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Trident Systems is a technology company specializing in innovative services for the aerospace and defense sectors, with the aim of providing affordable solution
Title: Senior Data Scientist Location: Remote, US Full Time Employee Full-Time Remote, US 6 days agoRequisition ID: 1814 Apply Salary Range:$78,900.00 To $187,200.00 Annually Position Title: Senior Data Scientist Requisition ID: 1814 Position Location: Remote Position Reports To: Associate Data Science Manager Supervises Others: No At Trident Systems, we believe that strong engineering principles are fundamental to driving innovation and solving complex problems. We promote a culture characterized by rigorous engineering practices and a commitment to continuous improvement. This is achieved by leveraging our organization's collective expertise through collaborative development processes, which include thorough design and peer reviews. We can deliver innovative, high-performance solutions that meet our customers' evolving requirements by integrating our specialized knowledge in aerospace electronic systems with appropriately scaled development methodologies. We are a mission partner supporting DoD, Intelligence Community, and Civil space customers. We develop complex, radiation effects mitigated, designs that balance competing requirements in modern space programs, delivering cutting-edge solutions that enable our customers to achieve more in space Position Summary This position will be part of the Predictive Maintenance and Logistics Team supporting Department of Defense (DoD) customers on projects that leverage advanced technologies including machine learning, artificial intelligence (ML/AI), and cloud infrastructure. The Senior Data Scientist will contribute to the development, evaluation, and deployment of data-driven models focused on time-series telemetry and operational system data. The role emphasizes hands-on Python development using modern machine learning frameworks, working with real-world sensor and telemetry data to build models that support health monitoring, anomaly detection, forecasting, and decision support. The Senior Data Scientist will collaborate closely with engineers, data visualization specialists, and program leadership to transition analytical solutions from research into operational environments. U.S. citizenship and the ability to obtain a security clearance are required. Duties and Responsibilities - Develop and evaluate machine learning models using Python to analyze time-series and telemetry data. - Perform data exploration, feature engineering, and preprocessing on structured and semi-structured datasets. - Utilize natural language processing and probabilistic modeling to extract data from maintenance records. - Develop Physics-informed models based on the known relationships of signals for systems with low historical data available. - Implement algorithms for anomaly detection, predictive modeling, and trend analysis in operational data. - Support model validation, performance evaluation, and documentation. - Contribute to the deployment of models into production and embedded environments in coordination with engineering teams. - Collaborate with data visualization and software teams to integrate model outputs into dashboards and decision-support tools. - Document methodologies, assumptions, and results for technical and non-technical stakeholders. - Stay current with emerging machine learning techniques and apply best practices to ongoing projects. - Ability to support travel or off-site work, as needed - Perform other duties as assigned. Required Qualifications - Master’s degree in Data Science, Computer Science, Engineering, Applied Mathematics, or a related field with 4+ years of experience, or Bachelor’s degree in a related field with 6+ years of relevant experience (or equivalent experience in lieu of a degree). - Proficiency in Python for data analysis and machine learning. - Experience with common machine learning libraries (e.g., scikit-learn, PyTorch, TensorFlow, or similar). - Experience with natural language processing techniques and toolchains. - Familiarity with time-series data, telemetry, or sensor-based datasets. - Working knowledge of data analysis tools such as NumPy, Pandas, and SciPy. - Ability to communicate technical concepts clearly in both written and verbal form. - Strong analytical thinking and problem-solving skills. - Must be a U.S. Citizen with the ability to obtain and maintain a security clearance. Preferred Qualifications - Experience applying machine learning to predictive maintenance, health monitoring, or operational analytics on time-series data systems. - Experience applying advanced techniques to extract meaningful data from bulk maintenance records to inform future maintenance actions. - Exposure to model deployment concepts (e.g., batch pipelines, APIs, or edge/embedded environments). - Familiarity with cloud platforms or big data environments. - Experience working in a government or DoD context. - Familiarity with the relationship between engine signals and performance. - Knowledge of version control (e.g., Git) and collaborative development workflows. Pay Information Full-Time Salary Range: $78,900 - $187,200 Please Note: Actual compensation offered will be determined based on several factors including, but not limited to, relevant experience, skills, education, certifications, internal equity, business considerations, and geographic location where applicable. Benefits Hired applicants may be eligible for benefits including but not limited to: - Health benefits - Medical - Dental - Vision - Basic life with AD&D - Short term disability - Long term disability - Ancillary (Voluntary life with AD&D, accident, critical illness, hospital, and pet) - Spending accounts (HSA, FSA, and DCFSA) - Paid time off - Holidays - 401(k) (including company match) - Tuition reimbursement - Leaves (Parental, maternity, and military) - Annual discretionary bonus (for eligible roles) - Potential annual bonus Trident Systems reserves the right to change or assign other duties to this position. Trident Solutions is an affirmative action and equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state or local laws. To request reasonable accommodation to participate in the job application or interview process, please contact recruiting@tridsys.com. Pay Transparency: The contractor will not discharge or in any other manner discriminate against employees or applicants because they have inquired about, discussed, or disclosed their own pay or the pay of another employee or applicant. However, employees who have access to the compensation information of other employees or applicants as a part of their essential job functions cannot disclose the pay of other employees or applicants to individuals who do not otherwise have access to compensation information, unless the disclosure is (a) in response to a formal complaint or charge, (b) in furtherance of an investigation, proceeding, hearing, or action, including an investigation conducted by the employer, or (c) consistent with the contractor’s legal duty to furnish information. 41 CFR 60-1.35(c)
Central Business Solutions, Inc (A Certified Minority Owned Organization) Address: 37600 Central Court Suite 214 Newark CA, 94560 Phone: (833) 247-8800 Fax: (510) 740-3677 Web: www.cbsinfosys.com Checkout our excellent assessment tool: www.skillexam.com Checkout our job board: www.job-360.net
Role Description Client is seeking a senior SAP PP/DS Solution Architect to lead end-to-end design and delivery of a complex production planning and scheduling solution. The role is onsite-leading and offshore-collaborating, requiring strong client stakeholder management. The ideal candidate is a hands-on architect with deep scheduling and optimizer experience and a track record of leading customer-facing engagements. Primary location is Nashville, TN with occasional travel to Bath, NY and Green Bay; remote with flexibility is acceptable for the right candidate. - Own end-to-end PP/DS solution design and delivery; lead the solution from onsite. - Drive PP/DS configuration across scheduling, heuristics, and optimizer-based planning. - Manage senior client stakeholders, facilitate workshops, and ensure alignment on solution direction. - Collaborate closely with offshore delivery team to translate design into execution. - Govern integration to surrounding SAP modules and external optimization tooling where applicable. Qualifications - 12–15 years of planning experience. - 2–3 full-lifecycle PP/DS implementations as Architect or Lead. - Very strong PP/DS scheduling and optimizer expertise. - Exceptional client communication and stakeholder management; ability to lead the solution from onsite. Requirements - Hands-on experience with third-party optimization tools (e.g., Gurobi). - Exposure to SAP BTP landscape.
• Own the end-to-end analytics lifecycle for leadership and key stakeholders, ensuring high-impact reporting is delivered on schedule. • Serve as the primary analytics lead for top-tier client requests, acting as a consultant to design solutions that address complex healthcare business challenges. • Establish and uphold data integrity standards by leading peer code reviews and providing expert guidance on SQL optimization and complex logic validation. • Oversee the reporting roadmap and project lifecycle via Jira and Confluence, ensuring transparent communication of project statuses. • Translate dense healthcare findings into compelling narratives and presentations that bridge technical complexity with business-critical decision-making. • Lead high-priority routine and ad-hoc analyses, including internal and external audits, delivering insights within accelerated timeframes. • Identify bottlenecks in the data lifecycle and partner with Data Engineering and Data Architecture teams to develop automated, scalable solutions. • Approximately 60% writing SQL and/or Looker code for reporting and custom analyses, 20% collaborating with team members, and 20% communicating results to stakeholders.
The LDES Council is a global non-profit with over 60 members in 20 countries to accelerate #LDES technologies.
• Conduct fast-paced quantitative analyses in response to pollution episodes, energy market developments and other policy-relevant events, identifying impactful and policy-relevant findings. • Integrate, clean and analyse diverse proprietary, in-house and open datasets. • Produce reproducible code, robust methodology documentation, and reusable datasets. • Develop clear and effective data visualisations that communicate analytical insights. • Support research by combining quantitative analysis with domain expertise and desk research. • Develop new datasets, analytical tools and data products to strengthen CREA's research capabilities. • Work closely with colleagues to shape research questions and identify the most important analytical findings. • Contribute to reports, briefings and other research outputs by ensuring analyses are robust, transparent and reproducible.
• Responsible for mining big data, interpreting and analyzing complex data sets • Develops and deploys predictive models to analyze company performance and improve customer experiences • Applies statistical techniques and machine learning algorithms to identify trends within Mazda data • Collaborates closely with data engineers, analysts, and business stakeholders to integrate data-driven solutions
Rootshell Enterprise Technologies Inc. is a recognized provider of professional IT Consulting services in the US.
Role Description We are actively seeking a Data Scientist, Senior-Enterprise DS & AI Org for one of our clients. The role is remote and only available for W2 candidates. - Computer vision model experience is a must. A detailed write-up on experience with computer vision models is required. - Ability to synthesize complex information into clear insights and translate those insights into decisions and actions. - Demonstrated ability to explain technical concepts including but not limited to: - Statistical inference - Machine learning algorithms - Software engineering - Model deployment pipelines - Competency in the mathematical and statistical fields that underpin data science. - Ability to develop, coach, and teach career-level data scientists in data science, artificial intelligence, and machine learning techniques and technologies. - Strong in Python & R. Qualifications - Minimum: Bachelor's degree in Data Science, Machine Learning, Computer Science, Physics, Econometrics, Economics, Engineering, Mathematics, Applied Sciences, Statistics, or equivalent field. - Desired: Master's degree in one of the above areas. Requirements - Minimum: 4 years in data science (or 2 years if possessing a master's degree). - Demonstrated knowledge of and abilities with data science standards and processes (model evaluation, optimization, feature engineering, etc.) along with best practices to implement them. - Competency in software engineering, statistics, and machine learning techniques as they apply to data science deployment. - Competency in commonly used data science and/or operations research programming languages, packages, and tools. - Hands-on and theoretical experience of data science/machine learning models and algorithms. - Mastery in systems thinking and structuring complex problems. - Desired: experience building computer vision models. - Desired: experience with AWS technologies (S3, GroundTruth, Sagemaker). Company Description Rootshell Enterprise Technologies Inc. is a recognized provider of professional IT Consulting services in the US.
• Support clients across the alternative investment industry through project-based engagements. • Provide expert advice to Alternative Asset Firm and Family Office clients. • Develop data infrastructure, tools, and analysis to enhance investment processes. • Advise on vendor selection and oversight. • Create and implement policies, procedures, and control measures. • Analyze and evaluate client advancements towards goals through KPIs.
• Assist in developing, testing, and improving machine learning and AI models. • Support data collection, preparation, transformation, and analysis activities. • Participate in experiments and evaluations to identify opportunities for model improvement. • Collaborate with product, engineering, and analytics teams on AI-enabled solutions. • Create reports, dashboards, and visualizations that communicate findings and insights. • Contribute to documentation, presentations, and knowledge sharing within the team. • Learn and apply best practices in machine learning, software development, and data science. • Stay current on emerging AI, machine learning, and generative AI technologies.
• Design the Future of Ads Identity: Develop/employ probabilistic models for identity resolution. Design the methodology that links on-platform and off-platform actions to maximize addressability while honoring privacy. • Advance Lift Methodologies & Experimentation: Own the statistical rigor behind Reddit’s Brand and Conversion Lift products. Innovate experimental design and develop infrastructure that supports large-scale, high-velocity, low-bias testing for advertisers. • Maximize Signal for Predictive Performance: Define the strategy for new signal sources. You will mathematically quantify the value of these signals and work with modeling teams to incorporate them into predictive models, directly improving bidding efficiency and ROAS. • Define Ground Truth & Evaluation Frameworks: Solve the industry-wide challenge of validating identity and measurement. Design the objective functions and truth sets used to train our models and measure the incremental impact of our identity graph. • Lead Through Cross-Functional and Technical Influence: Collaborate deeply with engineering, product, and sales to align on strategic goals, translate insights into action, and drive execution. Set a high technical bar by mentoring others and championing best practices across modeling, experimentation, and measurement.
• Define the long-term data science vision & strategy across ads measurement, signal quality, identity, attribution, and privacy. Establish how Reddit should evaluate advertiser value, measurement quality, and signal utility across first-party and third-party products. • Define the long-term data science strategy across ads measurement, signal quality, identity, attribution, and privacy. Establish how Reddit should evaluate advertiser value, measurement quality, and signal utility across first-party and third-party products. • Create rigorous frameworks for validating lift, attribution, identity quality, modeled conversions, signal loss recovery, and privacy-aware measurement. Define ground truth, objective functions, quality metrics, guardrails, and decision frameworks that guide product and engineering investments. • Lead the evolution of Reddit’s experimentation and lift methodologies across Brand Lift, Conversion Lift, Split Testing, and emerging measurement products. Improve study quality, reduce bias and contamination, and develop scalable diagnostics for experiment health, feasibility, and interpretability. Partner with Ads Engineering to operationalize complex causal models, ensuring that scientific methodologies are not only accurate but also performant, scalable, and resilient in high-throughput production environments. • Quantify how signal quality, match rates, identity resolution, modeled conversions, and privacy changes affect bidding efficiency, CPA, ROAS, and advertiser outcomes. Partner with modeling and ranking teams to translate measurement improvements into performance gains. • Lead a privacy-first measurement paradigm, positioning Reddit as a market leader in trusted advertising by recovering signal utility through compliant modeling. • Lead cross-org efforts to define reusable methodologies, dashboards, scorecards, quality metrics, and best practices. Build repeatable systems that improve how Ads DS evaluates launches, monitors regressions, sizes opportunities, and communicates impact. • Partner with senior leaders across Product, Engineering, Sales, Marketing Science, Legal/Privacy, and Ads leadership to shape roadmap decisions. Translate complex scientific tradeoffs into clear business and product recommendations. • Mentor Staff and Senior data scientists, sponsor high-impact technical work, and raise the bar for causal inference, measurement science, identity evaluation, data quality, and cross-functional decision-making across Ads DS.
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Python, SQL, AI/ML, AI, PyTorch, Pandas
