Job Description
Are you ready to define the future of Artificial Intelligence and Big Data?
At Apex Analytica, we are looking for a visionary Senior Data Scientist to lead our cutting-edge analytics initiatives. In this role, you will transform complex datasets into actionable business strategies, driving growth and innovation across our global platforms. You will work in a collaborative environment with world-class engineers and product managers to build predictive models that matter.
Why Join Us?
- Work on high-impact projects that solve real-world problems.
- Access to state-of-the-art hardware and cloud infrastructure.
- Competitive compensation package with equity options.
The Role:
We are seeking a highly analytical individual to own the end-to-end data science lifecycle, from data ingestion and feature engineering to model deployment and monitoring.
Responsibilities
- Model Development: Design, train, and deploy complex machine learning and deep learning models using Python, TensorFlow, and PyTorch to solve business challenges.
- Big Data Processing: Ingest, clean, and process massive datasets using Spark and SQL to ensure high data quality for analysis.
- Feature Engineering: Identify and create meaningful features from raw data to improve model accuracy and performance.
- Collaboration: Partner with cross-functional teams (Product, Engineering, Marketing) to translate data insights into actionable product roadmaps.
- MLOps: Implement automated pipelines for model training and deployment, ensuring scalability and reproducibility.
- Communication: Present complex analytical findings to non-technical stakeholders in a clear, compelling manner.
Qualifications
- Education: Master’s or Ph.D. degree in Computer Science, Statistics, Mathematics, or a related quantitative field.
- Technical Skills: Strong proficiency in Python (Pandas, NumPy, Scikit-learn) and SQL.
- Experience: Minimum of 5+ years of experience in data science, machine learning, or a related analytical role.
- Frameworks: Proven experience with deep learning frameworks (TensorFlow, Keras, PyTorch) and big data tools (Hadoop, Spark).
- Statistical Analysis: Deep understanding of statistical methods, A/B testing, and experimental design.
- Certifications: AWS or GCP Data Science/AI certifications are a plus.