Remote Apache + Artificial Intelligence + Python Jobs

\nPosition: Sr. or Team Lead Machine Learning Engineer, Full Time\n\nLocation: Fully Remote anywhere in the USA or optional office location in SF\n\nAt Cisco Meraki, we know that technology can connect, empower, and drive us. Our mission is to simplify technology so our customers can focus on what's most meaningful to them: their students, patients, customers, and businesses. We’re making networking easier, faster, and smarter with technology that simply works.\n\nAs a Machine Learning engineer on the Insight team, you will collaborate with firmware and full stack engineers to design, plan, and build customer-facing analytics tools. Meraki's cloud-managed model offers a unique opportunity to draw upon data from millions of networks across our wide ranging customer base. The goal is to use the rich telemetry data available from these networks and combine it with the power of machine learning and the cloud to build an analytics engine that can provide intuitive, yet detailed insights into the performance of customer networks.\n\nWhat you can expect:\n\n\n* Build a system that ingests real-time streams of network performance data and identifies network performance degradation, optimizing for both low latency and few false positives\n\n* Design models that predict network performance for customers to help them understand their network performance issues\n\n* Work with firmware and backend engineers to design uplink selection algorithm for SD-WAN\n\n* Collaborate with full stack engineers to make intuitive data visualizations and integrate predictions seamlessly and powerfully into the user experience\n\n* Build, maintain, and monitor data pipelines and infrastructure for training and deploying models\n\n\n\n\nWhat we're ideally looking for:\n\n\n* 5+ years of relevant industry experience\n\n* Advanced training in mathematics, statistics, and modeling\n\n* Experience programming in Python AND some other programming language like scala, golang, ruby, etc.\n\n* Experience working with algorithms and building models for supervised and unsupervised learning.\n\n* Experience using data processing and ML libraries such as Pandas, Scikit-Learn, Tensorflow, Keras, etc.\n\n* Experience working with distributed computing engines like Apache Spark, etc. and real time data streaming services like Amazon Kinesis.\n\n* Experience implementing and monitoring data pipelines.\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, Executive, Amazon, Cloud, Python, Apache and Backend jobs that are similar:\n\n $75,000 — $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 Thrive Global is changing the way people live through our behavior change platform and apps used to impact individual and organizational well-being and productivity. The marriage of data and analytics, our best-in-class content and science-backed behavior change IP will help people go from knowing what to do to actually doing it, enabling millions of consumers to begin the Thrive behavior change journey.  As a technical lead on Thrive’s Data Science and Analytics team, you will play a significant role in building Thrive’s platform and products.\n\nWho We Are Looking For\n\n\n* A versatile engineering lead who has significant experience with data at all levels of maturity:  raw telemetry through deployment and maintenance of models in operations \n\n* Is excited about collaborating with others, engineering and non-engineering, both learning & teaching as Thrive grows.\n\n* An innovator looking to push the boundaries of automation, intelligent ETL, AIOps and MlOps to drive high-quality insights and operational efficiency within the team\n\n* Has a proven track record of building and shipping data-centric software products\n\n* Desires a position that is approximately 75% individual technical contributions and 25% mentoring junior engineers or serving as a trusted advisor to engineering leadership\n\n* Is comfortable in a high growth, start-up environment and is willing to wear many hats and come up with creative solutions.\n\n\n\n\nHow You’ll Contribute\n\n\n* Collaborate with the Head of Data Science and Analytics to design an architecture and infrastructure to support data engineering and machine learning at Thrive\n\n* Implement a production-grade data science platform which includes building data pipeline, automation of data quality assessments, and automatic deployment of models into production\n\n* Develop new technology solutions to ensure a seamless transition of machine learning algorithms to production software, to enable the building out of easy to use datasets and to reduce other friction points within the data science life-cycle\n\n* Assist with building a small but skilled interdisciplinary team of data professionals: scientists, analysts, and engineers\n\n* Consider user privacy and security at all times\n\n\n\n\nRequired Skills\n\n\n* Master’s or Ph.D. degree in Computer Science or a related discipline (e.g., Mathematics, Physics)\n\n* 3+ years of technical leadership, team size of 5 or more, in data engineering or machine learning projects\n\n* 8+ years of industry experience with data engineering and machine learning\n\n* Extensive programming experience in Java or Python with applications in data engineering and machine learning.\n\n* Experience with data modeling, large-scale batch, and real-time data processing, ETL design, implementation and maintenance\n\n* Excellent verbal and written communication skills\n\n* Self-starter with a positive attitude, intellectual curiosity and a passion for analytics and solving real-world problems\n\n\n\n\nRelevant Technology and Tools Experience\nA good cross-section of experience in the following areas is desired:\n\n\n* AI/ML platforms:  TensorFlow, Apache MXnet, Theano, Keras, CNTK, scikit-learn, H2O, Spark MLlib, AWS SageMaker, etc.\n\n* Relational databases: MySQL, Postgres, RedShift, etc.\n\n* Big data technologies:  Spark, HDFS, Hive, Yarn, etc.\n\n* Data ingestion tools: Kafka, NiFi, Storm, Amazon Kinesis, etc.\n\n* Deployment technologies:  Docker, Kubernetes, or OpenStack\n\n* Public Cloud:  Azure, AWS or Google Cloud Platform\n\n\n\n\nOur Mission\nThrive Global’s mission is to end the stress and burnout epidemic by offering companies and individuals sustainable, science-based solutions to enhance well-being, performance, and purpose, and create a healthier relationship with technology. Recent science has shown that the pervasive belief that burnout is the price we must pay for success is a delusion. We know, instead, that when we prioritize our well-being, our decision-making, creativity, and productivity improve dramatically. Thrive Global is committed to accelerating the culture shift that allows people to reclaim their lives and move from merely surviving to thriving.\n\nWhat We Offer\n\n\n* A mission-driven company that’s truly making a difference in the lives of people around the world  \n\n* Ability to develop within the company and shape our growth strategy\n\n* Human-centric culture with a range of wellness perks and benefits\n\n* Competitive compensation package\n\n* Medical, vision and dental coverage + 401k program with company match\n\n* Generous paid time-off programs \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, Executive, Teaching, Amazon, Java, Cloud, Python, Junior and Apache jobs that are similar:\n\n $75,000 — $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

\nData Science and Big Data are all we do.\n\nIf you're inspired by innovation and passionate about driving customer success - this may be the ideal opportunity to leverage your systems engineering and automation experience to build and support Machine Learning platforms for the clients we serve.\n\nAt phData, our proven success has skyrocketed the demand for our services, resulting in quality growth and an expanded presence at our company headquarters located in downtown Minneapolis and in Bangalore, India.\n\nAs the world’s first and only Data Science Enablement services firm and the largest pure-play Big Data service provider, our team includes Apache committers, Machine Learning experts and the most knowledgeable Spark and Scala development team in the industry. phData has earned the trust of customers by demonstrating our mastery of Data Science and Big Data services along with our commitment to excellence.\n\nIn addition to phenomenal growth and learning opportunities, we offer competitive compensation and excellent perks including base salary, annual bonus, extensive training, paid certifications - in addition to generous PTO, a comprehensive benefits program and employee equity.\n\nMachine Learning Platform Architect\n\nAs a Machine Learning Platform Architect, you will serve as the guiding force in architecting and engineering Machine Learning platforms for enterprise clients. In this hands-on role, your responsibilities will include:\n\n\n* Help automate and deploy Machine Learning platforms and applications\n\n* Guide customers on the best practices of upgrades, patches, and maintenance\n\n* Deploy continuous integration and security\n\n* Maintain constant curiosity and a thirst for learning\n\n* Investigate product related issues both for individual customers and for common trends that may arise\n\n* Participate in occasional weekend on-call rotation for critical support needs\n\n* Provide a best-in-class customer experience\n\n\n\n\nRequired Experience:\n\n\n* 5-7 years of Linux Systems Engineering experience to include monitoring, patches, upgrades, and O/S support\n\n* Proven system/application automation and deployment experience using Ansible, Chef, Puppet or similar tools\n\n* Experience with Application Web Frameworks is a plus;  Apache, Engenix, Tomcat, Spring, Flask, Play, etc is plus\n\n* Previous Consulting experience with external customers is highly preferred\n\n* Hands-on configuration with Security including LDAP, Active Directory\n\n* Passion for providing a great customer experience\n\n* Ability to work in a fast paced and agile environment\n\n* Excellent communication skills (written and verbal)\n\n* Strong problem-solving and analytical skills\n\n* Demonstrable troubleshooting skills\n\n* A positive attitude toward feedback and continual improvement\n\n\n\n\nPreferred Qualifications:\n\n\n* Working knowledge and experience with Python related technologies.\n\n* Understanding of networking, distributed systems, and Linux operating system concepts\n\n* Knowledge of relational database management systems (RDBMS), SQL and database concepts\n\n* On-the-job experience troubleshooting enterprise customer issues\n\n* Knowledge and experience with Kubernetes\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, Architecture, Python, Scala, Apache and Linux jobs that are similar:\n\n $80,000 — $125,000/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

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. Our data science team is deliberate and self-reflective about the kind of data team and culture that we are building, seeking data scientists and engineers that are not only strong in their own aptitudes but care deeply about supporting each other's growth. We have one of the richest healthcare datasets in the world, and our team brings a diverse set of technical and cultural backgrounds.\n\nDoximity’s social network has over 70% of US doctors as members. We recently launched a newsfeed which helps physicians navigate the latest practice-changing medical literature, parsing through millions of scientific studies while personalizing content to their patient base and every stage of their medical career. We’re looking for a deep learning expert to help our data science and engineering teams build models in support of the newsfeed, combining metadata from our clinician social graph with text-based features.\n\nHow you’ll make an impact:\n\n-Apply NLP methods and build deep neural networks to personalize medical content to our clinician -members.\n-Optimize the layout of different content types (e.g., journal articles, news articles, video, social updates) within the newsfeed.\n-Collaborate with data engineers to devise plans to refresh the newsfeed and surface optimized content to users near real-time.\n-Provide technical leadership to other data scientists and data engineers working on the newsfeed product.\n\nWhat we’re looking for:\n\n-4+ years of industry experience and M.S./Ph.D. in Computer Science, Engineering, Statistics, or other relevant technical field.\n-4+ years experience with various machine learning methods (classification, clustering, natural language processing, ensemble methods) and parameters that affect their performance.\n-Experience building deep neural networks in support of recommendation systems.\n-Solid engineering skills to build scalable solutions and help automate data processing challenges.\n-Desire to provide technical leadership and mentorship to other data team members.\n-Expert knowledge of probability and statistics (e.g., experimental design, optimization, predictive modeling).\n-Excellent problem-solving skills and ability to connect data science work to product impacts.\n-Fluent in SQL and Python; experience using Apache Spark (pyspark).\n-Experience working with relational and non-relational databases.\n\nNice to have:\n\n-Experience applying reinforcement learning to industry problems.\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 **TRIM MUFFIN LIGHT** when applying to show you read the job post completely (#RMjE2LjczLjIxNi4xODQ=). 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 Python, Machine Learning, Data Science, Senior, Medical and Apache jobs that are similar:\n\n $80,000 — $127,500/year\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. Our data science team is deliberate and self-reflective about the kind of data team and culture that we are building, seeking data scientists and engineers that are not only strong in their own aptitudes but care deeply about supporting each other's growth. We have one of the richest healthcare datasets in the world, and our team brings a diverse set of technical and cultural backgrounds.\n\nDoximity’s social network has over 70% of US doctors as members and 40M connections among them. We currently are looking for a data scientist to lead a team of other data scientists, data engineers and data analysts with the goal of utilizing this medical graph to better connect and promote discussion among our clinician members.\n\nHow you’ll make an impact:\n\n-Build link prediction models to recommend colleagues for our members to connect and engage with (the “people you may know” problem) to increase user engagement across Doximity’s platforms.\n-Leverage data from Doximity’s social graph to improve the user personalization models that recommend medical and social content to our clinician members.\n-Discover trends and new business opportunities from physician’s medical claims and referral networks.\n-Provide technical leadership to other data scientists and data engineers working on our growth and colleaguing product teams.\n\nWhat we’re looking for:\n\n-4+ years of industry experience and M.S./Ph.D. in Computer Science, Engineering, Statistics, or other relevant technical field.\n-4+ years experience with various machine learning methods (classification, clustering, natural language processing, ensemble methods) and parameters that affect their performance.\n-Experience applying graph theory, analytics, and processing to industry problems.\n-Solid engineering skills to build scalable solutions and help automate data processing challenges.\n-Desire to provide technical leadership and mentorship to other data team members.\n-Excellent problem-solving skills and ability to connect data science work to product impacts.\n-Fluent in SQL and Python; experience using Apache Spark (pyspark)\n-Experience working with relational and non-relational databases.\n\nNice to have:\n\n-Experience with neo4j and either Spark GraphX or GraphFrames for performing graph analytics\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 **SKIN PROUD MAJOR** when applying to show you read the job post completely (#RMjE2LjczLjIxNi4xODQ=). 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 Python, Machine Learning, Data Science, Senior, Stats, Medical and Apache jobs that are similar:\n\n $80,000 — $125,000/year\n

Doximity is the leading online medical network with over 70% of U.S. doctors as members. We have strong revenues, profits, 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. Launched by Jeff Tangney in 2011; Jeff previously founded healthcare pioneer Epocrates (NASDAQ: EPOC). Our beautiful offices are located in SoMa San Francisco.\n##Skills & Requirements\n- 4+ years of industry experience and M.S./Ph.D. in Computer Science, Engineering, Statistics, or other relevant technical field.\n- 4+ years experience with various machine learning methods (classification, clustering, natural language processing, ensemble methods, deep learning) and parameters that affect their performance.\n- Expert knowledge of probability and statistics (e.g., experimental design, optimization, predictive modeling).\n- Experience with recommendation algorithms and strong knowledge of machine learning concepts.\nSolid engineering skills to build scalable solutions and help automate data processing challenges.\n- Excellent problem-solving skills and ability to connect data science work to product impacts.\n- Fluent in SQL and Python; experience using Apache Spark (pyspark) and working with both relational and non-relational databases.\n- Familiarity with AWS, Redshift.\n\n##What you can expect\n- Employ scalable statistical methods and NLP methods to develop machine learning models at scale, owning them from inception to business impact.\n- Leverage knowledge of recommendation algorithms to increase user engagement through personalization of delivered content.\n- Plan, engineer and measure outcomes of online experiments to help guide product development.\n- Collaborate with a team of product managers, analysts, data engineers, data scientists, and other developers.\n- Think creatively and outside of the box. The ability to implement and test your ideas quickly is crucial.\n\n##Technical Stack\n- We historically favor Python and MySQL, but leverage other tools when appropriate for the job at hand.\n- Machine learning (linear/logistic regression, ensemble-models, boosted-models, clustering, NLP, text categorization, user modeling, collaborative filtering, etc) via industry-standard packages (sklearn, 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.\n- Computational resources: EC2, Spark.\n- Workflow management: Airflow.\n\n##Fun facts about the Data Science team\n- We have access to one of the richest healthcare datasets in the world, with deep information on hundreds of thousands of healthcare professionals and their connections.\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 **LIFE DISAGREE TREND** when applying to show you read the job post completely (#RMjE2LjczLjIxNi4xODQ=). 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 Python, Machine Learning, Data Science, Senior, Apache, Medical and Engineer jobs that are similar:\n\n $80,000 — $125,000/year\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 (#RMjE2LjczLjIxNi4xODQ=). 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