- Company Name
- JAKALA
- Job Title
- Data Scientist Senior Consultant
- Job Description
-
**Job Title**
Senior Data Scientist Consultant
**Role Summary**
Design, implement, and industrialize advanced forecasting solutions for clients in sectors such as Retail, Luxury, Media, Industry, and Finance. Lead technical modeling, data pipeline development, model evaluation, and deployment while translating results into actionable business insights.
**Expectations**
Deliver production‑ready forecasting models with high predictive accuracy. Collaborate closely with business stakeholders to define impactful use cases, maintain coding rigor and MLOps practices, stay abreast of emerging forecasting and MLOps technologies, and contribute to the growth of the forecasting service offering.
**Key Responsibilities**
- Conceive and deploy sophisticated time‑series forecasting models (ARIMA/SARIMA, Prophet, XGBoost, LSTM/GRU, hierarchical, transformer‑based, etc.).
- Build robust ETL pipelines for temporal data, ensure versioning, quality, and scalability in distributed environments.
- Establish rigorous evaluation frameworks (back‑testing, MAPE, WAPE, RMSE, MASE, etc.) and perform thorough validation.
- Optimize model performance, ensure robustness under production workloads, and manage end‑to‑end deployment using Python, MLflow, Docker, and CI/CD pipelines.
- Facilitate workshops, sketch data‑strategy roadmaps, and train stakeholders, converting technical findings into clear business recommendations.
- Produce internal and client POCs, refine forecasting offerings, and share knowledge across the team.
- Contribute to ongoing technology scouting in time‑series, foundation models, and MLOps.
**Required Skills**
- Proficiency in Python and ML/DL frameworks (scikit‑learn, PyTorch, TensorFlow).
- Deep expertise in time‑series forecasting techniques and related evaluation metrics.
- Strong SQL skills and experience with distributed data platforms (Spark, Databricks, Snowflake, etc.).
- MLOps experience: MLflow, Docker, CI/CD, model governance.
- Excellent communication, stakeholder engagement, and workshop facilitation abilities.
- Prior exposure to retail, luxury, media, industry, or finance data contexts is advantageous.
**Required Education & Certifications**
- Bachelor’s or Master’s degree in Computer Science, Statistics, Mathematics, or a related quantitative field.
- Professional certifications in data science or ML (e.g., AWS Certified Machine Learning, Google Cloud ML Engineer) are preferred.