Senior AI/ML Data Scientist I (P3)

At Nielsen, we are seeking a Data Scientist to join our team. Are you passionate about pushing the boundaries with the latest advancements in AI/ML? Does the prospect of applying Cutting-edge AI research to develop industry-defining software solutions for audience measurement excite you?

In this role, you will be at the forefront of our mission, leveraging sophisticated machine learning and AI to deliver a comprehensive understanding of audience behavior. You will architect and implement AI/ML systems that unlock novel insights from complex audience data.

Skills: Strong understanding and experience in Statistical Modelling and techniques.

Demonstrated ability to work with high motivation and agility in a dynamic environment.

Education: Bachelor's or Master's degree in Computer Science, Statistics, Mathematics, Engineering, or a related quantitative field. Python (Expert): Strong proficiency in Python with extensive experience in libraries such as: Scikit-learn, Pandas & NumPy, Matplotlib, Seaborn, SciPy.

Statistical Modeling: Strong grasp of statistical concepts including hypothesis testing, probability distributions, regression analysis, and inferential statistics.

Data Preprocessing & Feature Engineering: Proven ability to handle missing data, outliers, categorical variables, scaling, normalization, and create impactful features from raw data.

Proficiency in unsupervised learning techniques (e.g., K -Means, hierarchical clustering, PCA).

Knowledge of ensemble methods and their practical application.

SQL: Solid proficiency in SQL for data extraction, manipulation, and analysis from relational databases.

Classical Machine Learning: Thorough understanding of supervised learning (e.g., Linear Regression, Logistic Regression, Decision Trees, Random Forests, Gradient Boosting Machines like XGBoost/LightGBM/CatBoost, SVMs, Naive Bayes, K-Nearest Neighbors).

Model Evaluation & Validation: Hands-on experience with cross-validation, regularization techniques, hyperparameter tuning (e.g., GridSearchCV, RandomizedSearchCV), and understanding of various evaluation metrics for classification and regression.

Version Control: Experience with Git and collaborative development workflows.

● Programming Languages: Python 

Problem -Solving: Excellent analytical and problem-solving skills with the ability to break down complex problems into manageable components.

Communication: Strong verbal and written communication skills to articulate technical concepts and insights effectively.

Department: Technology
Function: Information Technology
Experience Level: Not Applicable