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\nWHO WE ARE \n\nKinship, Mars Petcare's newest division, is a hotbed for future innovation, data science and analytics, and at the forefront of emerging technology for pets, pet owners and veterinarians. At Kinship, we move quickly to shape the future of pet care. We are Optimistic, Purposefully Inquisitive, Open to all, and passionate about what’s possible. We’re a coalition of bright minds, big ideas, and bold businesses united by our love of pets.\n\nPart of Mars, Incorporated, a family-owned business with more than a century of history making diverse products and offering services for people and the pets people love, the 85,000 Associates in Mars Petcare are dedicated to one purpose: A BETTER WORLD FOR PETS. With 75 years of experience, our portfolio of almost 50 brands serves the health and nutrition needs of the world’s pets and The WALTHAM Centre for Pet Nutrition  has advanced research in the nutrition and health of pets for over 50 years. Mars Petcare is also a leading veterinary health provider through a network of over 2,000 pets. We’re also active in innovation and technology for pets, with WISDOM PANEL™ genetic health screening and DNA testing for dogs, the WHISTLE™ GPS dog tracker, and LEAP VENTURE STUDIO accelerator and COMPANION FUND™ programs that drive innovation and disruption in the pet care industry. \n\nA BIT ABOUT OUR TEAM \n\nPet Insight is a team of data scientists, technologists, and vets that has partnered with Whistle Labs, Banfield Pet Hospital, and pet-owner citizen scientists to conduct the largest population health study in pet care. We focus on research and development, building state-of-the-art technologies (see FilterNet and leveraging our unique data to create solutions that improve the lives of pets. We’re looking for a data scientist to focus on updating and improving existing Whistle algorithms and productized data science features.\n\n\nWe are seeking an experienced Python Engineer to add to our growing team!\n\nYou will:\n\n\n* Develop our core data processing application in Python, which generates results in both streaming and batch modes within a distributed cloud system. \n\n* Evaluate and improve the reliability and performance of the system, and articulately communicate results to the rest of the team with effective data visualizations.\n\n* Work with the Whistle backend and mobile development teams to transition new features to our production website and mobile apps.\n\n* Analyze data, using tools like Jupyter Notebooks, Pandas and the rest of the Scientific Python stack.\n\n* Manage and extend both our R&D and production databases (Postgresql, Redis, DynamoDB).\n\n* Contribute to the release and scaling of machine learning models in a high-volume, production environment.\n\n\n\n\n\nHere's what we're looking for in a strong candidate:\n\n\n* Technical degree (BS/MS in a technical subject like Engineering, Computer Science, Math, or Physics).\n\n* 2+ years experience in software development using Python tools suites (pandas, numpy, sqlalchemy, celery, etc.).\n\n* Facility with core programming paradigms, algorithms, and patterns.\n\n* An understanding of computing performance (both locally and over networks).\n\n* Commitment to software development best practices (Agile, Git, Test-Driven Development).\n\n* Experience building a streaming, distributed software application.  \n\n* Experience developing and scaling data pipelines and ETL processes. \n\n* Experience with SQL, including work with large databases and legacy databases. \n\n* Ability to communicate data stories clearly with graphs and visualizations.\n\n\n\n\n\nExtra treats for:\n\n\n* Experience with some or all of our technology stack (see above).\n\n* Experience managing a system of Amazon Web Services cloud resources, including networking, identity and access management, troubleshooting, and cost optimization.  \n\n* Familiarity with machine learning techniques. \n\n* Experience with dependency management and configuration using Docker and shell scripting.  \n\n* Experience developing and utilizing APIs.\n\n* Knowledge of statistics\n\n\n

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