Responsibilities

* Lead strategic and cross-functional programs focused on protecting user data.
* Partner with cross-functional privacy and security stakeholders (e.g., product, program, privacy and engineering teams) across Privacy Safety Security (PSS), and Protected Data (PD).
* Provide technical direction and influence process, policy, and technical implementations to improve privacy and security posture, and scale programs and teams.
* Manage stakeholders, risks, and dependencies for programs and represent programs from a technical, business, program perspective to leadership.
* Develop roadmaps and implementation plans to drive execution across multiple organizations, communicate, collaborate, and negotiate with internal and external partners.

Minimum qualifications:

* 10+ years of experience managing technical projects in the software engineering domain.
* Experience leading cross-functional programs with stakeholders in technical organizations. Preferred qualifications:
* Experience establishing methods, tools, and process improvements for groups or organizations.
* Experience delivering software products, with knowledge in project management.
* Ability to take ownership, manage multiple priorities in an ambiguous operations environment, and deliver outstanding results.
* Ability to collaborate.
* Excellent leadership skills across organizational and team boundaries.
* Excellent verbal and written communication and presentation skills with the ability to interact with technical and non-technical groups.

Pyspark, dataproc, spark, python, GCP, Machine learning models, tensor flow, PyTorch
At least 8-10 year’s experience in data science models.
The Senior Data Scientist is responsible for end-to-end data science solutions for our data products.
Has experience with traditional, as well as modern
Machine Learning/Statistical techniques, including Regression, Classification, Ensemble Methods, Deep Learning
Works closely with data engineers, analysts, ML
Engineers and application developers to help build ML and processes.
You have experience with deep learning libraries like TensorFlow and/or PyTorch as well as experience with Spark and/or Hadoop.
Have strong knowledge of Statistics, Machine Learning, Deep Learning, and NLP/NLU.
Have applied industry experience in NLP/NLU, forecasting, and Anomaly detection solution development.
Built solutions that are easy to integrate into external frameworks or existing platforms.
You bring a strong engineering mindset and exposure to software engineering principles, and Agile methodologies.
Functional knowledge of Google Cloud Platform or Azure Machine Learning Platform and their ML and compute components.
Experience in Retail customer behavior analysis and designing algorithms on the Hadoop ecosystem at scale
Experience with data pipeline and workflow management tools: Airflow, Kubeflow & Kafka topic, etc would be beneficial.
You have experience with deep-learning libraries like
TensorFlow and/or PyTorch as well as experience with Spark and/or Hadoop.
Have strong knowledge of Statistics, Machine
Learning, Deep Learning, and NLP/NLU.
Have applied industry experience in NLP/NLU,
Forecasting and Anomaly detection solution development.
Built solutions that are easy to integrate into external frameworks or existing platforms.
You bring a strong engineering mindset and exposure to software engineering principles, and Agile methodologies.
Functional knowledge of Google Cloud Platform or
Azure Machine Learning Platform and their ML and compute components.
Experience in Retail customer behavior analysis and designing algorithms on the Hadoop ecosystem at scale
Experience with data pipeline and workflow management tools: Airflow, Kubeflow & Kafka topic, etc would be beneficial.