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Data Optimisation Jobs in California (NOW HIRING)

Within the Data Operations organization, the Capacity Planning & Analytics team provides ... You will translate behavioral insights and empirical findings into optimized project structures and ...

Within the Data Operations organization, the Capacity Planning & Analytics team provides ... You will translate behavioral insights and empirical findings into optimized project structures and ...

Data Scientist

San Francisco, CA · Remote

$160K - $200K/yr

... data scientist. Federato is a venture backed company funded by some of the most prominent VC's in ... We build software to help large insurance carriers improve their portfolio optimization. Our goal ...

Data Scientist

San Francisco, CA · On-site +1

$160K - $200K/yr

... data scientist. Federato is a venture backed company funded by some of the most prominent VC's in ... We build software to help large insurance carriers improve their portfolio optimization. Our goal ...

Systems PhD - Software Engineer

Mountain View, CA · On-site

$205K - $244K/yr

Responsibilities : • Query compilation & optimization • Distributed query execution and scheduling • Vectorized engine execution • Data security • Resource Management • Transaction ...

Data Engineer

California City, CA · On-site

$140K - $168K/yr

Snowflake (Hands-on Implementation & Optimization) * Advanced SQL * Complex SQL Queries * SQL Query Optimization * Performance Tuning * Python * Data Engineering * Automation Scripting * Data ...

Required : • Gurobi Optimization • Developing predictive models in the area of marketing • Understanding business problems and translating it into data mining problems • Applying techniques ...

Required : • Gurobi Optimization • Developing predictive models in the area of marketing • Understanding business problems and translating it into data mining problems • Applying techniques ...

Showing results 21-40

Data Optimisation information

What are the most common challenges faced in a data optimisation role, and how can I prepare for them?

One of the main challenges in a Data Optimisation role is dealing with large, complex datasets that may have inconsistencies or missing information. You’ll often need to balance improving data quality with maintaining data integrity and system performance. Collaborating across departments, such as IT, analytics, and business operations, is typical, so strong communication skills are essential. Preparing by learning best practices in data cleaning, ETL processes, and familiarizing yourself with relevant tools will help you succeed and adapt quickly.

What are the key skills and qualifications needed to thrive as a data optimisation specialist?

To thrive as a Data Optimisation Specialist, you need strong analytical skills, proficiency in data analysis, and a background in statistics or computer science, often supported by relevant degrees or certifications. Familiarity with data management tools like SQL, Python, Excel, and optimisation platforms such as Google Analytics or Tableau is typically required. Excellent problem-solving abilities, attention to detail, and effective communication are essential soft skills for translating insights into actionable strategies. These skills ensure that data-driven decisions are accurate, impactful, and aligned with business objectives.

What are data optimisation jobs?

Data optimisation jobs involve analyzing and improving data quality, structure, and efficiency to support better decision-making and operational performance. These roles often require skills in data analysis, database management, and tools like SQL or data visualization software, with a focus on enhancing data accuracy and accessibility.

What is data optimisation?

Data optimisation refers to the process of improving the quality, accessibility, and efficiency of data within an organization. It involves cleaning, structuring, and organizing data so that it can be used more effectively for analysis, decision-making, and business operations. Data optimisation can help reduce storage costs, enhance system performance, and ensure that accurate and relevant data is available when needed. This process often includes data deduplication, compression, and the implementation of best practices for data management.

What is the difference between Data Optimisation vs Data Analysis?

AspectData OptimisationData Analysis
Primary FocusImproving data processes and system efficiencyInterpreting data to uncover insights
Skills RequiredData management, process improvement, technical skillsStatistical analysis, reporting, critical thinking
Work EnvironmentIT teams, data engineering, system optimizationBusiness units, research teams, analytics departments
CertificationsData management, database certificationsData analysis, statistical certifications

Data Optimisation focuses on enhancing data systems and processes for efficiency, while Data Analysis involves examining data to generate insights. Both roles require strong technical skills, but their objectives differ: one improves data infrastructure, the other interprets data for decision-making.

What are popular job titles related to Data Optimisation jobs in California? For Data Optimisation jobs in California, the most frequently searched job titles are:
What job categories do people searching Data Optimisation jobs in California look for? The top searched job categories for Data Optimisation jobs in California are:
What cities in California are hiring for Data Optimisation jobs? Cities in California with the most Data Optimisation job openings:
Infographic showing various Data Optimisation job openings in California as of August 2026, with employment types broken down into 1% As Needed, 82% Full Time, 13% Part Time, and 4% Contract. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution.

Senior Data Scientist, Cloud Gaming - Prescriptive Analytics and Optimization

Nvidia

Santa Clara, CA • On-site

Full-time

Re-posted yesterday


Nvidia rating

9.6

Company rating: 9.6 out of 10

Based on 17 frontline employees who took The Breakroom Quiz

8th of 242 rated software companies


Job description

Our team is building an innovative Data Platform that employs advanced analytics, including prescriptive modeling and constrained optimization, for real-time routing and scheduling at scale.

This platform encompasses data collection, processing, visualization, analysis, anomaly detection, root cause identification, and predictive modeling. Our data include GPU availability/lifecycle, latency measurements from end users to data centers, game performance across different GPU types, and queuing information. Our active projects include applying optimization techniques to the cloud gaming experience; developing user behavior profiling, user base segmentation, actionable cluster detection, effective personalized recommendations, lifetime value analysis, and critical areas such as capacity management, prescriptive scheduling, and subscription churn analysis. We also focus on time-series forecasting, decision-making models, resource allocation, and latency minimization.

You will wield the power of Data, AI, and Operations Research to help deliver a best-in-class cloud streaming performance and experience to our users across the world. Our technology stack relies on industry-standard components (Python, SQL, Delta Lake, Apache Spark, Databricks, MLflow, Grafana, Elasticsearch).

What You will be Ding:

  • Build and deploy scalable ML/AI and optimization models to enhance demand forecasting, optimize capacity allocation, and develop user-specific feature engineering for real-time cloud gaming services.

  • Develop reusable framework deployments for data ingestion, processing, and analysis to support dynamic user interventions for targeted business outcomes.

  • Acquire and apply domain knowledge of the product and software stack to identify and drive the resolution of data inconsistencies and improve model performance, especially in the context of optimization outcomes.

  • Identify, analyze, and interpret trends or patterns in complex data sets using supervised and unsupervised learning techniques, informing prescriptive solutions.

  • Design and implement improvements to real-time prescriptive scheduling pipelines, using techniques like linear programming and constraint optimization, to enhance capacity utilization and user retention.

  • Improve productivity of the organization by mining petabytes of data for actionable insights for business and engineering, often through prescriptive recommendations.

  • Collaborate with a variety of partners to understand requirements, design robust solutions, and guide the team to deliver impactful results.

  • Leverage agentic AI to deliver best-in-class automation and programming solutions for complex analytical problems.

What We Need to See:

  • BS/MS (or equivalent experience) with 6+ years of experience or PhD in Data Science, Computer Science, Operations Research, Statistics, Applied Mathematics, or related quantitative fields, with a strong emphasis on prescriptive analytics and optimization.

  • Strong background knowledge and practical experience in probability, statistics, AI/ML, prescriptive modeling, and optimization methodologies (e.g., linear programming, network flow, decision theory, and multi-armed bandit).

  • Strong coding skills, including the ability to write readable, testable, maintainable, and extensible code (primarily Python), with experience in libraries or tools relevant to optimization (e.g., Google OR-Tools).

  • Experience with common tools for data storage and processing, including drilling into problems of running large-scale software across large clusters

  • Strong experience in data cleaning, aggregation, transformation, and extraction, with an understanding of how data quality impacts performance.

Ways to Stand Out from the Crowd

  • Good interpersonal and presentation skills in working with multiple partners, adept at explaining intricate analytical solutions and their business implications.

  • Experience in time series analysis and forecasting for demand prediction in optimization contexts is a plus.

  • Experience in active ML production pipelines (MLflow, Kubeflow) with a focus on deploying and monitoring optimization models is a plus.


We are an equal opportunity employer and value diversity at our company. We do not discriminate on the basis of race, religion, color, national origin, sex, gender, gender expression, sexual orientation, age, marital status, veteran status, or disability status. We will ensure that individuals with disabilities are provided reasonable accommodation to participate in the job application or interview process, to perform essential job functions, and to receive other benefits and privileges of employment. Please contact us to request accommodation.

Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 184,000 USD - 287,500 USD.

You will also be eligible for equity and benefits.

Applications for this job will be accepted at least until July 20, 2026.

This posting is for an existing vacancy.

NVIDIA uses AI tools in its recruiting processes.

NVIDIA is committed to fostering an inclusive work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.#deeplearning

What Nvidia employees say

Pay

Benefits

Hours and flexibility

Workplace

Get the full story on Breakroom


Nvidia logo

About Nvidia

Sourced by ZipRecruiter

NVIDIA has been transforming computer graphics, PC gaming, and accelerated computing for more than 25 years. It's a unique legacy of innovation that's fueled by great technology--and amazing people. Today, we're tapping into the unlimited potential of AI to define the next era of computing. An era in which our GPU acts as the brains of computers, robots, and self-driving cars that can understand the world. Doing what's never been done before takes vision, innovation, and the world's best talent.

Industry

Computer and electronic product manufacturing

Company size

10,000+ Employees

Headquarters location

Santa Clara, CA, US

Year founded

1993