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Remote Cfa Data Science Jobs in California (NOW HIRING)

ABC Legal Services

Data Scientist

Los Angeles, CA · On-site +1

$110K - $130K/yr

Proven ability to translate complex data science findings into clear, actionable insights for non-technical stakeholders * Strong self-direction and communication skills suited for a remote work ...

MhyMatch

Data Scientist

San Francisco, CA · On-site +1

Remote/Hybrid Brief Overview of the Our Client is seeking a highly skilled Data Scientist to leverage large volumes of data using modern tools and technologies to uncover insights, build predictive ...

Fullpower Technologies

Data Scientist

Santa Cruz, CA · Remote

$130K - $170K/yr

Fullpower-AI delivers a complete B2B IoT platform for AI-powered algorithms, remote contactless ... The ideal candidate will have a strong background in machine learning and data science and a proven ...

Mercor

Chief Data Scientist

San Francisco, CA · Remote

$70 - $100/hr

Data Science Experts Type: Contract Compensation: $70-$100/hour Location: Remote Commitment: 40 hours/week Role Responsibilities * Guide research and engineering teams on data science methodology ...

Swish Analytics

Tennis Data Scientist

San Francisco, CA · On-site +1

$135K - $190K/yr

Data Science is at the core of our business, so this team has true ownership and impact over developing core components of Swish's data products. This position is remote from the USA. Duties:

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Remote Cfa Data Science information

What are the key skills and qualifications needed to thrive as a Remote CFA Data Science professional, and why are they important?

To excel as a Remote CFA Data Science professional, you typically need a solid background in quantitative analysis, financial modeling, and data science, with a CFA designation and a degree in finance, statistics, or a related field. Familiarity with tools such as Python, R, SQL, and financial analytics platforms, along with proficiency in data visualization software, is essential. Strong problem-solving abilities, communication skills, and self-motivation are vital soft skills for effective collaboration and independent remote work. These competencies ensure accurate financial insights, efficient data-driven decision-making, and effective teamwork across distributed environments.

How do Remote CFA Data Science professionals typically collaborate with cross-functional teams despite working remotely?

Remote CFA Data Science professionals often collaborate with investment analysts, portfolio managers, and IT teams through digital communication tools like Slack, Zoom, and project management platforms. Regular virtual meetings, shared dashboards, and collaborative coding environments help streamline workflow and ensure everyone stays aligned on project goals. While time zone differences or limited face-to-face interaction can be challenging, clear documentation and proactive communication are key strategies to maintain effective teamwork.

What are remote CFA Data Science jobs?

Remote CFA Data Science jobs are positions that combine expertise in data science with knowledge of finance, specifically leveraging the Chartered Financial Analyst (CFA) credential. Professionals in these roles analyze financial data, build predictive models, and provide insights to guide investment decisions—all while working remotely. These jobs typically require strong quantitative skills, proficiency in programming languages like Python or R, and a deep understanding of financial markets. The remote aspect allows for flexible work arrangements, enabling professionals to contribute from anywhere in the world.

What is the difference between Remote Cfa Data Science vs Remote Cfa Investment Analyst?

AspectRemote Cfa Data ScienceRemote Cfa Investment Analyst
CredentialsCFA Charter, Data Science skillsCFA Charter, Investment analysis skills
Work EnvironmentData analysis, modeling, programmingFinancial research, portfolio management
Industry UsageFinance, tech, data-driven firmsAsset management, investment firms

Remote Cfa Data Science focuses on applying data analysis and modeling techniques within finance, often requiring programming skills alongside CFA credentials. In contrast, Remote Cfa Investment Analysts primarily conduct financial research and portfolio analysis. Both roles are CFA-certified and operate in finance but differ in daily tasks and skill sets.

What are popular job titles related to Remote Cfa Data Science jobs in California? For Remote Cfa Data Science jobs in California, the most frequently searched job titles are:
What job categories do people searching Remote Cfa Data Science jobs in California look for? The top searched job categories for Remote Cfa Data Science jobs in California are:
What cities in California are hiring for Remote Cfa Data Science jobs? Cities in California with the most Remote Cfa Data Science job openings:
Remote Cfa Data Science jobs near you
Data Science

Data Science

Adidev Technologies Inc

San Francisco, CA • Remote

Full-time

Posted 23 days ago

Job description

Adidev Technologies Inc 

www.adidevtechnologies.com

URGENT HIRE - HIRING PROCESS - 24-48 HOURS!

Adidev Technologies is seeking 1-2 yrs of relevant experience in Data Science. A project can last anywhere from 6 months to 18 months. Salary varies depending on experience, and we are in search of candidates looking to start as soon as possible. Excellent written and oral communication are required as is the ability to work well in a team environment.

If you are looking for a new challenge and are ready to make an impact on a growing team, then this will be a perfect fit. As a Data Scientist/Data Science Specialist for Adidev Technologies Inc., you will be enhancing and debugging large-scale applications for one of our well-known clients.

Adidev Technologies is a growing software consulting company that is constantly expanding. As we are working with renowned clients and ready to take on new ones, we are seeking brilliant software engineers. Not only do we offer a great team to work with, but we also offer you an opportunity to make an immediate impact and get rewarded accordingly

 

Job Description

  • Demonstrated experience using machine learning, deep learning, statistical methodology, and simulation/optimization modeling in geospatial, network topography, recommendation systems, environmental systems, and/or agronomic problems.
  • Strong foundation in Python programming in a cloud environment.
  • Strong quantitative abilities, distinctive problem-solving, and excellent analysis skills
  • Expertise in data wrangling using SQL,
  • Practical knowledge and experience with cloud-computing systems and platforms, including the routine deployment of pipelines through Kubernetes
  • Fluency in querying/extracting/aggregating data via SQL scripting.
  • Extract, load and transform data (ETL) from structured and unstructured sources
  • Apply Natural Language Processing and Computer Vision to solve business use cases,
  • Strong skills in scientific data analyses, modeling, visualization and communication of results.
  • Knowledge of Python libraries (NumPy, Pandas, SciKit-Learn, TensorFlow, PyTorch), Spacy, MongoDB, PostgreSQL, Flask, streamlet and a good knowledge of data pipelines construction
  • Ph.D., M.S. or B.S. in Computer Science, Computational Physics, Operations Research, Geospatial Sciences, Remote Sensing Science, Environmental Sciences, Computational Astronomy or related scientific discipline


Must  have 

  • Understanding of various machine learning algorithms (e.g. SVM, Random Forests, Gradient Boosting, Log-Log regression, XGBoost, Lasso, Ridge, Clustering techniques, Neural Networks and others)
  • Regression (e.g. ? Linear/Logistic/MNL/Mixed Effects/Regularization)
  • Classification (K-means, Hierarchical, Latent Class, DBScan, SVM)
  • Dimension Reduction techniques (Principal Component analysis, Singular Value Decomposition etc.)
  • Optimization (Linear programming, Stochastic Gradient Descent, Genetic Algorithm etc.)
  • Experience with neural network approaches to text classification CNN, RNN, LSTM,Keras
  • Machine Learning algorithms? Neural Networks, Naïve Bayes, Bagging & Boosting, Random Forest
  • Distributed computing tools and cloud technology (AWS)

QUALIFICATIONS

  • Degree in Data Science, Computer Science, Engineering, Math, or Statistics preferred

  • At least 2 yrs of relevant experience in Data Science


SKILLS

  • SQL, statistical modeling, Feature engineering, Data visualization, Deploying models to production, Python programming, AWS, Domains(Healthcare/ Manufacturing/ Marketing/ Financial/ Telecommunication), powerbi/tableau, data warehouse

Benefits

  • Competitive Salary

  • Paid Relocation

  • Remote Support

  • Guaranteed Regular Salary Reviews

  • Job Type: W2 or Contract 1099 (full-time - 40 hours)

Employment Type: FULL_TIME

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