Manjunath Kalal

AI/ML Engineer and Data Scientist with 3+ years of experience building and deploying machine learning solutions, specializing in time-series forecasting, anomaly detection, sequence modeling, feature engineering, and large-scale data processing. Proficient in Python, SQL, PySpark, TensorFlow, PyTorch, Scikit-learn, XGBoost, Prophet, and MLflow, with hands-on experience developing production-ready ML pipelines, implementing model monitoring workflows, and designing scalable data solutions. Experienced in forecasting using ARIMA, SARIMA, LSTM, GRU, and deep learning models for behavioral and demand prediction problems.

Master's in Computer Science (Data Analytics) with expertise in developing reliable AI/ML systems and translating complex data insights into measurable business impact.

DATA SCIENTIST - Nielsen Media Pvt. Ltd. - Bengaluru, KA, India

(2025-04 - 2026-02)

Project: Common Homes Identification and Monitoring

• Designed feature engineering pipelines for behavioral sequence analysis by creating tuning-pattern similarity features, temporal alignment metrics, aggregation-based behavioral indicators to improve audience household identification.
• Built and evaluated machine learning models including Random Forest for common home identification and anomaly detection models such as Isolation Forest and Local Outlier Factor to identify abnormal behavioral patterns and improve data quality across high-volume telemetry datasets.
• Developed and evaluated time-series forecasting models including ARIMA, SARIMA, Prophet, LSTM, and GRU to forecast television tuning behavior patterns and audience viewing trends. Implemented sequence modeling experiments using PyTorch to explore deep learning approaches for behavioral forecasting and future scalability with larger datasets.
• Designed scalable batch data processing pipelines using PySpark, Spark, Databricks, and Airflow to automate daily and monthly feature generation, tuning alignment metric calculation, model input preparation, and data validation workflows.
• Implemented MLflow-based experiment tracking and model lifecycle workflows to manage model evaluation, compare machine learning experiments, and improve reproducibility across anomaly detection and behavioral matching models.
• Developed monitoring dashboards using Tableau to track model performance indicators, tuning alignment metrics, anomaly trends, and data quality signals, enabling stakeholders to identify operational issues and assess model reliability.
• Applied statistical analysis and root cause investigation on anomalous data patterns, collaborating with engineering and business teams to resolve data quality issues and improve downstream viewer and demographic assignment workflows.

DATA SCIENCE INTERN - Dimension64 Consulting Pvt. Ltd. - Bengaluru, KA, India

(2024-07 - 2025-03)

• Developed and evaluated time-series forecasting models including ARIMA, SARIMA, and RNN-based approaches using sales data to improve demand forecasting, inventory planning, and business decision-making in the FMCG domain.
• Performed time-series data preprocessing, feature engineering, trend and seasonality analysis, lag feature generation, and model evaluation to improve forecasting accuracy and reliability.
• Developed predictive lead scoring models using machine learning algorithms including XGBoost and Scikit-learn by integrating demographic and web analytics data to identify high-conversion customers and improve sales prioritization.
• Conducted statistical analysis, regression modeling, and A/B testing to evaluate marketing campaign performance, identify customer behavior patterns, and generate actionable insights for improving campaign effectiveness and ROI.
• Collaborated with cross-functional teams to translate business requirements into analytical solutions, supporting data-driven decision-making across forecasting, pricing optimization, and customer analytics initiatives.

ANALYST – DATA OPERATION - Nielsen Sports India Pvt. Ltd. - Bengaluru, KA, India

(2021-04 - 2022-10)

• Performed data annotation, labeling, and quality validation across television broadcasts, digital media content, news articles, and audio transcripts to generate reliable training and analytical datasets.
• Applied data preprocessing and consistency validation techniques on high-volume datasets, ensuring data accuracy and reliability for downstream reporting, analytics, and machine learning workflows.
• Analyzed brand exposure data across TV, digital, and social media channels using statistical techniques to evaluate advertising performance, audience engagement, and campaign effectiveness.
• Automated data collection and preprocessing workflows using Python-based web scraping scripts, improving efficiency in competitor intelligence, brand monitoring, and analytical data preparation.

BUSINESS ANALYST - Klinchko Fasteners - Bengaluru, KA, India

(2019-10 - 2021-03)

• Collaborated with B2B clients and internal engineering, production, and operations teams to gather requirements, translate business needs into actionable solutions, and improve operational workflows.
• Developed interactive Excel and Power BI dashboards to visualize sales performance, customer behavior, demand trends, and operational metrics, enabling data-driven decision-making.
• Partnered with supply chain and operations teams to analyze demand patterns, optimize production planning, and improve delivery efficiency through data-driven insights.
• Communicated analytical findings and recommendations to business stakeholders, supporting strategic decisions and continuous process improvements.

Master of Science - Computer Science (Data Analytics) - Mahatma Gandhi Rural Development & Panchayat Raj University Gadag, KA, India

Bachelor of Engineering - Mechanical Engineering - Tontadarya College of Engineering Gadag, KA, India