- Company Name
- Amyantek
- Job Title
- Data Science Specialist
- Job Description
-
**Job title:** Intermediate Data Science Developer
**Role Summary:**
Design, develop, and deploy cloud‑based data and analytics solutions, including data lakes, lakehouses, ETL pipelines, predictive models, and visualizations. Work cross‑functionally with product, IT, and business partners to translate requirements into scalable, high‑performance solutions on Microsoft Azure (and other cloud platforms).
**Expectations:**
- 2–5 years of professional experience in data science, analytics, or a related quantitative field.
- Proven track record delivering end‑to‑end data products, from data ingestion to model deployment and reporting.
- Ability to clean, transform, and analyze large datasets; experience with production‑grade analytics workflows.
**Key Responsibilities:**
- Participate in product teams to gather requirements, architect solutions, and implement cloud‑based data products.
- Design, build, and maintain data lakes/lakehouses, automated data pipelines (Azure Data Factory, Databricks), and analytics models.
- Create dashboards and reports (Power BI, Tableau, Looker) for business users and stakeholders.
- Collaborate with IT and cluster teams to deploy, test, and troubleshoot solutions; resolve operational issues.
- Conduct knowledge transfer and document architecture, processes, and best practices.
- Communicate analytical insights and recommendations to non‑technical audiences.
**Required Skills:**
- **Programming & Data Handling:** Python (pandas, NumPy, scikit‑learn, statsmodels, matplotlib, seaborn), SQL (complex queries, joins, aggregations, optimization).
- **Data Engineering & Big Data:** Experience with Apache Spark, Hadoop, and cloud data services (Azure Data Lake, Azure Databricks, Azure Synapse).
- **Machine Learning & Statistical Modeling:** Supervised/unsupervised learning, model evaluation, cross‑validation, and basic deep‑learning familiarity.
- **Analytics & Visualization:** Power BI (preferred), Tableau or Looker; data storytelling and presentation skills.
- **Cloud & DevOps:** Azure (or AWS/GCP), version control (Git), CI/CD concepts, and API/ETL workflow knowledge.
- **Soft Skills:** Strong written and oral communication, teamwork, deadline adherence, problem‑solving, and knowledge‑transfer proficiency.
**Required Education & Certifications:**
- Bachelor’s degree (or equivalent experience) in Computer Science, Data Science, Statistics, Engineering, or related quantitative discipline.
- Optional certifications: Microsoft Azure Data Scientist Associate, Microsoft Certified: Data Analyst Associate, or equivalent.