Senior Data Scientist

Evolv Technologies Inc. • Waltham, MA

2h • $129,000 - $209,000 • Onsite

About The Position

Join the Evolv Machine Learning & Sensors team as a Data Scientist focused on driving deep understanding of sensor data, feature spaces, and data quality that power our AI/ML systems. This hands-on role emphasizes representation analysis, exploratory data insights, and data-centric improvements that directly enhance model accuracy, robustness, and generalization. You will work across classical ML and deep learning pipelines to identify blind spots, diagnose data issues, and guide data curation and collection strategies.

Requirements

• Master’s or PhD in Data Science, Computer Science, Applied Mathematics, Statistics, Physics, or related field.
• 2-3+ years of data science experience working with real‑world ML datasets (time‑series, images, video, sensors).
• Proficiency in Python and data science libraries (NumPy, pandas, matplotlib, seaborn).
• Hands‑on experience using UMAP, t‑SNE, PCA, or other representation analysis methods.
• Experience analyzing data for both classical ML and deep learning models.
• Strong understanding of ML fundamentals and model evaluation methodologies.

Nice To Haves

• Experience with sensor or time‑series data (magnetic, radar, 3D, environmental, IoT).
• Familiarity with scikit‑learn workflows and preprocessing techniques.
• Experience addressing imbalanced datasets, label noise, and data drift.
• Knowledge of embedding analysis, feature importance, and model interpretability.
• Experience collaborating with annotation or data collection teams.
• Familiarity with MLOps or data versioning tools (MLflow, W&B, DVC).

Responsibilities

• Data Understanding & Representation Analysis: Analyze high‑dimensional sensor and feature data using UMAP, t‑SNE, PCA, and related techniques. Identify clusters, outliers, distribution gaps, and blind spots across classes and environments. Diagnose dataset shift, domain mismatch, sparsity, and representation collapse.
• Model‑Aware Data Analysis: Conduct data analysis aligned with both classical ML models (XGBoost, SVR, k‑NN, tree‑based models) and deep learning models (CNNs, Transformers). Analyze embeddings, confusion matrices, and failure cases to map model issues back to data causes.
• Data Quality & Curation: Investigate imbalanced data, noisy sensor signals, and mislabeled or ambiguous samples. Develop strategies for weakly labeled or unlabeled data using clustering or pseudo‑labeling. Define data quality metrics, acceptance criteria, and labeling strategies. Work with internal teams and external vendors to improve label consistency and coverage.
• Insight‑Driven Improvements: Translate exploratory insights into clear recommendations for data collection, relabeling, or filtering. Drive data‑centric improvements instead of relying solely on algorithmic changes. Track KPIs such as data quality, data quantity, collection rate, and utilization efficiency.
• Collaboration & Communication: Work closely with internal and external data collection teams to refine data pipelines. Communicate findings through visualizations, reports, and technical deep‑dives.

Benefits

• Equity as part of your total compensation package
• Medical, dental, and vision insurance
• Health Savings Account (HSA)
• A 401(k) plan (and 2% company match)
• Flexible Paid Time Off (PTO)- take the time you need to recharge, with manager approval and business needs in mind
• Quarterly stipend for perks and benefits that matter most to you
• Tuition reimbursement to support your ongoing learning and development
• Subscription to Calm

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level