JV
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
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