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We work with companies funded by the best investors including Sequoia Capital, Lightspeed Ventures, Tiger Global Management, A16Z, Accel, DFJ, and more. Proficiency in Python and basic ML libraries like Pytorch or TensorFlow.
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TaxBit investors include Haun Ventures, IVP, Insight Partners, Paradigm, Tiger Global, PayPal Ventures, Winklevoss Capital, Coinbase Ventures, and other leading crypto investors. You will be involved in understanding digital asset trading and transaction data (across equities, commodities, fiat, cryptocurrency, etc.
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Strong experience in building ETL data pipelines and analysis using Python, SQL, and PySpark. Knowledge of programming languages in data engineering such as Python or PySpark.
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We’ve built one of the most experienced leadership teams in Fintech and were recently valued at over $25.5B. We’ve raised over $1.7B in funding from leading investors including Sequoia Capital Global Equities, SoftBank Vision Fund 2, General Atlantic, Tiger Global, Dragoneer, DST, Coatue, Iconiq, Menlo Ventures and others.
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Design, develop and maintain data intensive web applications and using a variety of technologies, including but not limited to Scala/SQL/PySpark, Python, HTML, CSS, JavaScript, React, Angular, Node.js, Ruby, and Java.
$123,700 - $240,500 a yearFull-timeExpandApply NowActive JobUpdated Yesterday - UpvoteDownvoteShare Job
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Proficiency in Python, R, and SQL as well as data visualization and dashboarding tools (e.g. Tableau, Looker, QlikView) and Big Data technologies such as Apache Spark and cloud computing platforms.
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You might have picked up proficiency in a few different languages (Java, Scala, Python or the others) and programming styles (functional, object-oriented, script/procedural or big data.
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With $180 million in funding from YC Continuity (Y Combinator), CRV and Tiger Global, we're valued at $1.5 billion in just 3 years. Work in a variety of languages and technologies, including Python, Typescript, React, GraphQL and SQL.
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RequirementsBachelors Degree in Data Science, Computer Science, or related field10+ years of Data Science and Machine Learning experience requiredProficiency in Python or R. Ability to write complex SQL queriesProficiency with Machine Learning concepts and modeling techniques to solve problems such as clustering, classification, regression, anomaly detection, simulation and optimization problems on large scale data sets.
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Expertise with SQL and Python and visualization tools (e.g. Looker, Tableau, Power BI) You should be an expert in working with complex data, using visualization tools such as Looker, and have a keen understanding of how to apply data to address ambiguous problems.
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You have an expert level understanding of Python, SQL and cloud technologies like AWS. You have a proficient understanding of advanced machine learning techniques and we'll give you bonus points for experience in Computer Vision, NLP and or Deep Learning.
$156,000 - $218,500 a yearFull-timeExpandUpdated 3 days ago - UpvoteDownvoteShare Job
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Work will involve building semantic search engines, LLM fine-tuning, Vector DB applications, and cutting-edge data science work. Develop generative solutions, optimize models, familiarity with frameworks like Langchain, Llama index, LLM open-source models including LLAMA and related frameworks, and proficiency in Python.
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This role will manage a fast growing team and data stack - Python, Bigquery, and Postgresql - and set the foundation for how J2 solves data science problems. We are a team of industry insiders and technologists, backed by Primary Ventures, Tiger Global, BoxGroup and Greycroft.
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Experience working platform like Apache Spark, Apache Flink, Glue, Kafka Experience with SQL/ NoSQL platforms such as Redshift, DynamoDB, Tiger graph, Snowflake Experience with Orchestration tool like Alteryx, Terraform, Salt, CloudFormation Working Experience with Data platforms like Databricks Good knowledge of Cloud AWS, Azure, OCI (+ knowledge of CSP-specific services) Experience with incident management tools.
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Understand business problems, making sense of the data landscape & footprint, performing a combination of Gen AI, Advanced NLP, Exploratory analysis. NLP libraries such as NLTK or SpaCy for processing text data.
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