Delphi-US
Title: Senior Data Scientist (Contract) - Job#4669
Location:
Remote or Hybrid (Houston TX)
Job Description: Our Machine Learning team tackles major opportunities for operational efficiency and revenue generation and deploys these models across environments where they re-shape the way we work. We are seeking a curious, proactive, and innovative Data Scientist to join our team. The ideal candidate has a strong scientific background, experience blending various datasets, building statistical/machine learning models, and communicating the results back to business partners.
Candidates Must Have the following background to be considered:
Domain expertise with methane, air quality measurement, or atmospheric modeling would be very valuable since gas concentrations and movements are a lot of the modeling work. Modeling and studying other related scientific phenomena could be a good backup too. Spatiotemporal statistical modeling expertise. Time series expertise alone would also be a good backup even if we don't have the spatial statistics component. Bonus points for someone with Bayesian time series/spatial experience. Python / R programming to model and analyze the data. SQL - we're working with a variety of disparate datasets as we build out sensors at our environmental sites, so it's important that candidates can navigate uncharted datasets and quickly figure out how to link these accurately. SQL Expertise is a Must: to collect, aggregate new data sources & stage for modelling & analysis methane measurement and atmospheric sciences dispersion models statistical modeling data management (SQL) experience
Responsibilities: • Apply machine learning, advanced analytical techniques, and critical thinking to solve complex business problems • Seek, build, and consolidate data inputs proactively to create and improve models • Translate business partners' needs into data science projects and make technical decisions based on the tradeoff between complexity and value • Drive projects, individually and collaboratively, through the data science lifecycle including data collection, exploration/analysis, model development, validation, and deployment • Develop presentations to communicate key messages to senior sponsors, non-technical partners, fellow data scientists, and other stakeholders • Work with technical partners to deploy models and streamline the process to scale our work
Required Qualifications: Building statistical or machine learning models for prediction and inference o Ability to code within Python (R also considered) o Advanced SQL knowledge to pull and transform data
Education and Experience • Quantitative Foundation: B.S. degree in a quantitative field (e.g., Statistics, Engineering, Computer Science, Meteorology, Physics, Mathematics, Economics, Operations Research). • Experience: 3+ years' experience in data science building and deploying models into production
Technical Skills • Programming: compose clean, efficient, and reusable code in Python and/or R. • Machine Learning / Modeling: understand what types of algorithms to use, their benefits and drawbacks, and how to implement them. • Data Wrangling: write efficient SQL queries from scratch that blend data from a variety of sources in the right form for modeling, analysis, and scoring. • Statistical Analysis: investigate trends, patterns, and relationships using statistical methods and tests to reach actionable conclusions and understand causal relationships. • Data Visualization: grasp data-ink ratios and bring data-driven stories to life through visuals. • Scientific Research: experience using adjacent scientific literature to advance our thinking and modeling in novel areas where existing research is thin
Soft Skills • Curious: bring intellectual curiosity, an inquisitive nature, and a desire to deepen your knowledge and continue learning. • Ownership: take responsibility to proactively advance projects, contribute to the team/organization, and improve existing processes. • Business acumen: understand the bigger picture for customers and the business while connecting your work to key objectives for both. • Storytelling: write and present messages and insights clearly to persuade non-technical partners that they can confidently use our models and solutions.
Preferred Qualifications • A graduate degree (Masters or PhD) in a quantitative field • Experience with spatial modeling, greenhouse gas emissions, atmospheric modeling, or remote sensing data • Proficiency using git for version control, collaboration, and releases • Expertise with cloud services like AWS (SageMaker, S3, Redshift, etc.) and Snowflake • Built dashboards for visualizing model outputs and performance monitoring using Microsoft PowerBI, Python dash, or similar tools
About Delphi-US Delphi-US is a national recruiting firm based in Newport, Rhode Island. We specialize in IT, Engineering and Professional Staffing services for organizations from Main Street to Wall Street. Our mission is simple: To connect great people to great companies. We accomplish this with a proprietary skill-based and cultural matching process that results in higher qualified submissions along with increased interviews and offer rates. You'll find our team is friendly, professional and ready to advocate on your behalf, armed with industry trends, and an understanding of employer expectations.
Location:
Remote or Hybrid (Houston TX)
Job Description: Our Machine Learning team tackles major opportunities for operational efficiency and revenue generation and deploys these models across environments where they re-shape the way we work. We are seeking a curious, proactive, and innovative Data Scientist to join our team. The ideal candidate has a strong scientific background, experience blending various datasets, building statistical/machine learning models, and communicating the results back to business partners.
Candidates Must Have the following background to be considered:
Domain expertise with methane, air quality measurement, or atmospheric modeling would be very valuable since gas concentrations and movements are a lot of the modeling work. Modeling and studying other related scientific phenomena could be a good backup too. Spatiotemporal statistical modeling expertise. Time series expertise alone would also be a good backup even if we don't have the spatial statistics component. Bonus points for someone with Bayesian time series/spatial experience. Python / R programming to model and analyze the data. SQL - we're working with a variety of disparate datasets as we build out sensors at our environmental sites, so it's important that candidates can navigate uncharted datasets and quickly figure out how to link these accurately. SQL Expertise is a Must: to collect, aggregate new data sources & stage for modelling & analysis methane measurement and atmospheric sciences dispersion models statistical modeling data management (SQL) experience
Responsibilities: • Apply machine learning, advanced analytical techniques, and critical thinking to solve complex business problems • Seek, build, and consolidate data inputs proactively to create and improve models • Translate business partners' needs into data science projects and make technical decisions based on the tradeoff between complexity and value • Drive projects, individually and collaboratively, through the data science lifecycle including data collection, exploration/analysis, model development, validation, and deployment • Develop presentations to communicate key messages to senior sponsors, non-technical partners, fellow data scientists, and other stakeholders • Work with technical partners to deploy models and streamline the process to scale our work
Required Qualifications: Building statistical or machine learning models for prediction and inference o Ability to code within Python (R also considered) o Advanced SQL knowledge to pull and transform data
Education and Experience • Quantitative Foundation: B.S. degree in a quantitative field (e.g., Statistics, Engineering, Computer Science, Meteorology, Physics, Mathematics, Economics, Operations Research). • Experience: 3+ years' experience in data science building and deploying models into production
Technical Skills • Programming: compose clean, efficient, and reusable code in Python and/or R. • Machine Learning / Modeling: understand what types of algorithms to use, their benefits and drawbacks, and how to implement them. • Data Wrangling: write efficient SQL queries from scratch that blend data from a variety of sources in the right form for modeling, analysis, and scoring. • Statistical Analysis: investigate trends, patterns, and relationships using statistical methods and tests to reach actionable conclusions and understand causal relationships. • Data Visualization: grasp data-ink ratios and bring data-driven stories to life through visuals. • Scientific Research: experience using adjacent scientific literature to advance our thinking and modeling in novel areas where existing research is thin
Soft Skills • Curious: bring intellectual curiosity, an inquisitive nature, and a desire to deepen your knowledge and continue learning. • Ownership: take responsibility to proactively advance projects, contribute to the team/organization, and improve existing processes. • Business acumen: understand the bigger picture for customers and the business while connecting your work to key objectives for both. • Storytelling: write and present messages and insights clearly to persuade non-technical partners that they can confidently use our models and solutions.
Preferred Qualifications • A graduate degree (Masters or PhD) in a quantitative field • Experience with spatial modeling, greenhouse gas emissions, atmospheric modeling, or remote sensing data • Proficiency using git for version control, collaboration, and releases • Expertise with cloud services like AWS (SageMaker, S3, Redshift, etc.) and Snowflake • Built dashboards for visualizing model outputs and performance monitoring using Microsoft PowerBI, Python dash, or similar tools
About Delphi-US Delphi-US is a national recruiting firm based in Newport, Rhode Island. We specialize in IT, Engineering and Professional Staffing services for organizations from Main Street to Wall Street. Our mission is simple: To connect great people to great companies. We accomplish this with a proprietary skill-based and cultural matching process that results in higher qualified submissions along with increased interviews and offer rates. You'll find our team is friendly, professional and ready to advocate on your behalf, armed with industry trends, and an understanding of employer expectations.