- Company Name
- Talkiatry
- Job Title
- Senior Data Scientist
- Job Description
-
**Job Title:** Senior Data Scientist
**Role Summary:**
Senior Data Scientist, individual contributor, leading end-to-end data initiatives for product, operations, and clinical teams. Responsibilities span growth analysis, experimentation, predictive modeling, and applied analytics to drive product strategy and operational efficiency.
**Expectations:**
- Deliver measurable business impact through data-driven insights.
- Actively uncover opportunities, anticipate stakeholder questions, and present findings in clear business terms.
- Balance advanced modeling with pragmatic solutions, ensuring statistical rigor and practical applicability.
- Communicate insights proactively to cross‑functional teams (Product, Engineering, Design, Operations, Clinical, Finance).
**Key Responsibilities:**
1. **Growth & Performance Analysis** – Identify product growth opportunities, analyze patient behavior, forecast retention, no‑shows, and demand patterns.
2. **Experiment Design & Evaluation** – Partner with teams to design A/B experiments, define success metrics, ensure statistical power, analyze results, and disseminate learnings.
3. **Predictive Modeling** – Build, evaluate, and productionalize models (scikit‑learn, statsmodels, etc.) for patient outcomes and operational metrics.
4. **Applied Analytics** – Lead analyses on clinician utilization, marketplace dynamics, and patient growth; create repeatable reporting frameworks.
5. **Collaboration & Data Quality** – Work with Data Engineering/BI to define data requirements, identify pipeline gaps, and maintain reliable data assets.
6. **Thought Leadership** – Shape questions for Ops, Clinical, and Finance leaders; provide strategic guidance on data-driven decisions.
**Required Skills:**
- 4+ years in data science, analytics, or related fields with a track record of business impact.
- Advanced proficiency in Python (pandas, scikit‑learn, statsmodels), SQL, and modern data warehouses (Snowflake, Redshift, BigQuery).
- Strong experimental design, causal inference, and statistical methodology background.
- Practical knowledge of ML trade‑offs; ability to choose between sophisticated models and simpler analyses.
- Excellent communication skills – translate technical findings into stakeholder‑friendly insights.
- Experience with DBT, product growth experimentation, or similar environments is a plus.
**Required Education & Certifications:**
- Bachelor’s (or higher) degree in Computer Science, Statistics, Mathematics, Engineering, or related quantitative field.
- Certifications in data science/analytics or statistical methods are advantageous but not mandatory.