Remote Principal Data Scientist, Predictive Modeling at Nielsen

Description:

The Principal Data Scientist, Predictive Modeling at Nielsen will design, test, and implement recommendation engine models to convert sparse datasets into synthetic datasets, requiring proficiency in coding from scratch.
The role involves proving model validity through analytic research, such as holdouts, and communicating predictive power to both internal teams and clients.
The candidate will use iterative modeling to identify ideal parameters for sparse data, including minimum completeness levels and key datapoints for predictive accuracy.
The position requires consulting with internal and external partners on sourcing ideal sparse data based on analytic findings.
The Principal Data Scientist will support the screening and hiring of other data scientists and assist in onboarding and developing junior staff.
The role includes defining and implementing a vision for scaling new models across larger datasets, focusing on efficiency in speed and computer usage.
The candidate will support automation for routine processes and pilot programs for research and development purposes.
Conducting tactical or strategic analyses to address business and customer opportunities is also part of the responsibilities.
The use of tools such as Python, R, and SPSS for complex data analysis and automating procedures is required.
The candidate will develop, test, and implement high-quality, modular Python code for integration into existing production systems.
The role involves developing and implementing machine learning solutions to leverage big data from various sources and assisting with ad hoc analyses and projects.

Requirements:

An undergraduate or graduate degree in Mathematics, Statistics, Social Science, Engineering, Computer Science, Economics, Business, or related fields that require rigorous data analysis and strong statistical skills is required.
The candidate must have 10+ years of relevant data science experience, particularly in predictive modeling and recommendation engines.
Strong skills in Python and relevant packages, including PyTorch, along with familiarity with other scripting languages, are essential.
Knowledge of statistical tests and procedures such as Correlation, Regression, Hypothesis Testing, Segmentation Techniques, ANOVA, Chi-squared, Student t-test, and Time Series is required.
Familiarity with machine learning and data modeling techniques, including Decision Trees, Random Forests, Incremental Response Modeling, Scoring, SVM, Neural Networks, and Credit Scoring, is necessary.
The candidate must possess strong critical thinking and creative problem-solving skills, as well as strong planning and organizational skills.
Excellent verbal, presentation, and written communication skills, along with fluency in English, are required.
Demonstrated success in a time-critical production environment is essential.
Familiarity with SQL, Oracle, or other relational database software for manipulating large datasets is required.
Knowledge of BI tools such as Spotfire, Tableau, or other data visualization software is necessary.
Proficiency in the MS Office suite (Excel, PowerPoint, Word) and/or Google Office Apps (Sheets, Docs, Slides, Gmail) is required.
Knowledge of the Atlassian suite of software, including Bitbucket, Confluence, Jira, Hipchat, Crucible, and Fisheye, is preferred.
Familiarity with the Apache Spark ecosystem, Databricks, and AWS is also required.

Benefits:

Joining Nielsen means being part of a dynamic team committed to excellence and making an impact together.
The company champions employee success, ensuring that when employees succeed, the organization does too.
Employees will have the opportunity to work in a collaborative environment that fosters continuous improvement and operational efficiency.
The role offers the chance to build new capabilities and drive business advancement.
Employees can expect a supportive work culture that values their contributions and encourages professional growth.