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Data Science Jobs in Oxnard, CA (NOW HIRING)

Director, Strategic Data Lead

Thousand Oaks, CA ยท On-site

$199.06 - $269.32/hr

You will work closely with Brand teams, BAI PODs, Access, Field Effectiveness, Data Science, Data Management, Legal, Privacy, Compliance, Procurement, and external data partners to ensure Amgen is ...

New

Data Architect Senior

Malibu, CA ยท On-site

$145K - $180K/yr

Bachelor's degree in Computer Science, Information Systems, Data Science, Engineering, or related field. Equivalent experience may be considered. * 5+ years of experience in data architecture ...

Data Warehouse Engineer

Calabasas, CA ยท On-site +1

$110K - $125K/yr

Share knowledge with the Director and future data science hires via code examples, patterns, and mentoring. * Deliver specialized data engineering enhancements as directed by the Data Team Director.

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Data Science information

See Oxnard, CA salary details

$39.7K

$130K

$208.1K

How much do data science jobs pay per year?

As of Aug 7, 2026, the average yearly pay for data science in Oxnard, CA is $129,977.00, according to ZipRecruiter salary data. Most workers in this role earn between $104,300.00 and $144,000.00 per year, depending on experience, location, and employer.

Is a data scientist in high demand?

Yes, data scientists are in high demand across many industries due to the increasing reliance on data-driven decision making. The role requires skills in programming, statistics, and machine learning, and job growth is expected to continue as organizations expand their data capabilities.

What are the key skills and qualifications needed to thrive as a data scientist, and why are they important?

To thrive as a Data Scientist, you need a strong background in statistics, programming (often Python or R), and data analysis, usually supported by a degree in a quantitative field. Familiarity with machine learning libraries (like scikit-learn or TensorFlow), big data tools (such as Hadoop or Spark), and data visualization platforms is typically required. Critical thinking, problem-solving, and effective communication are vital soft skills for translating complex data insights into actionable business strategies. These skills and qualities are essential for extracting value from data, driving informed decisions, and effectively collaborating with multidisciplinary teams.

What are some common challenges faced by data scientists when working with real-world datasets?

Data scientists often encounter challenges such as missing or inconsistent data, unstructured formats, and noisy information in real-world datasets. Cleaning and preprocessing data to ensure its quality can be time-consuming but is critical for building accurate models. Additionally, data scientists may work closely with domain experts and other team members to better understand the data's context and ensure their analyses align with business objectives. Overcoming these challenges requires strong problem-solving skills and effective collaboration within cross-functional teams.

What is data science?

Data science is an interdisciplinary field that uses scientific methods, algorithms, and systems to extract insights and knowledge from structured and unstructured data. It combines skills from statistics, computer science, and domain expertise to analyze and interpret complex data sets. Data scientists work with large amounts of data to identify patterns, make predictions, and help organizations make data-driven decisions.

What is the difference between Data Science vs Data Analyst?

AspectData ScienceData Analyst
Required skillsStatistics, programming (Python, R), machine learningData visualization, SQL, basic statistics
Work environmentDeveloping models, predictive analytics, researchReporting, data cleaning, descriptive analysis
Tools usedPython, R, Jupyter, TensorFlowExcel, SQL, Tableau, Power BI
Industry usageTech, finance, healthcare, e-commerceRetail, marketing, finance, healthcare

Data Science and Data Analyst roles often overlap but differ mainly in scope. Data Scientists focus on building predictive models and advanced analytics, requiring programming and machine learning skills. Data Analysts primarily handle data cleaning, reporting, and visualization. Both roles are essential in data-driven industries, but Data Science is more technical and research-oriented, while Data Analysis emphasizes interpreting data for business insights.

What does a data scientist do?

As a Data Scientist, you are qualified to work in such diverse fields as research and development, politics, advertising and marketing, technology, healthcare, government, and higher education as well as multiple others. In general, your duties and responsibilities will be to compile and analyze relevant statistics and turn those numbers into algorithms that reveal insights that can be used by other researchers in their areas of study. Data Science can reveal things like consumer buying habits or the likelihood of success for a course of action. Other duties might vary, depending on your unique field of specialty. Related areas in which a Data Scientist might wish to focus include work as a Data Analyst, Machine Learning Engineer, and Project Manager.
What are the most commonly searched types of Data Science jobs in Oxnard, CA? The most popular types of Data Science jobs in Oxnard, CA are:
What are popular job titles related to Data Science jobs in Oxnard, CA? For Data Science jobs in Oxnard, CA, the most frequently searched job titles are:
What job categories do people searching Data Science jobs in Oxnard, CA look for? The top searched job categories for Data Science jobs in Oxnard, CA are:
What cities near Oxnard, CA are hiring for Data Science jobs? Cities near Oxnard, CA with the most Data Science job openings:
Infographic showing various Data Science job openings in Oxnard, CA as of August 2026, with employment types broken down into 100% Full Time. Highlights an 80% In-person, 4% Hybrid, and 16% Remote job distribution, with an average salary of $129,977 per year, or $62.5 per hour.

Director, Strategic Data Lead

SwiftCruit

Thousand Oaks, CA โ€ข On-site

$199.06 - $269.32/hr

Other

Posted 2 days ago

New


Job description

Career Category: Sales & Marketing Operations

Job Description

Join Amgenโ€™s Mission of Serving Patients. At Amgen, if you feel like youโ€™re part of something bigger, itโ€™s because you are. Our shared missionโ€”to serve patients living with serious illnessesโ€”drives all that we do. Since 1980, weโ€™ve helped pioneer the world of biotech in our fight against the worldโ€™s toughest diseases. With our focus on four therapeutic areasโ€”Oncology, Inflammation, General Medicine, and Rare Diseaseโ€” we reach millions of patients each year. Amgen is advancing a broad and deep pipeline of medicines to treat cancer, heart disease, inflammatory conditions, rare diseases, and obesity and obesityโ€‘related conditions. As a member of the Amgen team, youโ€™ll help make a lasting impact on the lives of patients as we research, manufacture, and deliver innovative medicines to help people live longer, fuller, happier lives.

Director, Strategic Data Lead

In this vital role, lead strategic data partnership across priority commercial business areas, translating brand priorities, customer needs, business questions, and analytic use cases into clear, actionable data strategies and sourcing recommendations. You will work closely with Brand teams, BAI PODs, Access, Field Effectiveness, Data Science, Data Management, Legal, Privacy, Compliance, Procurement, and external data partners to ensure Amgen is using the right data, using existing data more effectively, and identifying new data opportunities that can improve decision-making and business impact.

What you will do
  • Lead strategic data partnership across priority commercial business areas, bringing a Commercial Data Strategy perspective to brand planning, business decisionโ€‘making, and dataโ€‘enabled opportunities.
  • Translate brand plans, strategic imperatives, launch needs, access priorities, field priorities, and customer opportunities into practical data strategies and sourcing recommendations.
  • Partner across Brand teams, BAI PODs, and crossโ€‘functional stakeholders to understand analytic frameworks, measurement needs, and business decisions that data must support.
  • Frame data use cases from the customer and business angle, including the customer segment, behavior to influence, barrier to address, decision to be made, data needed, and expected business value.
  • Develop a strong understanding of Amgenโ€™s commercial data ecosystem, including current data assets, underused sources, known gaps, vendor landscape, customer journey needs, and external market signals.
  • Identify and act on opportunities to better use data Amgen already purchases, reduce duplication, rationalize underused assets, and redirect spend toward higherโ€‘value data needs.
  • Assess whether business needs can be met through existing data, enhanced use of current assets, or new external data sources.
  • Develop and present data opportunity briefs and recommendations that clearly articulate the business question, customer use case, analytic need, data requirements, potential vendors, feasibility considerations, risks, and investment rationale.
  • Establish and own the prioritization framework for data opportunities across competing business needs, balancing value, urgency, feasibility, strategic relevance, and investment tradeโ€‘offs.
  • Connect the right execution teams across Data Management, Data Science, DTI, Legal, Privacy, Compliance, Procurement, Finance, BAI PODs, and vendors to bring approved data strategies to life.
  • Lead business input into renewal, sourcing, investment, and vendor negotiations by defining data usage, future need, duplication risk, strategic relevance, data rights, deliverables, and value tradeโ€‘offs.
  • Maintain visibility to upcoming brand priorities, launch milestones, market events, competitive dynamics, and data needs.
  • Communicate data strategy, recommendations, tradeโ€‘offs, and decision points clearly to senior stakeholders across the business teams.
What we expect of you

The dynamic professional we seek is someone with these qualifications.

Basic Qualifications
  • Doctorate degree and 4years of experience in data acquisition, data governance, commercial data operations, vendor management, commercial analytics, data strategy, or a related field ORMasterโ€™s degree and 8years of experience in the same areas ORBachelorโ€™s degree and 10years of experience in the same areas.
  • In addition to meeting at least one of the above requirements, you must have at least 4years of experience directly managing people and/or leading teams, projects, programs, or directing the allocation of resources. Your managerial experience may run concurrently with the required technical experience.
Preferred Qualifications / Competencies
  • Strong understanding of commercial analytic frameworks and how data supports segmentation, targeting, measurement, launch readiness, market access, customer journey analysis, field execution, brand performance, and KPI development.
  • Ability to think customerโ€‘back and define data use cases based on customer needs, desired behaviors, barriers, leverage points, decision needs, and expected business value.
  • Strong business acumen with the ability to connect brand strategy, customer insights, market dynamics, analytic needs, and external data opportunities.
  • Experience partnering with Analytics, Market Research, Data Science, or Commercial teams to support insights, measurement, research, and business decisionโ€‘making.
  • Understanding of pharmaceutical and healthcare data ecosystems, including sales, claims, patient, provider, payer, plan, specialty pharmacy, lab, EHR/EMR, digital, media, access, and realโ€‘world data.
  • Ability to identify data reuse opportunities, duplication risks, underused assets, and data investment tradeโ€‘offs across vendors and business needs.
  • Experience shaping data opportunity briefs, business cases, useโ€‘case summaries, or strategic recommendations for senior leadership decisionโ€‘making.
  • Ability to influence decisions and drive alignment without direct authority across senior stakeholders and crossโ€‘functional teams.
  • Strong negotiation, diplomacy, and stakeholder management skills, with the ability to align internal partners and vendors around business needs, deliverables, value, and execution tradeโ€‘offs.
  • Experience partnering with Legal, Privacy, Compliance, Procurement, Finance, DTI, Data Management, and vendor partners to support responsible, scalable, and compliant use of data.
  • Strategic mindset with the ability to balance forwardโ€‘looking opportunity identification with practical execution through established owners and operating models.
  • Strong facilitation, prioritization, problemโ€‘solving, and stakeholder management skills.
  • Ability to operate as a business thought partner and internal consultant, not only as a data acquisition or vendor management resource.
Benefits

Amgen offers a comprehensive employee benefits package, a discretionary annual bonus program, stockโ€‘based longโ€‘term incentives, awardโ€‘winning timeโ€‘off plans, flexible work models where possible, and opportunities for career development.

Salary Range

199,064.90USDโ€“269,323.10USD

Equal Employment Opportunity

Amgen is an Equal Opportunity employer and will consider all qualified applicants for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, protected veteran status, disability status, or any other basis protected by applicable law. 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.

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