of XGBoost and neural network models.
Won Kaggle competition by predicting housing prices using XGBoost and neural network models
Achieved top 5% ranking in the competition
Used feature engineering techniques to improve model performance
I was interviewed in Nov 2022.
I applied via Referral and was interviewed in Mar 2023. There were 3 interview rounds.
2 case studies asked, from topics picked up from my CV
based on 1 interview
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