We’re a company that makes open source tools for data science and machine learning. You might know us from popular tools like [DVC](https://dvc.org) (Data Version Control) and [CML](https://cml.dev) (Continuous Machine Learning), or our [YouTube channel](https://www.youtube.com/channel/UC37rp97Go-xIX3aNFVHhXfQ). Our team is small, remote-first, and passionate about creating best practices for managing the complexities of data science.\n\nWe’re seeking a Developer Advocate to help us sustain and grow our active, worldwide community! \n\n## Job description\nAs an open source project, our community is everything. Our code, docs and outreach activities are fueled by community contributions, and user feedback is a huge driver for our product development. We invest heavily in building relationships with data scientists, engineers and developers around the world, from brand new contributors making their first pull request to longtime users working out a special use case. \n\nThe ideal candidate will:\n- Craft blog posts, release notes, and newsletters to share exciting developments on our projects, amazing contributions, and important technical Q&As. \n- Turn frequently-asked questions in the community into reusable resources, like tutorials and use-cases\n- Be a connector and maintain an engaged presence online. Respond to timely discussions and questions on social media and design shareable, creative campaigns for regular tweets and posts. \n- Enable community members of all skill levels to get involved. Welcome newcomers and encourage creative contributions. When folks make videos, blogs, or projects with our tools, help them boost the signal.\n- Lead community-building events like virtual meetups and present at relevant industry conferences\n- Be analytical and data-driven in creating useful content for the community. Define, report and analyze metrics to understand our community’s needs and interests.\n\n## Skills we’re looking for\n- Experience in either data science or open source software.\n- Experience blogging or publishing technical content online. Bonus points if it’s related to open source or data science. \n- Experience building and/or managing a technical community.\n- Understanding of Git, Git-flow and CI/CD. You don’t have to be a superuser, but we make tools built around Git and you’ll need to know how to use them.\n- Strong communication skills. Everyone on our team, from engineers to developer advocates, needs to be able to communicate over digital - platforms kindly and clearly.\n- Proficient written and spoken English is required. \n \n### Mega bonus skills\n- Knowledge of our tools and the MLOps space\n- A strong existing network in data science or open source\n\n### Perks\n- A fully remote job with a competitive salary and benefits package.\n- Our team culture is family-friendly. Our leadership includes several working parents, and our health insurance and unlimited PTO policies are designed with families in mind.\n- This role can grow with you. There are plenty of opportunities for leadership and autonomy in our small team! \n- Impact- you get to work on projects that are used every day by teams around the world! DVC and CML are used by researchers and data science teams across tech, finance, and government organizations. \n- You will get a [DeeVee](https://twitter.com/DVCorg/status/1314668966082572288/photo/1). \n\nPlease mention the words **BUILD CRUISE ARMOR** when applying to show you read the job post completely (#RMjE2LjczLjIxNi42MQ==). This is a feature to avoid spam applicants. Companies can search these words to find applicants that read this and see they're human.\n\n \n\n#Location\nWorldwide

We’re a company that makes open source tools for data science and machine learning. You might know us from popular tools like [DVC](https://dvc.org) (Data Version Control) and [CML](https://cml.dev) (Continuous Machine Learning), or our [YouTube channel](https://www.youtube.com/channel/UC37rp97Go-xIX3aNFVHhXfQ?). Our team is small, remote-first, and passionate about creating best practices for managing the complexities of data science.\n\nWe’re seeking a **Technical Community Manager** to help us sustain and grow our active, worldwide community! \n\n## Job description\nAs an open source project, our community is everything. Our code, docs and outreach activities are fueled by community contributions, and user feedback is a huge driver for our product development. We invest heavily in building relationships with data scientists, engineers and developers around the world, from brand new contributors making their first pull request to longtime users working out a special use case. \n\nThe ideal candidate will:\n\n* Enable community members of all skill levels to get involved. Welcome newcomers and encourage creative contributions. When folks make videos, blogs, or projects with our tools, help them boost the signal.\n* Be a connector and maintain an engaged presence online. Respond to timely discussions and questions on social media and design shareable, creative campaigns for regular tweets and posts. \n* Make blog posts, release notes, and newsletters to share exciting developments on our projects, amazing contributions, and important technical Q&As. \n* Turn frequently-asked questions in the community into reusable resources, like tutorials and use-cases\n* Lead community-building events like virtual meetups and our ambassador program. \n* Be analytical and data-driven in building and nurturing the community. Define, report and analyze metrics to understand our community’s needs and growth. \n\n\n## Skills we’re looking for\n* Experience in either **data science or open source software**.\n* Experience building and/or managing a ** technical community**.\n* Understanding of Git, Git-flow and CI/CD. You don’t have to be a superuser, but we make tools built around Git and you’ll need to know how to use them.\n* Experience blogging or publishing technical content online. Bonus points if it’s related to open source or data science. \n* Strong communication skills. Everyone on our team, from engineers to developer advocates, needs to be able to communicate over digital platforms kindly and clearly.\n* Proficient written and spoken English is required. \n \n**Mega bonus skills**\n* Knowledge of our tools and the MLOps space\n* A strong existing network in data science or open source\n\n## Perks\n* A fully remote job with a competitive salary and benefits package.\n* Our team culture is family-friendly. Our leadership includes several working parents, and our health insurance and unlimited PTO policies are designed with families in mind.\n* This role can grow with you. There are plenty of opportunities for leadership and autonomy in our small team! \n* Impact- you get to work on projects that are used every day by teams around the world! DVC and CML are used by researchers and data science teams across tech, finance, and government organizations. \n* You will get a DeeVee.\n\n \n\nPlease mention the words **GRASS EXCESS UNVEIL** when applying to show you read the job post completely (#RMjE2LjczLjIxNi42MQ==). This is a feature to avoid spam applicants. Companies can search these words to find applicants that read this and see they're human.\n\n \n\n#Location\nWorldwide

\nThe Machine Learning Specialist advances Advent Health Partners’ machine learning strategy.\nAdvent has a number of tools designed to display and gather data. This data has deeper\nmeaning and it is our goal as a company to build a machine learning architecture to maximize\nthe interpretation of this data in order to develop reliable predictive models\n\nEssential Duties and Responsibilities\n Communicate effectively with executive and clinical personnel\n Identify trends and relationships in the data used for creating and testing hypotheses.\n Mine and analyze structured/unstructured data to create algorithms\n Identify information-rich features in large target datasets\n Formulate innovative solutions to problems where machine learning is applicable\n Collaborate with Principal Scientist, Product Manager, Senior Application Developer and\nVP Engineering to produce the best possible end product\n Recommend a scalable, reliable hardware/software/saas platform\n Maintain discussions of proposed features as Github Issues\n Tweak and debug in collaboration with peers\n Maintain Slack conversations during working hours\n Provide work effort estimates to management to assist in setting priorities\n Deliver timely work in accordance with estimates\n Solve problems as they arise and communicate potential roadblocks to manage\nexpectations\n Adhere strictly to all security policies.\n\nMinimum Qualifications (Knowledge, Skills, and Abilities)\n Advanced Degree in a quantitative field such as Computer Science, Physics, Statistics,\nor related fields is preferred\n 2+ years in machine learning post-doc or professional\n Demonstrated experience working with both structured and unstructured data\n Demonstrated experience in identifying information-rich features and/or strategies for\nidentifying information-rich features in large datasets\n\n Knowledge of a variety of machine learning techniques (clustering, classification,\nregression, neural networks, etc.) and their real-world advantages/drawbacks\n Strong programming skills in Python and relevant ML libraries such as scikit-lern,\nTensorFLow and PyTorch.\n Experience in using NLP modules within Python\n Familiar with OCR modules within Python\n Experience in healthcare industry is a plus\n Experience in applying core Machine Learning methodologies: Regression, Naive\nBayesian classifier, Clustering, Matrix Factorization, k-Nearest Neighbors, Natural\nLanguage processing, Decision trees, Support Vector Machines, Neural Networks/ Deep\nLearning, Convolution Neural Networks\n Experience with AWS\n Proficient in REST, JSON\n Understanding of unit testing\n Strong written and verbal communication skills\n An experienced grasp of version control, branches and git in particular\n Thorough understanding of working in development, staging and production\nenvironments\n Unix-related skills including installation with apt-get, compiling from source, intermediate\nshell scripting \n\n#Salary and compensation\n No salary data published by company so we estimated salary based on similar jobs related to Machine Learning, Git, Python, Senior, Medical and Non Tech jobs that are similar:\n\n $70,000 — $127,500/year\n
\n\n#Benefits\n 💰 401(k)\n\n🌎 Distributed team\n\n⏰ Async\n\n🤓 Vision insurance\n\n🦷 Dental insurance\n\n🚑 Medical insurance\n\n🏖 Unlimited vacation\n\n🏖 Paid time off\n\n📆 4 day workweek\n\n💰 401k matching\n\n🏔 Company retreats\n\n🏬 Coworking budget\n\n📚 Learning budget\n\n💪 Free gym membership\n\n🧘 Mental wellness budget\n\n🖥 Home office budget\n\n🥧 Pay in crypto\n\n🥸 Pseudonymous\n\n💰 Profit sharing\n\n💰 Equity compensation\n\n⬜️ No whiteboard interview\n\n👀 No monitoring system\n\n🚫 No politics at work\n\n🎅 We hire old (and young)\n\n

Doximity is transforming the healthcare industry. Our mission is to help doctors save time so they can provide better care for patients.\n\nWe value diversity — in backgrounds and in experiences. Healthcare is a universal concern, and we need people from all backgrounds to help build the future of healthcare.\n\nHow you’ll make an impact:\n\n-Employ appropriate methods to develop performant machine learning models at scale, owning them from inception to business impact.\n-Plan, engineer, and deploy both batch-processed and real-time data science solutions to increase user engagement with Doximity’s products.\n-Collaborate cross-functionally with data engineers and software engineers to architect and implement infrastructure in support of Doximity’s data science platform.\n-Improve the accuracy, runtime, scalability and reliability of machine intelligence systems\n-Think creatively and outside of the box. The ability to formulate, implement, and test your ideas quickly is crucial.\n\nWhat we’re looking for:\n\n-3+ years of industry experience; M.S. in Computer Science or other relevant technical field preferred.\n-3+ years experience collaborating with data science and data engineering teams to build and productionize machine learning pipelines.\n-Fluent in SQL and Python; experience using Spark (pyspark) and working with both relational and non-relational databases.\n-Demonstrated industry success in building and deploying machine learning pipelines, as well as feature engineering from semi-structured data.\n-Solid understanding of the foundational concepts of machine learning and artificial intelligence.\n-A desire to grow as an engineer through collaboration with a diverse team, code reviews, and learning new languages/technologies.\n-2+ years of experience using version control, especially Git.\n-Familiarity with Linux, AWS, Redshift.\n-Deep learning experience preferred.\n-Work experience with REST APIs, deploying microservices, and Docker is a plus.\n\nAbout Doximity\n\nWe’re thrilled to be named the Fastest Growing Company in the Bay Area, and one of Fast Company’s Most Innovative Companies. Joining Doximity means being part of an incredibly talented and humble team. We work on amazing products that over 70% of US doctors (and over one million healthcare professionals) use to make their busy lives a little easier. We’re driven by the goal of improving inefficiencies in our $2.5 trillion U.S. healthcare system and love creating technology that has a real, meaningful impact on people’s lives. To learn more about our team, culture, and users, check out our careers page, company blog, and engineering blog. We’re growing fast, and there’s plenty of opportunity for you to make an impact—join us!\n\nDoximity is proud to be an equal opportunity employer, and committed to providing employment opportunities regardless of race, religious creed, color, national origin, ancestry, physical disability, mental disability, medical condition, genetic information, marital status, sex, gender, gender identity, gender expression, pregnancy, childbirth and breastfeeding, age, sexual orientation, military or veteran status, or any other protected classification. We also consider qualified applicants with criminal histories, consistent with applicable federal, state and local law. \n\nPlease mention the words **BARELY INVOLVE INNER** when applying to show you read the job post completely (#RMjE2LjczLjIxNi42MQ==). This is a feature to avoid spam applicants. Companies can search these words to find applicants that read this and see they're human.\n\n \n\n#Salary and compensation\n No salary data published by company so we estimated salary based on similar jobs related to Git, Python, Machine Learning, Engineer, Linux and Medical jobs that are similar:\n\n $75,000 — $122,500/year\n

\nDo you want to learn Big Data & Machine Learning within your Java Developer role? Would you enjoy working on Large Data Sets/Data Lakes? Do you want the flexibility of working from home?\n\nIf the answer’s yes, then this is the role for you!\n\nThe best part is that you need no prior experience working in a Data Engineering position – just a solid knowledge of Java and the passion for wanting to make the move into a more data heavy role!\n\nWe’re a mature tech start-up based in Central London and we need an innovative, passionate and enthusiastic Java Developer to create and maintain a highly scalable intelligent Data Lake platform, making use of Big Data and Machine Learning concepts which you will get to learn on the job.\n\nWe have a unique platform and we’re totally revitalising the way mobile apps are promoted, advertised and marketed. As a result, we’re helping thousands of developers manage and monetise their apps, making them more visible to the wider public, making them easier to download, increasing the amount of downloads and therefore increasing revenue streams.  \n\nWith excellent investment and a team of experienced leaders, we now need to scale up the development team (starting with the Java team and then looking to scale up the Data Science function).\n\nTo succeed as Java Developer (with a focus on data), you’ll learn skills on the job to:\n\n\n* Develop a complex, intelligent Data Lake Platform\n\n* Work collaboratively with Java and Data Science teams\n\n* Design highly scalable Java 8 architecture\n\n* Utilise big data and machine learning technology\n\n\n\n\nWe’re at the forefront of the industry and Tech is everything to us. As Java Developer you’ll have the opportunity to work with the latest technologies in the market (Big Data, Machine Learning, Scala, Python, Spark), with scope to gain cross-training into other areas of the business including Data Scientists roles or further careers within Java at Lead level in the future.\n\nIn order to do this, you’ll bring your experience including:\n\n\n* A passion for Clean Code and best engineering principles, and you’ll be able to discuss where and why you’ve implemented them in previous roles.\n\n* Conceptual knowledge of Dropwizard for microservices architecture\n\n* Knowledge of Gradle for Automation and GIT for version control\n\n\n\n\nFamiliarity of Docker Containers and AWS knowledge would be a big bonus, and an understanding of REST API & GUICE for dependency is highly beneficial but definitely not essential.\n\nYour work/life balance matters, and we know that you’ll do you best work when you’re comfortable. So, with that in mind, we use Slack, Zoom and other tech to create a flexible working environment, enabling you to work remotely or with the option of flexible hours.\n\nOnce up to speed with the tech and applications, you can choose to work from home or come into the office after rush hour. Avoid that manic/uncomfortable commute!\n\nWe know you’ll be successful as our new Java Developer so we’re offering a competitive benefits package including share options and an extremely fast rate of progression due to rapid business growth plans.\n\nAnd that’s not all! As well as the experience you’ll gain in Big Data, Machine Learning & AWS, you’ll have unlimited holidays, work alongside an ambitious Data Science team and progress rapidly. Oh, and as well as a healthy salary, we’ll keep you healthy with unlimited fruit, tea and coffee (OK, caffeine isn’t that healthy, but it makes us happy…).\n\nAre you ready to tackle this challenge?\n\nKick your Java Developer career up a gear and apply now! \n\nTapdaq work in partnership with Talent Point, a Hiring Communications business, who have designed this role on behalf of Tapdaq. When you apply, Giggs will give you a call and he'll tell you even more details about the role and help you though every step of the process.\n\n\n \n No terminology in this advert is designed to discriminate on grounds of gender, race, colour, religion, creed, disability, age, sex or sexual orientation. We’re an equal-opportunity employer and do not discriminate against these or any other class protected by applicable law. \n\n#Salary and compensation\n No salary data published by company so we estimated salary based on similar jobs related to Java, Machine Learning, Developer, Digital Nomad, Git, API and Mobile jobs that are similar:\n\n $70,000 — $120,000/year\n
\n\n#Benefits\n 💰 401(k)\n\n🌎 Distributed team\n\n⏰ Async\n\n🤓 Vision insurance\n\n🦷 Dental insurance\n\n🚑 Medical insurance\n\n🏖 Unlimited vacation\n\n🏖 Paid time off\n\n📆 4 day workweek\n\n💰 401k matching\n\n🏔 Company retreats\n\n🏬 Coworking budget\n\n📚 Learning budget\n\n💪 Free gym membership\n\n🧘 Mental wellness budget\n\n🖥 Home office budget\n\n🥧 Pay in crypto\n\n🥸 Pseudonymous\n\n💰 Profit sharing\n\n💰 Equity compensation\n\n⬜️ No whiteboard interview\n\n👀 No monitoring system\n\n🚫 No politics at work\n\n🎅 We hire old (and young)\n\n

\n\n* In deiner Rolle wirst du unseren Matching-Algorithmus perfektionieren. \n\n* Wir suchen keinen reinen Wissenschaftler, sondern in dieser Phase jemanden, der vor allem viel praktische Erfahrung mit Datenvorverarbeitung und einen guten Überblick über die AI Landschaft mitbringt. \n\n* Du solltest in deinem letzten Job schon einmal Machine Learning (am besten in einer Startup Umgebung) implementiert haben. \n\n* Die dazugehörige Infrastruktur kannst du selbst mitgestalten (Data Management, etc.).\n\n* Zugriff auf unser Backend mit bisherigen Booking Transaktionen für Performance-Indikatoren.\n\n* Im Optimalfall kennst du die APIs der großen Social Networks in und auswendig. Wenn du einen anderen Background hast, haben wir bei uns aber auch entsprechenden Ikonen. \n\n* Du solltest GIT Branches im Terminal mergen können.\n\n* Du hast schon mal ein Team geleitet oder traust dir zu eines zu leiten.\n\n* Die Arbeit generell ist im Social Media / Marketing Umfeld (YouTube, Instagram, Facebook,...). Dich sollte das Thema schon interessieren, um mit uns auf Augenhöhe über Features zu diskutieren.\n\n\n \n\n#Salary and compensation\n No salary data published by company so we estimated salary based on similar jobs related to Machine Learning, Engineer, Git, Marketing and Backend jobs that are similar:\n\n $70,000 — $120,000/year\n
\n\n#Benefits\n 💰 401(k)\n\n🌎 Distributed team\n\n⏰ Async\n\n🤓 Vision insurance\n\n🦷 Dental insurance\n\n🚑 Medical insurance\n\n🏖 Unlimited vacation\n\n🏖 Paid time off\n\n📆 4 day workweek\n\n💰 401k matching\n\n🏔 Company retreats\n\n🏬 Coworking budget\n\n📚 Learning budget\n\n💪 Free gym membership\n\n🧘 Mental wellness budget\n\n🖥 Home office budget\n\n🥧 Pay in crypto\n\n🥸 Pseudonymous\n\n💰 Profit sharing\n\n💰 Equity compensation\n\n⬜️ No whiteboard interview\n\n👀 No monitoring system\n\n🚫 No politics at work\n\n🎅 We hire old (and young)\n\n

Why work at Doximity?\n\nDoximity is the leading social network for healthcare professionals with over 70% of U.S. doctors as members. We have strong revenues, real market traction, and we're putting a dent in the inefficiencies of our $2.5 trillion U.S. healthcare system. After the iPhone, Doximity is the fastest adopted product by doctors of all time. Our founder, Jeff Tangney, is the founder & former President and COO of Epocrates (IPO in 2010), and Nate Gross is the founder of digital health accelerator RockHealth. Our investors include top venture capital firms who've invested in Box, Salesforce, Skype, SpaceX, Tesla Motors, Twitter, Tumblr, Mulesoft, and Yammer. Our beautiful offices are located in SoMa San Francisco.\n\nSkills & Requirements\n\n-3+ years of industry experience; M.S. in Computer Science or other relevant technical field preferred.\n-3+ years experience collaborating with data science and data engineering teams to build and productionize machine learning pipelines.\n-Fluent in SQL and Python; experience using Spark (pyspark) and working with both relational and non-relational databases.\n-Demonstrated industry success in building and deploying machine learning pipelines, as well as feature engineering from semi-structured data.\n-Solid understanding of the foundational concepts of machine learning and artificial intelligence.\n-A desire to grow as an engineer through collaboration with a diverse team, code reviews, and learning new languages/technologies.\n-2+ years of experience using version control, especially Git.\n-Familiarity with Linux, AWS, Redshift.\n-Deep learning experience preferred.\n-Work experience with REST APIs, deploying microservices, and Docker is a plus.\n\nWhat you can expect\n\n-Employ appropriate methods to develop performant machine learning models at scale, owning them from inception to business impact.\n-Plan, engineer, and deploy both batch-processed and real-time data science solutions to increase user engagement with Doximity’s products.\n-Collaborate cross-functionally with data engineers and software engineers to architect and implement infrastructure in support of Doximity’s data science platform.\n-Improve the accuracy, runtime, scalability and reliability of machine intelligence systems\n-Think creatively and outside of the box. The ability to formulate, implement, and test your ideas quickly is crucial.\n\nTechnical Stack\n\n-We historically favor Python and MySQL (SQLAlchemy), but leverage other tools when appropriate for the job at hand.\n-Machine learning (linear/logistic regression, ensemble models, boosted models, deep learning models, clustering, NLP, text categorization, user modeling, collaborative filtering, topic modeling, etc) via industry-standard packages (sklearn, Keras, NLTK, Spark ML/MLlib, GraphX/GraphFrames, NetworkX, gensim).\n-A dedicated cluster is maintained to run Apache Spark for computationally intensive tasks.\n-Storage solutions: Percona, Redshift, S3, HDFS, Hive, Neo4j, and Elasticsearch.\n-Computational resources: EC2, Spark.\n-Workflow management: Airflow.\n\nFun facts about the Data Science team\n\n-We have one of the richest healthcare datasets in the world.\n-We build code that addresses user needs, solves business problems, and streamlines internal processes.\n-The members of our team bring a diverse set of technical and cultural backgrounds.\n-Business decisions at Doximity are driven by our data, analyses, and insights.\n-Hundreds of thousands of healthcare professionals will utilize the products you build.\n-A couple times a year we run a co-op where you can pick a few people you'd like to work with and drive a specific company goal.\n-We like to have fun - company outings, team lunches, and happy hours! \n\nPlease mention the words **WAVE SPOT WORTH** when applying to show you read the job post completely (#RMjE2LjczLjIxNi42MQ==). This is a feature to avoid spam applicants. Companies can search these words to find applicants that read this and see they're human.\n\n \n\n#Salary and compensation\n No salary data published by company so we estimated salary based on similar jobs related to Git, Python, Machine Learning, Data Science, Engineer, Linux, Docker and Apache jobs that are similar:\n\n $80,000 — $122,500/year\n