Syren Technologies - Data Scientist

Job Title: Data Scientist

Location: Hyderabad (Hybrid, Remote)

Job Type: Full-time

Experience Level: 3-6 Years

Responsibilities:

Feature Engineering and Data Preprocessing:

- Work with raw data to perform data cleaning, transformation, and feature engineering to prepare datasets for analysis.

- Collaborate with cross-functional teams to gather and understand data requirements.

Model Deployment and Monitoring:

- Maintain, optimize, and scale recommendation engines used in FMCG or consumer goods environments to ensure high availability, accuracy, and low-latency performance across channels.

- Continuously improve recommendation models using advanced ML techniques such as collaborative filtering, content-based filtering, matrix factorization, and hybrid recommender systems Model.

Collaboration and Communication:

- Collaborate with product, marketing, and engineering teams to integrate recommendations into consumer - facing applications, personalization engines, or B2B retail platforms.

- Communicate complex findings and insights in a clear and understandable manner to both technical and non - technical stakeholders.

Continuous Learning and Research:

- Stay abreast of industry trends and advancements in data science and machine learning.

- Continuously enhance skills through training and self-directed learning.

Qualifications:

Education and Experience:

- Bachelor's or master's degree in computer science, Statistics, or a related field.

- Proven experience as a Data Scientist.

Technical Skills:

- Strong proficiency in Python for data analysis, statistical modeling, and machine learning (e.g., pandas, scikit-learn, statsmodels, NumPy).

- Hands-on experience in developing recommendation engine & Graph embedding algorithms like GraphSAGE.

- Hands-on experience on handling Large Dataset using Azure Databricks and Azure Cloud is must.

- Strong understanding on Model Evaluation parameters.

- Experience with machine learning frameworks (e.g. PyTorch, scikit-learn).

- Strong knowledge of statistical analysis and data visualization tools.

Problem-Solving:

- Ability to translate business problems into analytical frameworks and develop data-driven solutions.

Communication Skills:

- Strong interpersonal and communication skills with the ability to explain complex concepts to non-technical stakeholders.

Team Collaboration:

- Demonstrated ability to work effectively in a collaborative team environment.