Nikhil Anand

Product Manager

Boston, Massachusetts, United States4 yrs 10 mos experience

Most Likely To Switch

Key Highlights

Achieved 35% improvement in core metrics through ML models.
Developed end-to-end NLP Recommendation System.
Expert in A/B testing and data-driven decision making.

Stackforce AI infers this person is a Data Scientist with expertise in SaaS and Fintech industries.

Contact

anand.nik@northeastern.edu LinkedIn

Skills

Core Skills

Machine LearningData AnalysisRisk AssessmentData EngineeringData Science

Other Skills

A/B TestingAirflowAlgorithmsAmazon Web Services (AWS)Big Data AnalyticsCredit Risk ManagementData MiningData ModelingData RiskData VisualizationData WranglingDatabasesDeep LearningETLGoogle BigQuery

About

Data Scientist with 5+ years of work experience in collaborating with Business and Technical Stakeholders in decision-making, developing and deploying Machine Learning Models, and designing AB Experiments for product improvements. Improved core metrics and KPIs by more than 35% by developing an end-to-end ML model to create a more engaging NLP Recommendation System at Internshala and optimized large-scale data-pipelines at Wayfair to integrate physical retail pipelines with E-Commerce. Technical Skills: • Languages: Python, SQL, R, Scala, Java, SAS • Machine Learning: Regression, Gradient Boost, Random Forest, K-Means, ARIMA, Facebook Prophet, XGBoost, Ensemble Modeling, Supervised and Unsupervised Machine Learning, Feature engineering and extraction, Exploratory Data Analysis, Statistical Analysis, Model Productionalization, Deployment, and Monitoring. • Statistics: A/B Testing, Hypothesis Tests, Causal Inference, Multivariate Testing, Non-Parametric tests, Survival Analysis • Database/Tools: MySQL, MongoDB, PyTorch, Scikit-Learn, RDS, DynamoDB, Glue, Lambda, Tableau Other Skills: • Critical thinking • Problem-Solving • Data Storytelling • Communication Contact: imnikhilanand@gmail.com

Experience

4 yrs 10 mos

Total Experience

1 yr 7 mos

Average Tenure

1 yr 10 mos

Current Experience

Constant contact

Decision Scientist

Jul 2024 – Present · 1 yr 10 mos · Waltham, Massachusetts, United States · On-site

Built & deployed a customer churn prediction model using XGBoost, achieving ~80% recall in identifying at-risk customers. Leveraged SHAP values to interpret model predictions and surface key drivers of churn for business stakeholders.
Defined and refined Sales Ideal Customer Profiles (ICPs) by analyzing firmographic, geographic, lifetime value (LTV), and customer acquisition cost (CAC) data, enabling more targeted marketing campaigns and improved sales efficiency.
Developed and deployed a Health Score model to quantify user activity, enabling proactive risk detection and reducing churn.
Designed and implemented a churn monitoring and financial impact dashboard, tracking weekly churn risk predictions, model performance, key churn drivers, and estimated week-over-week revenue impact to support proactive retention strategies.
Engineered a metric monitoring system leveraging Shewhart anomaly detection rules to track business performance, reducing root cause analysis time by 12 man-hours.
Designed and deployed a web scraping and LLM-based solution to identify bad leads by extracting phone numbers from websites. This system prevented low-quality leads, safeguarding $6M in annual ELTV.
Conducted regression analysis to identify factors impacting customer acquisition in Canada and the UK, analyzing various features. Pinpointed key issues, resulting in a 17% reduction in acquisition costs.
Conducted time-series analysis using SARIMA to model seasonality across marketing channels, developing a forecasting framework for optimizing new user and sales predictions.
Developed LLM based solution to segregate Real Estate customers between Broker and Agent for traget marketing.

SQLPythonMachine LearningData AnalysisLarge Language Models (LLM)

Bank ozk

Data Risk Engineer

Sep 2023 – Jul 2024 · 10 mos · Little Rock, Arkansas, United States · On-site

Architected a comprehensive Risk Management pipeline utilizing the Commercial Mortgage Metric model, facilitating the rigorous analysis and monitoring of $350 million in mortgage loan credit risk.
Developed and operationalized an advanced Credit Risk framework to identify and mitigate active commitment risk for Marine and Recreational Vehicle Loans worth $112 million.
Conducted data validation for Moody's CMM and APA models to identify aggregate ~6% Data Risk and generated risk assessment reports for stakeholders.

SQLCredit Risk ManagementRisk AssessmentData AnalysisData Risk

Wayfair

Data Engineer

Jul 2022 – Dec 2022 · 5 mos · Boston, Massachusetts, United States · On-site

Implemented an ETL framework to integrate Kafka streams from Retail Assortment Tool for physical storefronts with eCommerce demand resulting in 25% reduction in workload, optimizing production & shipment processes.
Minimized aggregate manual work 40 hours per month by orchestrating data pipelines for Physical Retail inventory forecast that improved the operational efficiency, scalability, and error handling.
Implemented data pipeline to process unstructured data from RetailNext APIs on product assortment and placement. Informed downstream planning and decision-making, providing valuable insights for 50+ stakeholders.

SQLGoogle BigQueryPythonAirflowDatabasesData Engineering

Internshala

2 roles

Senior Data Scientist

Jan 2021 – Aug 2021 · 7 mos · Gurugram, Haryana, India · On-site

Delivered actionable insights to business stakeholders by analyzing user interaction with web page elements, resulting in a significant 13% increase in click-through rate (CTR) for Native Ads placement.
Conducted root-cause analysis to identify reduced Response-to-Message ratio, uncovering message invisibility after certain period. Recommend layout changes in chat module that resulted in ~9% increase in response rate.
Designed and executed 3 A/B experiments to improve conversion across campaign landing pages. Investigated user flow and shared product strategies, achieving an aggregate jump of 7% in core metrics.
Developed Recommendation Engine to enhance user personalization. Leveraged a pre-trained word2vec model to extract textual features combined with numerical features. The implementation resulted in an NDCG score of 0.85 and a significant 13% increase in secondary conversion.
Defined KPIs and successfully implemented a customer acquisition tracking framework. Conducted thorough source & medium-level segmentation, generating actionable insights that led to an impressive 12% reduction in CAC.

A/B TestingSQLPythonMachine LearningData AnalysisData Science

Data Scientist

Jun 2019 – Jan 2021 · 1 yr 7 mos · Gurugram, Haryana, India · On-site

Developed & implemented Smart Reply model for chat module leveraging LSTM-CNN-DNN architecture that achieved an accuracy of 95%. The model improved the interaction rate by 35% delivering exceptional results in improving user engagement.
Implemented an SVM-based text classifier, leading to an improvement of 21% in chat initiation rate. With an accuracy of 98% in identifying critical messages, the model prompted users to respond, yielding remarkable results.
Conducted analysis to develop an MVP subscription model with a focus on user retention. Assessed the potential impact of offering different subscription packages. Observed a controlled risk that increased revenue by 1.5%.
Achieved a notable 4% improvement in optimum productivity level through comprehensive analysis of users' post-fulfillment activity. Delivered strategic product recommendations to enhance the overall end-user experience.
Conducted analysis of an A/B test to evaluate personalized recommendations. Applied segmentation techniques to assess the conversion rate among valuable customers. Observed a notable increase of 12% in conversions.
Developed a memory-based Markov chain model to suggest tags on posts by analyzing the sequence of tags used. This change led to an increase in Tagged Posts Ratio of 80%.

A/B TestingSQLPythonMachine LearningData AnalysisData Science

Talkoye

Data Science Intern

Mar 2019 – May 2019 · 2 mos · New Delhi, Delhi, India

Implemented a voice assistant deploying Dialogue Flow to replicate online shopping by designing conversational intent.
Set up webhook services using APIs written in NodeJS and set up database on MySQL.

Myanalyticsmentor

Data Science Intern

Aug 2018 – Nov 2018 · 3 mos · Bengaluru, Karnataka, India

Developed Multinomial NB text-classifier to recognize subject and topic from questions posed in Engineering Examination with an F1 score of ~83%.
Produced the results of the model as subject-wise and topic-wise distribution leveraging Python libraries.

Mindmyweb

Software Developer Intern

Sep 2017 – Jan 2018 · 4 mos · New Delhi Area, India · On-site

Created dashboard for E-learning platform to manage Video Content, Question-Answers, and Marketing Campaigns.
Built dashboard for Inventory Management and tools for communicating users for an E-commerce platform.

Shiksha sankalp

Summer Intern

Jun 2016 – Jul 2016 · 1 mo · New Delhi Area, India

Assessed various slums in the western part of Delhi from the perspective of launching NGO's Learning Reward Program for underprivileged students.
Visited these slums and conducted a desk study for assessing the feasibility of implementing the model there.