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Entry Level Behavioral Data Science Jobs in California

Menlo Ventures

Senior Data Scientist

San Francisco, CA · On-site

$123K - $218K/yr

Shape the direction of key data science areas for 2020 - usage forecasting, product analytics, user behavior, and funnel analysis. * Work closely with Product Management, Sales, Customer Success and ...

Parafin

Data Scientist

San Francisco, CA · On-site

$235K - $330K/yr

Building and shipping ML models (XGBoost and friends) that forecast merchant repayment behavior ... Your Background and Skills Bachelor's Degree (or higher) in Computer Science, Statistics ...

Parafin, Inc

Data Scientist

San Francisco, CA · On-site

The Data Science Team Our Impact Data is core to Parafin's mission to grow small businesses. Our ... Building and shipping ML models (XGBoost and friends) that forecast merchant repayment behavior ...

MrBeast

Data Scientist

San Francisco, CA · Hybrid

... data science workflow ever allowed. The Product You'll work as part of a small, fast-moving team on ... The work spans the full journey from raw user behavior to actionable insight. That means: Product ...

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All JobsBehavioral Data Science JobsEntry Level Behavioral Data Science JobsEntry Level Behavioral Data Science Jobs in California

Entry Level Behavioral Data Science information

What is the difference between Entry Level Behavioral Data Science vs Entry Level Data Analyst?

AspectEntry Level Behavioral Data ScienceEntry Level Data Analyst
Required CredentialsBachelor's in Psychology, Data Science, or related fields; basic knowledge of statistics and programmingBachelor's in Statistics, Mathematics, or related fields; proficiency in Excel, SQL, and data visualization tools
Work EnvironmentResearch settings, tech companies, or consulting firms focusing on human behavior analysisBusiness environments, marketing firms, or finance departments analyzing data trends
Employer & Industry UsageOrganizations studying consumer behavior, user experience, or social sciencesCompanies seeking to interpret data for decision-making, reporting, and operational insights

Entry Level Behavioral Data Science focuses on understanding human behavior through data, often requiring knowledge of psychology and statistics. Entry Level Data Analysts primarily interpret and visualize data to support business decisions. While both roles require analytical skills, behavioral data science emphasizes behavioral insights, whereas data analysts focus on data reporting and visualization.

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

The most popular types of Behavioral Data Science jobs in California are:

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For Entry Level Behavioral Data Science jobs in California, the most frequently searched job titles are:

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Cities in California with the most Entry Level Behavioral Data Science job openings:

Entry Level Behavioral Data Science jobs near you

Data Scientist - Fraud Detection

Mountain View, CA • On-site

DataVisor
Software Development • 1 - 10 employees
Learn more about DataVisorexternal

Full-time

Medical, PTO

Posted 15 days ago

Key responsibilities

  • Develop and deploy machine learning models for fraud detection and risk assessment.

  • Perform exploratory data analysis (EDA) to identify trends, anomalies, and patterns in transactional data.

  • Collaborate with engineering and business teams to integrate ML models into production systems.

Job description

About DataVisor:
DataVisor is the world’s leading AI-powered Fraud and Risk Platform that delivers the best overall detection coverage in the industry. With an open SaaS platform that supports easy consolidation and enrichment of any data, DataVisor's fraud and anti-money laundering (AML) solutions scale infinitely and enable organizations to act on fast-evolving fraud and money laundering activities in real time. Its patented unsupervised machine learning technology, advanced device intelligence, powerful decision engine, and investigation tools work together to provide significant performance lift from day one. DataVisor's platform is architected to support multiple use cases across different business units flexibly, dramatically lowering total cost of ownership, compared to legacy point solutions. DataVisor is recognized as an industry leader and has been adopted by many Fortune 500 companies across the globe.

Our award-winning software platform is powered by a team of world-class experts in big data, machine learning, security, and scalable infrastructure. Our culture is open, positive, collaborative, and results-driven. Come join us!

Position Overview:

We are looking for a motivated Entry-Level Data Scientist to join our Fraud Detection team. In this role, you will leverage your machine learning and data analysis skills to identify fraudulent activities, build predictive models, and uncover hidden patterns in large datasets. You will work closely with cross-functional teams to develop scalable solutions that enhance our fraud detection capabilities. This is a great opportunity to grow your skills in a fast-paced, data-driven environment while making a real impact in the fight against fraud.

Key Responsibilities:

  • Develop and deploy machine learning models for fraud detection and risk assessment.
  • Perform exploratory data analysis (EDA) to identify trends, anomalies, and patterns in transactional data.
  • Clean, preprocess, and analyze large datasets using Python and popular data science libraries (pandas, NumPy, scikit-learn, etc.).
  • Collaborate with engineering and business teams to integrate ML models into production systems.
  • Continuously monitor model performance and refine algorithms to improve accuracy.
  • Stay updated with the latest advancements in fraud detection techniques and ML/AI technologies.

Requirements

  • Master’s degree in Computer Science, Data Science, Statistics, or a related quantitative field. Ph.D. degree is a plus. 
  • Strong programming skills in Python and familiarity with data science libraries (NumPy, Pandas, scikit-learn, TensorFlow/PyTorch is a plus).
  • Solid understanding of machine learning algorithms (supervised/unsupervised learning, anomaly detection, classification, etc.).
  • Experience with SQL and data manipulation/analysis in large datasets.
  • Strong problem-solving skills and patience for deep-dive data exploration.
  • Prior internship or project experience in fraud modeling, risk analysis, or related fields is a plus.
  • Excellent communication skills and ability to work in a collaborative environment.
Nice to have
  • Familiarity with big data tools (Spark, Hadoop, Dask).
  • Knowledge of graph-based fraud detection techniques.
  • Experience with cloud platforms (AWS, GCP, Azure).

Benefits

PTO, Stock Option, Health Benefits