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Assistant Blockchain Data Scientist Jobs (NOW HIRING)

MLabs

Staff Product Data Scientist

Manhattan, NY · On-site

$110 - $140/hr

Data Scientist Location: New York On-site | Full-time Compensation: Competitive Our client is a ... Direct experience with cryptocurrency, blockchain data, or fintech/consumer tech products.

De Circle

Data Scientist - DyDx

New York, NY · On-site +1

Build pipelines for blockchain transaction, order book, and market participant data to support ... Bachelor's or Master's degree in quantitative fields (Computer Science, Statistics, Economics) or a ...

Find Data Science

Data Scientist

San Francisco, CA

Document methodologies and processes to ensure that data science projects are scalable and sustainable. * Assist in the data governance process to ensure data accuracy and integrity. Requirements

mLabs

Data Scientist

Manhattan, NY · On-site

$250 - $350/hr

... blockchain, cryptocurrency, and artificial intelligence is seeking a highly autonomous and proactive Data Scientist to join its core engineering group. Having backed over 300 high-growth startups now ...

Jobzhr

Data Scientist

Manhattan, NY · On-site

$250 - $350/hr

... blockchain, cryptocurrency, and artificial intelligence is seeking a highly autonomous and proactive Data Scientist to join its core engineering group. Having backed over 300 high-growth startups now ...

MLabs

Data Scientist

New York, NY · On-site

$250K - $350K/yr

... blockchain, cryptocurrency, and artificial intelligence is seeking a highly autonomous and proactive Data Scientist to join its core engineering group. Having backed over 300 high-growth startups now ...

ITrade STEM

Blockchain Security Analyst

Miami, FL · On-site

Requirements : * Bachelor's degree in Computer Science, Cybersecurity, Forensic Analysis, or ... Proficiency in Python, JavaScript, or similar programming languages for blockchain data analysis.

ITrade STEM

Blockchain Security Analyst

Miami, FL · Remote

Bachelor 's degree in Computer Science, Cybersecurity, Forensic Analysis, or related field ... Experience with graph analysis tools and data visualization software.Understanding of MEV ...

ITrade STEM

Blockchain Security Analyst

Miami, FL · On-site

Requirements : * Bachelor's degree in Computer Science, Cybersecurity, Forensic Analysis, or ... Proficiency in Python, JavaScript, or similar programming languages for blockchain data analysis.

Brewer Science

Data Scientist

Rolla, MO · On-site

They are currently seeking a purpose-driven candidate to fill an open position as a Data Scientist, responsible for working cross functionally to assist in data collection plans, analyze and model ...

Brewer Science, Inc.

Data Scientist

Rolla, MO · On-site

A Data Scientist is responsible for working cross functionally in the organization with different groups to assist in data collection plans, to analyze, process, and model data, and to teach data ...

Brewer Science Inc.

Data Scientist

Rolla, MO · On-site

A Data Scientist is responsible for working cross functionally in the organization with different groups to assist in data collection plans, to analyze, process, and model data, and to teach data ...

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Assistant Blockchain Data Scientist information

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How much do assistant blockchain data scientist jobs pay per year?

As of Aug 15, 2026, the average yearly pay for assistant blockchain data scientist in the United States is $165,018.00, according to ZipRecruiter salary data. Most workers in this role earn between $133,500.00 and $170,000.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as an assistant blockchain data scientist?

To thrive as an Assistant Blockchain Data Scientist, you need a solid understanding of data analysis, blockchain technology, and programming languages such as Python or R, often supported by a degree in computer science or a related field. Familiarity with blockchain platforms (e.g., Ethereum), data visualization tools, SQL, and relevant certifications (such as blockchain or data analytics certificates) is highly valued. Analytical thinking, problem-solving abilities, and effective communication set exceptional candidates apart in this role. These skills are crucial for analyzing complex blockchain data, deriving actionable insights, and collaborating with technical and non-technical stakeholders.

What are some common challenges an assistant blockchain data scientist may face when analyzing on-chain data?

Assistant Blockchain Data Scientists often encounter challenges such as dealing with the sheer volume and complexity of blockchain data, as well as ensuring data quality and consistency across decentralized sources. Interpreting and cleaning raw transaction data, which may not always be structured or labeled, requires strong analytical and problem-solving skills. Collaboration with blockchain developers and other data scientists is key to overcoming these hurdles and developing meaningful insights that support business goals.

What is an assistant blockchain data scientist?

Assistant Blockchain Data Scientists are entry-level professionals who support senior data scientists in analyzing and interpreting data generated from blockchain networks. Their responsibilities often include gathering blockchain data, cleaning and preprocessing it, and assisting in developing models to extract insights about blockchain transactions, network activity, and trends. They also help create reports, visualize data, and may work with smart contract data to identify patterns or anomalies. This role requires knowledge of data science tools, programming languages like Python, and a fundamental understanding of blockchain technology.
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Assistant Blockchain Data Scientist jobs near you
Infographic showing various Assistant Blockchain Data Scientist job openings in the United States as of August 2026, with employment types broken down into 1% As Needed, 84% Full Time, 11% Part Time, and 4% Contract. Highlights an 86% Physical, 4% Hybrid, and 10% Remote job distribution, with an average salary of $165,018 per year, or $79.3 per hour.

Data Scientist - Credit & Risk

Divine Research Inc

San Francisco, CA • On-site

Full-time

Re-posted 7 days ago

Job description

Traditional credit was built for people who already have money. Requirements for credit history, collateral, and costly underwriting create insurmountable barriers for those who need capital most. Over 1.4 billion people lack access to credit. A vendor in Lagos earns cash daily but can't prove a steady income. A Colombian nurse with years of perfect informal repayments remains invisible to banks. Most lending systems spend a lot to guess who will repay, and yet so many who are creditworthy still can't get a loan.
We built an alternative called Credit. Since December 2024, it has issued over one million unsecured loans using stablecoins. People from around the world have used these loans to pay for things like groceries, medicine, and transportation. Backed by $6.6 million from Paradigm and Nascent, we're scaling a system that has already reached more than 900,000 unique borrowers. Help us take it to the next level.
About the role
We're looking for a data scientist to drive credit risk intelligence across Credit, our leading unsecured lending system. You'll own portfolio monitoring and reporting, research emerging risk trends, and transform borrower behavioral data into actionable guidance that shapes our credit strategy and roadmap.
While our engineering & research teams owns the underlying models, you'll be the person who makes sense of what they're telling us, tracking portfolio health, identifying issues early, and turning insights into clear recommendations for risk strategy and underwriting policy. Over time, this role may expand to drive broader product analytics across our suite of products.
This role is based in San Francisco, California. We work in a hybrid model, with the team in office 3 days per week.
Stack
  • Python
  • SQL
  • Grafana/Prometheus/Metabase
  • Blockchain data and indexing tools (Dune, Shovel)
Key responsibilities
  • Monitor credit risk models, including underwriting, loss forecasting, and fraud detection, and iterate based on observed portfolio performance
  • Design, build, and maintain scalable data pipelines, monitoring infrastructure, and dashboards to track portfolio health, user behavior, and key risk indicators
  • Partner with product, research, and engineering teams to define north star metrics and translate them into measurable, actionable credit and growth strategies
  • Design and analyze A/B tests, quasi-experiments, and causal inference studies to evaluate the impact of product and policy changes
  • Produce portfolio monitoring and investigative analyses, making recommendations based on findings
  • Translate complex quantitative findings into clear, compelling narratives for product, leadership, and cross-functional stakeholders
Requirements
  • 4+ years of experience in decision science, credit risk analytics, or a closely related quantitative role within fintech or consumer lending
  • Deep proficiency in Python and SQL; comfortable owning analyses end-to-end from raw data to recommendation
  • Strong understanding of credit risk modeling concepts, including PD/LGD modeling, scorecard development, reject inference, vintage analysis, and risk segmentation
  • Demonstrated experience monitoring credit risk metrics and portfolio performance, including loss forecasting and underwriting model improvement
  • Proven ability to influence and collaborate with cross-functional teams and senior stakeholders, with a track record of translating analytical findings into accessible, actionable insights
  • Experience designing and evaluating experiments (A/B tests, holdout groups, or causal inference frameworks) in a consumer product context
  • Comfortable with ambiguity and biased toward action; thrives with minimal oversight and brings strong problem-solving skills and sharp attention to detail
Nice to have
  • Experience building or maintaining large-scale data pipelines supporting B2C financial products
  • Familiarity with credit bureau data, cash flow underwriting, or alternative data sources in credit model development
  • Experience working in emerging markets, ideally on financial products serving everyday consumer needs (microfinance, BNPL, digital lending)
  • Strong understanding of DeFi protocol mechanics (lending, yield vaults, ERC4626) and experience with onchain data tooling (Dune, Shovel, Ponder, Goldsky or similar)
  • Exposure to regulatory frameworks relevant to consumer credit (FCRA, ECOA, or equivalent)

Divine Research is an equal opportunity employer.

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