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Data Mining Jobs in California (NOW HIRING)

Responsibilities : • Developing predictive models in the area of marketing • Understanding business problems and translating it into data mining problems • Applying techniques such as ...

Responsibilities : • Developing predictive models in the area of marketing • Understanding business problems and translating it into data mining problems • Applying techniques such as ...

Data Scientist III

San Diego, CA · On-site

$125K - $207K/yr

Typical responsibilities include applying data mining, modeling, natural language processing, and machine learning methods to analyze large structured and unstructured datasets; visualizing ...

Typical responsibilities include applying data mining, modeling, natural language processing, and machine learning methods to analyze large structured and unstructured datasets; visualizing ...

Use data mining and machine learning techniques to develop robust models in areas such as segmentation and profiling, churn assessment, customer loyalty prediction, retention analysis, and product ...

Skill Agile, Civil, Database, Data Mining, Developer, Development, Java, Lifecycle, Linux, Management, MyS Location Cupertino, CA Total Experience 6 yrs. Max Salary Not Mentioned Employment Type ...

Responsibilities : • Apply data mining, modeling, NLP, and machine learning to large datasets • Visualize, interpret, and report data findings • Create dynamic and automated reporting products ...

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Data Mining information

See California salary details

$50.3K

$69.1K

$87.8K

How much do data mining jobs pay per year?

As of Aug 23, 2026, the average yearly pay for data mining in California is $69,083.00, according to ZipRecruiter salary data. Most workers in this role earn between $54,300.00 and $83,900.00 per year, depending on experience, location, and employer.

What is a data mining?

A Data Mining job involves extracting useful patterns, trends, and insights from large datasets using statistical, machine learning, and analytical techniques. Professionals in this field work with structured and unstructured data to help businesses make data-driven decisions. Common tasks include data preprocessing, feature selection, algorithm development, and result interpretation. They often use tools like Python, R, SQL, and data visualization software to analyze data effectively.

What are the key skills and qualifications needed to thrive in data mining, and why are they important?

To thrive in Data Mining, a strong background in statistics, mathematics, computer science, and data analysis is usually required, often supported by a related degree or equivalent experience. Familiarity with tools such as Python, R, SQL, and data mining platforms like Weka or RapidMiner, as well as certifications in data analytics, are highly beneficial. Strong problem-solving abilities, analytical thinking, and effective communication skills help professionals interpret complex data and share actionable insights with stakeholders. These competencies are crucial for extracting valuable information from large datasets and driving data-informed decision-making within organizations.

What are some common challenges faced by professionals in data mining roles?

Data Mining professionals often encounter challenges such as handling large and complex datasets, ensuring data quality, and selecting the most appropriate algorithms for specific business problems. Managing diverse data sources and cleaning data to prepare it for analysis can be time-consuming and requires careful attention to detail. Collaboration with business analysts, IT staff, and subject matter experts is frequent, as understanding the business context is essential for meaningful results. Overcoming these challenges is key to delivering accurate insights and supporting strategic decisions within an organization.

How much do data miners make?

Data miners typically earn between $50,000 and $90,000 annually, depending on experience, location, and industry. Entry-level positions may start lower, while experienced professionals with advanced skills in data analysis and tools like SQL or Python can earn higher salaries.

Is data mining a good career?

Data mining is a viable career that involves analyzing large datasets to extract useful information, often requiring skills in statistics, programming, and tools like SQL and Python. It is in demand across industries such as finance, healthcare, and marketing, with opportunities for advancement and specialization.

What are the most commonly searched types of Data Mining jobs in California?

The most popular types of Data Mining jobs in California are:

What cities in California are hiring for Data Mining jobs?

Cities in California with the most Data Mining job openings:

Infographic showing various Data Mining job openings in California as of August 2026, with employment types broken down into 60% Full Time, 20% Part Time, and 20% Contract. Highlights an 80% In-person, and 20% Remote job distribution, with an average salary of $69,083 per year, or $33.2 per hour.

Software Engineer (SE / Sr SE), Applied ML & Data Mining

PlusAI

Santa Clara, CA • On-site

$130K - $220K/yr

Full-time

Posted 23 days ago


Job description

Finding the right data is central to improving autonomous-driving models. Among petabytes of fleet data, you will develop methods that identify and rank the most valuable moments for training and evaluation, then turn those methods into reliable tools that autonomy and ML engineers use to search, review, and curate datasets. You will work at the intersection of applied machine learning, information retrieval, large-scale data processing, and product engineering. We welcome candidates with ML or data-mining foundations who are excited to grow across scalable systems and the product stack.

We are open to candidates at either the Software Engineer or Senior Software Engineer level. Level will be determined by experience, technical depth, scope of ownership, and demonstrated impact. You do not need experience with every technology in our stack; we value strong fundamentals, ownership, and the ability to learn.

Responsibilities:
  • Develop and evaluate mining, retrieval, and ranking methods using signals such as model confidence, disagreement, embeddings, anomalies, temporal behavior, and learned representations

  • Build and evolve semantic image/video/scenario search, including text-to-image/video and image-to-image or video-to-video retrieval, vector search, metadata and temporal or spatial filters, task-specific ranking, and search quality, freshness, latency, and reliability

  • Build and operate distributed mining, inference, and indexing pipelines over fleet-scale imagery, video, time-series, and autonomy-system data, including GPU batch inference, embedding generation, reproducible candidate datasets, and reliable index refreshes

  • Design and ship mining products end to end: Python APIs and services, relational data models, asynchronous jobs, modern TypeScript/React search and review experiences, deployment, access control, testing, observability, and production reliability

  • Ensure that your work is performed in accordance with the company's Quality Management System (QMS) requirements and contribute to continuous improvement efforts

Required Skills:
  • BS, MS, or PhD in Computer Science, Machine Learning, or a related technical field, or equivalent practical experience

  • Hands-on experience developing and evaluating machine-learning, data-mining, computer-vision, or information-retrieval methods with a framework such as PyTorch or TensorFlow, including experimentation, error analysis, and principled metrics

  • Foundations for data-centric machine learning: an understanding of model uncertainty and evaluation, embeddings and similarity search, and how training-data composition shapes model behavior

  • Self-driven with a strong sense of ownership: a quick learner who is eager to take responsibility and drive projects forward end to end

Preferred Skills:
  • Production full-stack experience spanning backend services and REST APIs, relational data modeling and SQL, and modern JavaScript or TypeScript frontend development using React or a comparable framework

  • Experience improving models through data - training or fine-tuning, active learning and data flywheels, hard-example mining, uncertainty or disagreement signals, dataset curation - ideally in autonomous driving, robotics, or perception

  • Experience with embedding and multimodal models (CLIP-style models, VLMs), vector databases (Milvus, FAISS, pgvector), or GPU batch inference at scale

$130,000 - $220,000 a year
We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.
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