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2-4+ years professional experience as a Data Scientist. Experience communicating data driven insights. Robinhood faces unique data challenges with a focus on integrating multifaceted data streams such as rapidly changing market data, user data based on app activity, and brokerage operations data to understand user behavior and the risks to our business.
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Experience using modern compute, data infrastructure and visualization tools, and services such as Kafka, Airflow, AWS S3, AWS EC2, DBT, Kubernetes, Terraform, Data Lakes, Data Warehouses, and Looker.
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Proficiency with Python and experience with DBT and Airflow is a plus. We are looking for a Lead Data Scientist to connect and organize our data across the company to drive visibility into performance and strategy across our sales, marketing, product, operations, finance, and engineering efforts.
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2+ years of experience in Data Science or a related field, with a focus on building NLP/LLMs or Deep Learning models. Optional: Experience with big data platforms such as Hadoop or Spark.
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A background in immunology and experience working with clinical trial data will be a plus and will help in the development of independent research projects. Experience in single cell data analyses and integrative multi-omics approaches is a strong plus.
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Experience with streaming / data processing technologies such as Beam, Spark, Kafka, Airflow, HBase, Presto. Experience in stream / data processing technologies like Kafka, Spark, Google BigQuery, Google Dataflow, Presto, HBase.
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Experience with multiple big data solutions such as DynamoDB, MongoDB, BigQuery, Databricks, SnowFlake, etc. Our data processing capabilities are powered by Spark, BigQuery and Databricks, handling petabytes of data.
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Experience with relational databases, data modeling principles, data pipeline tools and workflow engines, e.g. DBT, Apache Airflow, AWS GLUE, Spark. Substantial experience working with clinical study data, healthcare data, Real-World Evidence.
$180,000 - $210,000 a yearFull-timeExpandApply NowActive JobUpdated Today - UpvoteDownvoteShare Job
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Experience with data analysis and business case development, and managing programs from concept to implementation. - Experience in analysis of large volume of data to drive analysis and to make decisions.
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Proven experience with global Sales and Marketing organizations and experience with pharmaceutical data sources e.g., IQVIA/IMS, SHA and chart audits are required. Deep expertise in working on IQVIA and Symphony Claims, Komodo claims, Optum, Definitive health, Health Verity, EMR data, Lab Data and patient chart audits.
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Experience with data from phage or yeast display or NGS generally. Experience with technologies for measuring antibody diversity and selection, including sequencing data of immune repertoires.
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Experience using big data technologies (Snowflake, Airflow, Kubernetes, Docker, Helm, Spark, pySpark) Experience designing and building highly available, distributed systems of data extraction, ingestion, normalization and processing of large data sets in real time as well as batch, that will be used across engineering teams using orchestration frameworks like Airflow, KubeFlow or other pipeline tools.
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Data Visualization tools (like Tableau, Spotfire) and Python programming language experience a plus. Collaborates with Clinical Operations, Data Management, Clinical Development, Drug Safety, Statistical Programming, and Biostatistics to develop standard and custom data reports for quality data oversight / clinical data review.
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Experience and/or knowledge of the healthcare data domain in at least one of: electronic medical records (EHR/EMR), clinical imaging, clinical workflows; Electronic Data captures (EDC), and/or clinical research/trials.
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Expertise in data analysis and visualization, particularly in creating high-quality figures for scientific publications (some formal training and/or work experience in data science, data visualization, or scientific illustration preferred.
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