What are the responsibilities and job description for the Machine Learning Engineeri//Dearborn, MI//W2 position at Saanvi Technologies?
Machine Learning Engineering Engineer 1
Dearborn, MI
W2
Position Description
Please review ALL sections of this updated job description *****
Position Title: Launch Data Analyst / Statistical Analyst Primary Focus: Primary focus should be statistics, forecasting, and AI Assisted Analytics. Position Overview We're seeking a mid-level Launch Data Analyst who combines strong statistical modeling with practical data engineering and AI-assisted analytics. You'll translate historical launch data into robust metrics, trend forecasts, and risk analyses that inform key launch decisions. The role requires solid Python proficiency, the ability to build reproducible analytics, and the capacity to communicate complex methods and results to senior leaders. Position Duties - Statistical design and modeling Develop and maintain statistical models for launch metrics using historical data (time series, regression, causal inference when appropriate). Produce short- and medium-term forecasts (demand, adoption, risk indicators) and quantify forecast uncertainty. Apply causal analysis techniques when needed (e.g., differences-in-differences, propensity-score methods) to isolate effects. - Data collection, wrangling, and quality Ingest and clean data from Excel, SharePoint, databases, and cloud sources; implement reproducible data processing in Python. Validate data quality and document data lineage and assumptions. - AI-assisted analytics with guardrails Use AI tools to accelerate hypothesis generation, literature reviews, and exploratory analysis, while rigorously validating outputs and maintaining auditability. - Analytics automation and toolkit Build modular Python codebase to streamline repetitive tasks; modularize code for reuse; version control with Git. Create and maintain dashboards and reports (Power BI/Tableau) to communicate results to stakeholders. They will build and manage dashboards. - Insights communication and decision support Translate statistical findings into clear business recommendations; develop executive-ready presentations and summaries. - Provide actionable insights for launch planning, risk mitigation, and resource allocation. - Collaboration and governance Partner with tech team, product/launch teams, and leadership to align analyses with governance, privacy, and compliance standards. - Contribute to measurement plans and ensure analyses are reproducible and auditable.
Skills Required
For this Mid-Level Role - The minimum professional experience required for this role1-3 years' experience required in data analytics. Python and modeling skills requirement/minimum proficiency level - Candidates should be proficient to write code when needed with little guidance. Will consider strong candidates from other industries if they have relevant analytics experiences.
Experience Preferred
Automotive launch or manufacturing launch experience.
Education Required
Bachelor's degree in Statistics, Mathematics, Economics, Engineering, Computer Science, or related field
Education Preferred
Master's or higher degree preferred for deeper statistical focus and complex problem-solving skills.
Additional Safety Training/Licensing/Personal Protection Requirements
Additional Information :
Please review ALL sections of this updated job description ***** ***POSITION IS HYBRID / 4 days per week in office*** MLOps/DevOps familiarity (CI/CD, model deployment) is no longer part of the role.
Dearborn, MI
W2
Position Description
Please review ALL sections of this updated job description *****
Position Title: Launch Data Analyst / Statistical Analyst Primary Focus: Primary focus should be statistics, forecasting, and AI Assisted Analytics. Position Overview We're seeking a mid-level Launch Data Analyst who combines strong statistical modeling with practical data engineering and AI-assisted analytics. You'll translate historical launch data into robust metrics, trend forecasts, and risk analyses that inform key launch decisions. The role requires solid Python proficiency, the ability to build reproducible analytics, and the capacity to communicate complex methods and results to senior leaders. Position Duties - Statistical design and modeling Develop and maintain statistical models for launch metrics using historical data (time series, regression, causal inference when appropriate). Produce short- and medium-term forecasts (demand, adoption, risk indicators) and quantify forecast uncertainty. Apply causal analysis techniques when needed (e.g., differences-in-differences, propensity-score methods) to isolate effects. - Data collection, wrangling, and quality Ingest and clean data from Excel, SharePoint, databases, and cloud sources; implement reproducible data processing in Python. Validate data quality and document data lineage and assumptions. - AI-assisted analytics with guardrails Use AI tools to accelerate hypothesis generation, literature reviews, and exploratory analysis, while rigorously validating outputs and maintaining auditability. - Analytics automation and toolkit Build modular Python codebase to streamline repetitive tasks; modularize code for reuse; version control with Git. Create and maintain dashboards and reports (Power BI/Tableau) to communicate results to stakeholders. They will build and manage dashboards. - Insights communication and decision support Translate statistical findings into clear business recommendations; develop executive-ready presentations and summaries. - Provide actionable insights for launch planning, risk mitigation, and resource allocation. - Collaboration and governance Partner with tech team, product/launch teams, and leadership to align analyses with governance, privacy, and compliance standards. - Contribute to measurement plans and ensure analyses are reproducible and auditable.
Skills Required
- Statistics & modeling: Solid grounding in experimental design, regression (linear/logistic), time-series analysis, hypothesis testing, and interpretation of results in a business context. - Python proficiency: Proficient in Python (pandas, numpy, scipy, statsmodels, scikit-learn); able to write clean, modular, reproducible code that are ready to be integrated into application when needed; familiarity with Jupyter notebooks. - Data & tools: Strong SQL skills; experience with data visualization (Tableau, Power BI) and Excel for quick analyses. For BI tools (Power BI / Tableau), dashboard development is a core skill as they will build and manage dashboards. - AI-supported analysis: Comfortable using AI tools for research and problem-solving with rigorous validation of outputs. - Communication: Ability to explain complex methods to non-technical stakeholders; strong written and verbal communication; capable of producing executive-level dashboards and slides. - Time management: Proven ability to manage multiple priorities in a fast-paced environment; deliver insights within tight timelines. What Makes You Successful in This Role - Methodology with pragmatism: You design and defend robust analyses that drive tangible decisions, not just compute numbers. - Reproducibility and quality: You deliver clean, well-documented code and transparent data workflows. - AI-enabled, not AI-dominated: You leverage AI to accelerate insight, while maintaining control over validation, governance, and provenance. - Business acumen: You understand launch dynamics, constraints, and risks; you translate analytics into practical recommendations. - Collaboration: You communicate effectively with cross-functional teams and management.
- Automotive experience or domain knowledge in manufacturing or product launches. - Knowledge of additional languages or libraries (PuLP/OR-Tools) is a plus. - Familiarity with advanced forecasting or scenario analysis techniques and basic optimization concepts Ideal preference: experience building modular, version-controlled codebases.
For this Mid-Level Role - The minimum professional experience required for this role1-3 years' experience required in data analytics. Python and modeling skills requirement/minimum proficiency level - Candidates should be proficient to write code when needed with little guidance. Will consider strong candidates from other industries if they have relevant analytics experiences.
Experience Preferred
Automotive launch or manufacturing launch experience.
Education Required
Bachelor's degree in Statistics, Mathematics, Economics, Engineering, Computer Science, or related field
Education Preferred
Master's or higher degree preferred for deeper statistical focus and complex problem-solving skills.
Additional Safety Training/Licensing/Personal Protection Requirements
Additional Information :
Please review ALL sections of this updated job description ***** ***POSITION IS HYBRID / 4 days per week in office*** MLOps/DevOps familiarity (CI/CD, model deployment) is no longer part of the role.