Data Scientist | Machine Learning Engineer | Predictive Analytics Specialist

Mike Jarde

Professional Summary

Data Scientist with strong foundation in predictive modeling, product analytics, and machine learning. Proven track record building scalable data solutions using Python, SQL, and cloud platforms. Passionate about deploying data products that drive measurable business impact.

Work Experience

MIT DS & AI Fellowship Projects at MIT CSAIL + Sloan School of Management

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• Built 20+ DS/ML projects end-to-end including ETL, modeling, and visualization. • Used Python and SQL for production models; deployed pipelines with Airflow and MLflow. • Collaborated with mentors to translate ambiguous business questions into measurable outcomes.

Social Analytics Manager at Social Hive (YC-backed, Boston)

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• Analyzed multi-channel campaign data via Amplitude and Tableau to optimize engagement. • Ran A/B tests with Optimizely, boosting CTR by 18% across key landing pages. • Led content tagging pipeline design and automated reporting with pandas and Google Sheets API.

Freelance Data Tutor at InsightPrep

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• Taught Python, statistics, and ML to pre-college and adult learners. • Created interactive visualizations in Jupyter and Dash to explain regression concepts.

Growth Analytics Associate at Frost & Sullivan

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• Led segmentation and targeting model increasing ecommerce client ROI by 22%. • Cleaned CRM data in Snowflake; built logistic models with sklearn. • Designed uplift modeling strategy; tested targeting via A/B tests. • Developed Frost Radar tool aggregating 50,000+ companies; automated ranking and visualized in Tableau.

Economic Research Intern at Arcadia Analytics

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• Modeled housing disparity using U.S. Census data and spatial regressions in R. • Built OLS and SEM models; mapped patterns with LISA plots and choropleth maps.

Investment Research Intern at Shoreline Capital Partners

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• Evaluated CAPEX-adjusted investment risk via sectoral regression models. • Conducted macroeconomic stress testing and exposure simulations.

Policy Analyst Intern at Public Sector Strategies

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• Analyzed state infrastructure plans; built interactive Tableau dashboards. • Modeled stimulus spillover using cluster logic and regional indicators.

Education

Executive PG Program in Data Science in ML Modeling, Tree Ensembles, Experimental Design, Explainability

MIT Sloan

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Advanced Certificate in AI & DS in Deep Learning, NLP, Time Series, MLOps, Model Interpretability

MIT CSAIL

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B.A. Economics (Honors) in Econometrics, Mathematical Stats, Game Theory

Boston College

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Skills

Technical Skills

  • Python
  • SQL
  • R
  • VBA
  • scikit-learn
  • XGBoost
  • LightGBM
  • pandas
  • NumPy
  • matplotlib
  • seaborn
  • TensorFlow
  • PyTorch

Certifications

Google Data Analytics

Coursera

AWS Certified Cloud Practitioner

dbt Fundamentals

Responsible AI

Microsoft

Score
85/100
Header
90/100
Certifications
70/100
Skills
90/100
Profile
88/100
Projects
80/100
Work Experience
82/100
Education
75/100
Add consistent date formatting and employment types in work experience for clarity and ATS parsing.
Include start dates and completion status for education and certifications to improve completeness.
Enhance project descriptions with business outcomes and provide links to portfolios or code repositories.
Group skills into categories and add soft skills to balance the technical focus.
Expand certifications section with issuing authorities and dates, and add brief descriptions.
Strong technical proficiency across a wide range of data science and machine learning tools and frameworks.
Quantified achievements in work experience demonstrating measurable business impact.
Clear and focused professional headline and summary that incorporate key industry terms.
Experience with cloud platforms and deployment tools, indicating readiness for production environments.

Header

90%
Header includes full name, professional headline with relevant keywords, and clear contact information, which aids ATS parsing.
Add a location with city and state explicitly in a single line to improve geo-targeting by ATS.
Consider including a professional title or certification acronyms after the name for added clarity.

Certifications

70%
Certifications listed are relevant and add credibility, especially cloud and data analytics credentials.
Include issuing authorities and dates awarded consistently for all certifications.
Add brief descriptions or skills gained for each certification to show their relevance.
Consider adding more industry-recognized certifications if available to strengthen this section.

Skills

90%
Comprehensive list of hard skills and tools relevant to data science and machine learning, optimized for ATS keyword scanning.
Consider grouping skills into categories (e.g., Programming Languages, Machine Learning Frameworks, Cloud Platforms) for easier readability.
Add some soft skills to balance technical expertise with interpersonal abilities.

Profile

88%
Summary is concise and includes strong keywords like 'predictive modeling', 'machine learning', and 'cloud platforms' that ATS systems look for.
Profile highlights quantify achievements and specify tools, which improves both ATS and recruiter appeal.
Consider adding a brief objective or value proposition statement to clarify career goals.

Projects

80%
Projects demonstrate application of advanced modeling techniques and deployment, which is valuable for technical roles.
Descriptions include technical details and metrics but could be enhanced by stating business impact or outcomes more explicitly.
Add dates or timeframes to projects to show recent activity and progression.
Include links to project repositories or demos to improve recruiter engagement.

Work Experience

82%
Descriptions include relevant technical skills, tools, and quantifiable impacts, enhancing ATS keyword matching and recruiter interest.
Use consistent formatting for dates (e.g., month and year) and consider adding employment types for clarity.
Some job descriptions could better highlight leadership or collaboration skills and business outcomes.
Add metrics consistently across all roles to demonstrate impact, e.g., 'improved model accuracy by X%' or 'reduced processing time by Y%'.

Education

75%
Education section includes prestigious institutions and relevant fields of study, which is positive for ATS and recruiters.
Missing start dates and GPA may reduce completeness; consider adding these details if available.
Clarify if ongoing programs or expected graduation dates to indicate current learning efforts.
Include any honors, awards, or relevant coursework explicitly to strengthen this section.