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Amivero

Data Scientist

Amivero · United States

  • Hybrid
  • Full-time
  • $120,000 / year
  • United States
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Job highlights

  • Develop data science practice and identify patterns.
  • Design experiments and build predictive models.
  • Implement analytics pipelines and visualizations.
  • Recommend and test new algorithms.
  • Educate organization on analytical approaches.

About the role

About Amivero

Amivero’s team of IT professionals delivers digital services that elevate the federal government, whether national security or improved government services. Our human-centered, data-driven approach is focused on truly understanding the environment and the challenge, and reimagining with our customer how outcomes can be achieved.

Our team of technologists leverage modern, agile methods to design and develop equitable, accessible, and innovative data and software services that impact hundreds of millions of people.

As a member of the Amivero team you will use your empathy for a customer’s situation, your passion for service, your energy for solutioning, and your bias towards action to bring modernization to very important, mission-critical, and public service government IT systems.

Job Summary

Seeking a Data Scientist to gather critical insights, and identify and analyze patterns. In this role, you will work closely with the data team, fraud operational team, and leadership to develop our data science practice. If you are data-driven, results-oriented, and eager to help solve data problems of varying complexities, then this would be the perfect opportunity for you.

Responsibilities

  • Partner with leadership and stakeholders to develop our data science function
  • Design experiments, test hypotheses, and build data models
  • Work with data team to identify and analyze patterns
  • Design and lead implementation of analytics pipelines and visualization
  • Recommend and test new analytics algorithms and models
  • Educate the organization on new analytical approaches to drive business decisions

Qualifications

  • 3+ years of hands-on experience in data science for a SaaS company or a mature startup
  • 5+ years of experience in data analytics or related
  • BS/MS in Data Science or a related quantitative or scientific field
  • Experience with SQL & the Python ML ecosystem - pandas, numpy, sklearn, etc.
  • Experience with Time Series Prediction models & one or more deep learning libraries
  • Experience ingesting, processing, and visualizing data sources of varying types - structured/relational and unstructured
  • Experience in developing, managing, and manipulating large, complex datasets
  • Data-driven, detail-oriented individual with excellent storytelling and problem-solving abilities
  • Ability to work independently and autonomously, as well as part of a team
  • Superb time management, prioritization of tasks and ability to meet deadlines with little supervision

Key skills/competency

  • Data Science
  • Python
  • SQL
  • Machine Learning
  • Data Analysis
  • SaaS
  • Startup
  • Analytics Pipelines
  • Time Series Prediction
  • Deep Learning

Skills & topics

  • Data Scientist
  • Data Science
  • Python
  • SQL
  • Machine Learning
  • Data Analysis
  • SaaS
  • Startup
  • Analytics Pipelines
  • Time Series Prediction

How to get hired

  • Tailor your resume: Highlight data science, Python, SQL, and ML experience.
  • Showcase relevant projects: Detail SaaS or startup data science work.
  • Emphasize problem-solving: Provide examples of analyzing complex datasets.
  • Prepare for technical questions: Review Python ML ecosystem and time series models.
  • Demonstrate autonomy: Show ability to meet deadlines independently.

Technical preparation

Master Python ML libraries: pandas, numpy, sklearn.,Practice SQL for complex dataset manipulation.,Study Time Series Prediction and deep learning.,Build projects ingesting varied data sources.

Behavioral questions

Demonstrate data-driven problem-solving examples.,Showcase ability to work autonomously.,Provide examples of meeting deadlines independently.,Describe experience educating others on analytics.

Frequently asked questions

What are the key technical skills required for the Data Scientist role at Amivero?
For the Data Scientist position at Amivero, you'll need hands-on experience with SQL and the Python ML ecosystem, including libraries like pandas, numpy, and sklearn. Experience with Time Series Prediction models and at least one deep learning library is also essential. You should also be proficient in ingesting, processing, and visualizing diverse data sources.
What kind of experience is expected for a Data Scientist applicant at Amivero?
Amivero is looking for at least 3 years of hands-on data science experience, ideally within a SaaS company or a mature startup. Additionally, a minimum of 5 years of experience in data analytics or a related field is required. A BS/MS in Data Science or a similar quantitative/scientific field is also a prerequisite.
How important is experience with large, complex datasets for this Data Scientist role?
Experience in developing, managing, and manipulating large, complex datasets is a critical requirement for this Data Scientist role at Amivero. This indicates the need for candidates who can handle substantial data volumes and structures to derive meaningful insights.
What does Amivero value in a Data Scientist candidate beyond technical skills?
Amivero seeks a data-driven, detail-oriented individual with excellent storytelling and problem-solving abilities for their Data Scientist role. The company also emphasizes the importance of the ability to work independently and autonomously, alongside strong time management and prioritization skills.
Can you describe the day-to-day responsibilities of a Data Scientist at Amivero?
As a Data Scientist at Amivero, you will collaborate with leadership and stakeholders to build the data science function, design experiments, test hypotheses, and construct data models. You'll work with the data team to analyze patterns, design and implement analytics pipelines and visualizations, and recommend new analytical approaches to drive business decisions.

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