Required Skills &

- Expertise Core Data Science &
- AI

- Strong hands-on expertise in Python, which is the primary language used for AI/ML development.

- Proven experience building production-grade AI/ML solutions using Python (NumPy, Pandas, Scikit-learn, SciPy).

- Solid foundation in statistics, probability, linear algebra, and optimization.

- Experience with machine learning techniques: regression, classification, clustering, time series forecasting, anomaly detection.

- Exposure to deep learning frameworks such as TensorFlow or PyTorch.

- Willingness and ability to learn and work with other programming languages (e.g., Java, Scala, SQL, or platform-specific languages) as required by enterprise platforms and integrations. Data &
- Platforms

- Experience working with SQL and NoSQL databases.

- Understanding of data pipelines, ETL/ELT processes, and feature engineering workflows.

- Hands-on exposure to cloud platforms (AWS and/or Azure) for data science and ML workloads.

- Familiarity with model deployment, monitoring, versioning, and MLOps practices. Engineering &

- Collaboration

- Robust coding practices, version control (Git), and reproducible experimentation.

- Ability to translate business problems into analytical and ML solutions.

- Comfortable working in multi-language, enterprise technology stacks,



with a Python-first mindset for AI/ML.

Strong collaboration skills across engineering, product, and business teams.

Preferred Certifications

- AWS Certified Machine Learning Specialty

- Microsoft Certified: Azure Data Scientist Associate

- Google Professional Machine Learning Engineer

- TensorFlow Developer Certificate (good to have)

- Certifications in AI, Data Engineering, or Cloud Architecture are a plus

Good-to-Have Skills

- Exposure to GenAI, LLMs, Vector Databases, RAG, and Prompt Engineering.

- Experience with real-time analytics, streaming data, or IoT data.

- Familiarity with enterprise domains such as supply chain, manufacturing, or operations analytics.

- Understanding of data governance, privacy, and responsible AI principles.

Ideal Candidate

Profile

- 5+ years of hands-on experience in data science and applied machine learning.

- Strong Python-based AI/ML implementation experience with real-world production exposure.

- Proven ability to take models from experimentation to production.

- Demonstrates learning agility and adaptability to evolving enterprise platforms and technologies.

- Passion for data, AI-driven problem solving, and continuous learning.

📌 Walk-in || Data Science Analyst (Bengaluru)
🏢 ARCIS e Services
📍 Bengaluru