Data Scientist

Apply now: Data Scientist, location is Hybrid (Tysons, VA). The start date is ASAP for this permanent position.

Job Title: Data Scientist

Location-Type: Hybrid (2-3 Days A Week On-site - Tysons, VA 22102)

Start Date Is: ASAP

Duration: Permanent/Direct Hire

Annual Base Salary Range: $130k - $140k

Job Description

Drive predictive modeling efforts to optimize sales outreach and increase advertising revenue, supporting a new sales-focused data science product initiative.

Day-to-Day Responsibilities:

• Own the full data science lifecycle: hypothesis framing, model development, testing, deployment, and impact analysis.
• Build predictive conversion models using advertiser data, sales history, and market signals.
• Engineer features from vendor-sourced, multi-channel advertiser datasets.
• Translate ML outputs into executive-facing dashboards and automated BI reports.
• Develop and validate classification models (e.g., logistic regression, gradient boosting, neural nets).
• Leverage Snowflake ML (e.g., Snowpark, Cortex ML) for scalable model prototyping and deployment.
• Conduct A/B testing and causal inference studies to measure business impact.
• Ensure model governance: tracking, drift detection, retraining, and documentation.
• Partner cross-functionally with sales, marketing, and product teams.
• Mentor peers on responsible AI, experimentation, and predictive analytics.

Requirements

• Must-Have Skills/Experiences:
• 5 years of applied data science experience, ideally in media or advertising.
• Strong Python (pandas, scikit-learn) and advanced SQL skills.
• Hands-on with Snowflake, including Snowpark and/or Cortex ML.
• Experience with model deployment, monitoring, and performance tuning.
• Expertise in classification modeling, especially in customer conversion or lead scoring.
• Ability to interpret and present ML insights to non-technical stakeholders.
• Experience working in enterprise environments and with offshore teams.
• Strong communication and collaboration skills.
• Nice-to-Have Skills/Experiences (NOT required, but a plus!) :
• Advanced degree in Data Science, Machine Learning, or related field.
• Prior experience in revenue-focused analytics (sales or marketing).
• Familiarity with MLOps and model pipeline automation.
• Experience with AWS (especially SageMaker).
• Background in fast-moving, AI-driven organizations.

About the Company:

Mondo