Senior Data Science Engineer
NokiaAbout the role
We are looking for a seasoned Data Science Engineer to join our Advanced Analytics team. In this role, you will be responsible for designing, developing, and optimizing scalable data science solutions and machine learning pipelines. Your work will support the deployment, monitoring, and performance tuning of models in production environments.
You’ll collaborate closely with data scientists, mobile core engineers, and application developers to deliver actionable insights through advanced network monitoring and troubleshooting platforms.
- Architect, develop, and maintain end-to-end ML Ops pipelines to support the full machine learning lifecycle, including model training, validation, deployment, monitoring, and retraining.
- Collaborate cross-functionally with data scientists and engineers to operationalize machine learning models and integrate them seamlessly into network applications.
- Design and build scalable analytics solutions using big data technologies such as Spark, Hadoop, and Databricks.
- Automate data workflows, including ingestion, transformation, and feature engineering, to streamline model development and deployment.
- Monitor model performance and system health, proactively detecting data drift and anomalies using modern observability and alerting tools.
- Champion CI/CD methodologies for ML and analytics projects, incorporating automated testing, validation, and deployment processes.
- Optimize infrastructure for performance, cost-efficiency, and reliability across both cloud and on-premises environments.
You have:
- 8+ years of experience in data science, machine learning engineering, or ML Ops roles.
- Advanced proficiency in Python and key ML/analytics libraries such as scikit-learn, TensorFlow, PyTorch, pandas, and NumPy.
- Hands-on experience with ML Ops tools and platforms like MLflow, Kubeflow, SageMaker, Vertex AI, and Airflow.
- Deep expertise in deploying, monitoring, and maintaining machine learning models in production environments.
- Strong background in data analytics and big data processing using technologies such as Spark and Hadoop, along with proficiency in SQL and NoSQL databases.
- Experience working with major cloud platforms (AWS, Azure, GCP) and containerization technologies (Docker, Kubernetes). Familiarity with CI/CD pipelines, Git, and DevOps best practices.
It would be nice if you also had:
- Experience with data visualization tools such as Tableau, Power BI, or Plotly.
- Knowledge of data privacy, security, and compliance considerations in ML and analytics workflows.
P.S: This is an onsite position based in Sunnyvale, California. Visa sponsorship and relocation assistance are not available for this role.
Come create the technology that helps the world act together
Nokia is committed to innovation and technology leadership across mobile, fixed and cloud networks. Your career here will have a positive impact on people’s lives and will help us build the capabilities needed for a more productive, sustainable, and inclusive world.
We challenge ourselves to create an inclusive way of working where we are open to new ideas, empowered to take risks and fearless to bring our authentic selves to work
What we offer
Nokia offers continuous learning opportunities, well-being programs to support you mentally and physically, opportunities to join and get supported by employee resource groups, mentoring programs and highly diverse teams with an inclusive culture where people thrive and are empowered.
Nokia is committed to inclusion and is an equal opportunity employer
Nokia has received the following recognitions for its commitment to inclusion & equality:
- One of the World’s Most Ethical Companies by Ethisphere
- Gender-Equality Index by Bloomberg
- Workplace Pride Global Benchmark
Join us and be part of a company where you will feel included and empowered to succeed.
Additional Information
US/Canada Nokia Offers a comprehensive benefits package that includes but is not limited to:
- Corporate Retirement Savings Plan
- Health and dental benefits
- Short-term disability, and long-term disability
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