- Company Name
- Seneca Resources
- Job Title
- Applied Analytics Engineer (Dallas or Birmingham, AL)
- Job Description
-
**Job Title:**
Applied Analytics Engineer
**Role Summary:**
Contract-to-hire Applied Analytics Engineer responsible for designing, building, and deploying advanced predictive models and scalable data pipelines in a cloud-based big‑data environment. Works cross‑functionally to convert raw data into actionable insights, integrating machine learning, statistical analysis, and AI solutions into enterprise decision‑making processes.
**Expectations:**
- Deliver end‑to‑end analytics solutions, including model development, validation, deployment, and monitoring.
- Build and maintain robust, automated data pipelines that ingest, cleanse, and transform large structured and unstructured datasets.
- Collaborate with data engineers, analysts, and business stakeholders to translate business problems into data solutions.
- Adhere to best practices in MLOps, CI/CD, and documentation to ensure maintainable, production‑ready analytics products.
**Key Responsibilities:**
1. **Model Design & Validation** – Develop regression, classification, clustering, ensemble, NLP, and prescriptive models; conduct hypothesis testing and experimental design.
2. **Data Engineering** – Create scalable pipelines using Python, SQL, PySpark, Apache Spark, and cloud services (AWS/Azure/GCP).
3. **Feature Engineering & Preprocessing** – Clean, transform, and enrich data, ensuring high‑quality inputs for modeling.
4. **Pipeline Automation** – Implement automated workflows for data ingestion, transformation, and model deployment.
5. **Stakeholder Collaboration** – Partner with cross‑functional teams to specify analytics requirements and present insights.
6. **MLOps & Lifecycle Management** – Deploy models to production, monitor performance, and manage version control (Git) and CI/CD pipelines.
7. **Innovation & Knowledge Sharing** – Evaluate and integrate emerging technologies such as LLMs, LangChain, and AI‑powered tools; contribute to analytics platform improvements.
**Required Skills:**
- 5+ years in data science, ML engineering, or advanced analytics.
- Proficient in Python (NumPy, Pandas, Scikit‑learn, PySpark) and SQL.
- Experience with cloud platforms (AWS, Azure, GCP) and big‑data frameworks (Apache Spark).
- Strong data exploration, cleaning, feature engineering, and visualization skills.
- Familiarity with BI tools (Tableau, Power BI).
- Hands‑on with MLOps: model serving, monitoring, CI/CD pipelines.
- Version control (Git); basic knowledge of JIRA, ServiceNow, or similar tools.
**Required Education & Certifications:**
- Bachelor’s degree in Computer Science, Statistics, Mathematics, Data Science, or related field (or equivalent work experience).
- Optional certifications: Certified Data Scientist (CDS), AWS Certified Machine Learning – Specialty, GCP Professional Data Engineer, or similar credentials are a plus.
Birmingham, United states
On site
Mid level
12-03-2026