- Company Name
- Daintta
- Job Title
- Data Scientist
- Job Description
-
**Job Title**
Data Scientist
**Role Summary**
Lead data‑science initiatives for clients, driving projects from proof‑of‑concept to production. Develop scalable models, design robust pipelines, and communicate insights to stakeholders. Collaborate across multidisciplinary teams in an agile environment and provide subject‑matter expertise in data science, analytics, and engineering.
**Expectations**
- 5+ years of industry experience in data science (or related STEM field).
- Proven client‑delivery record in data science/engineering, analytics, security or intelligence.
- Strong consultative mindset, ethical data handling, and continuous professional growth.
- Excellent communication skills with the ability to explain complex concepts simply.
**Key Responsibilities**
- Lead client projects, assess business and technical needs, and identify data‑science opportunities.
- Manage end‑to‑end delivery: PoC → MVP → MMP, ensuring high‑quality, on‑time results.
- Build and maintain codebases using data‑science libraries, adhering to best‑practice design patterns.
- Design, evaluate, and deploy on‑premise, cloud (AWS, Azure, GCP) and hybrid ML solutions; oversee testing, risk mitigation, and monitoring.
- Conduct data exploration, feature engineering, and statistical analysis to uncover actionable insights.
- Present data stories to clients, translating technical findings into clear business recommendations.
- Support pitches, client presentations, and internal strategy sessions.
**Required Skills**
*Technical*
- Advanced proficiency in Python for data science (pandas, scikit‑learn, TensorFlow/PyTorch).
- Cloud‑native data‑science infrastructure (AWS, Azure, GCP).
- CI/CD pipelines for data workflows (Docker, Git, Jenkins/Travis/GitHub Actions).
- Database technologies: SQL, NoSQL (Elasticsearch, graph databases).
- Modeling of structured, semi‑structured, unstructured, time‑series, and image data.
- Knowledge of statistical methods, evidence‑based inference, and ML algorithm design.
*Soft*
- Strong interpersonal and stakeholder‑management skills.
- Ability to simplify complex concepts for diverse audiences.
- Ethical data‑handling mindset.
- Collaborative, adaptable, and proactive.
**Required Education & Certifications**
- Bachelor’s or Master’s degree in a STEM discipline (e.g., Computer Science, Statistics, Mathematics, Engineering).
- Relevant certifications (e.g., AWS Certified Machine Learning, Azure Data Scientist Associate, GCP Professional Data Engineer) are advantageous but not mandatory.
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