Skip to content
mimi

Senior Data Scientist - W2 Only

Jobs via Dice

Remote (Global) Full-time Senior 2w ago

About the role

About this Position

Job Title

Senior Data Scientist

Responsibilities

  • Establish a development framework for the PoC, including task breakdowns, milestones, deliverables, risks, and mitigation plans.
  • Participate in analyzing current intake processes, decision workflows, and resource allocation to identify and prioritize shortcomings.
  • Lead the design of a new intake approach using NLP and machine learning to address identified gaps.
  • Define functional components, evaluate architectural/computational trade-offs, and assess risks (technical, schedule, security).
  • Evaluate and select appropriate data sources (existing, sample, simulated) and document the final approach for transparency.
  • Develop and lead design reviews, assessing functional effectiveness, risks, data usage, and testing/demonstration methods.
  • Oversee PoC implementation with regular updates, risk mitigation, and support for resolving technical/administrative issues.
  • Conduct demo sessions, gather stakeholder feedback, contribute to roadmap development, and support Agile processes for project success.

Required Skills/Experience

  • Bachelor's, Master's, or Ph.D. in computer science, mathematics, engineering, physics, or related field.
  • Have participated in US Federal Gov't data science programs requiring TS/SCI clearance, delivering solutions requiring the combination of geospatial disciplines and pattern of life, and Social network connections.
  • Data engineering expertise, with demonstrable experience custom building programs processing in excess of 700 Million records in less than :30min, on a highly frequent, reoccurring basis.
  • Proven expertise working with client's data attributes to predict child welfare outcomes, including but not limited data attribute selection, data clean up and statistical tuning.
  • Extensive knowledge of statistical algorithms, machine learning, and adaptive systems.
  • Prior history of designing and building machine learning algorithms from the ground up.
  • Experience with making technical trade-offs between algorithmic approaches. based on collective errors, computational time, scalability, and outcomes.
  • Prior success in developing optimal non-rule-based decision-making systems where the inputs are stochastic.
  • Successful history of converting social processes and human decision-making into computational models that yield improved results.

Requirements

  • Have participated in US Federal Gov't data science programs requiring TS/SCI clearance, delivering solutions requiring the combination of geospatial disciplines and pattern of life, and Social network connections.
  • Data engineering expertise, with demonstrable experience custom building programs processing in excess of 700 Million records in less than :30min, on a highly frequent, reoccurring basis.
  • Proven expertise working with client's data attributes to predict child welfare outcomes, including but not data attribute selection, data clean up and statistical tuning.
  • Extensive knowledge of statistical algorithms, machine learning, and adaptive systems.
  • Prior history of designing and building machine learning algorithms from the ground up.
  • Experience with making technical trade-offs between algorithmic approaches. based on collective errors, computational time, scalability, and outcomes.
  • Prior success in developing optimal non-rule-based decision-making systems where the inputs are stochastic.
  • Successful history of converting social processes and human decision-making into computational models that yield improved results.

Responsibilities

  • Establish a development framework for the PoC, including task breakdowns, milestones, deliverables, risks, and mitigation plans.
  • Participate in analyzing current intake processes, decision workflows, and resource allocation to identify and prioritize shortcomings.
  • Lead the design of a new intake approach using NLP and machine learning to address identified gaps.
  • Define functional components, evaluate architectural/computational trade-offs, and assess risks (technical, schedule, security).
  • Evaluate and select appropriate data sources (existing, sample, simulated) and document the final approach for transparency.
  • Develop and lead design reviews, assessing functional effectiveness, risks, data usage, and testing/demonstration methods.
  • Oversee PoC implementation with regular updates, risk mitigation, and support for resolving technical/administrative issues.
  • Conduct demo sessions, gather stakeholder feedback, contribute to roadmap development, and support Agile processes for project success.

Skills

machine learningNLP

Don't send a generic resume

Paste this job description into Mimi and get a resume tailored to exactly what the hiring team is looking for.

Get started free