- Company Name
- CapTech
- Job Title
- Machine Learning/Data Science Engineer
- Job Description
-
**Job Title:**
Machine Learning/Data Science Engineer
**Role Summary:**
Design, develop, and deploy scalable machine learning systems and data-driven solutions for enterprise clients. Lead cross‑functional teams, manage model production pipelines, and contribute to growth of the ML practice through client engagements and knowledge sharing.
**Expectations:**
- Deliver end‑to‑end ML solutions that meet business objectives.
- Translate complex client problems into data‑centric models and analytical metrics.
- Scale models to handle multi‑billion‑record datasets on cloud platforms.
- Lead and mentor junior data scientists/engineers.
**Key Responsibilities:**
- Collaborate with clients, data scientists, and engineers to define ML project scope and deliverables.
- Deconstruct business requirements into data‑driven processes, models, and evaluation measures.
- Analyze and transform large datasets stored in AWS, Azure, or GCP environments.
- Design, build, and deploy advanced analytics such as recommender systems, NLP models, and risk scoring engines.
- Productionize ML pipelines with focus on optimization, scalability, and reliability.
- Deliver client presentations, propose solutions, and support business development initiatives.
- Guide model versioning, governance, and continuous integration/continuous deployment (CI/CD) practices.
**Required Skills:**
- Proficiency in Python or Scala for data‑engineering and ML development.
- Experience with SQL, Spark, NoSQL, and cloud data processing frameworks.
- Containerization (Docker) and microservices architecture.
- Data warehousing expertise (Snowflake, Databricks, Azure SQL, Amazon RDS).
- Application of statistical modeling and ML algorithms across domains (customer analytics, marketing, finance, digital channels).
- Production‑scale ML system implementation (personalization, NLP, computer vision).
- DevOps and automation best practices, including CI/CD pipelines.
- Model management, versioning, and deployment best practices.
- Strong communication and problem‑framing skills across cross‑industry business contexts.
**Required Education & Certifications:**
- Bachelor’s degree in Computer Science, Data Science, Statistics, Engineering, or related field, or equivalent combination of education and experience.
- Relevant certifications (e.g., AWS Certified Machine Learning – Specialty, Azure ML Engineer Associate, Google Professional Data Engineer) are advantageous but not mandatory.