Job Description
Are you ready to shape the future of AI?
Nexus Analytics is on the lookout for a visionary Senior Data Scientist to join our elite R&D team. We are building the next generation of predictive intelligence platforms that drive decision-making for Fortune 500 clients. If you thrive in a fast-paced, high-impact environment and have a passion for turning complex datasets into actionable insights, we want to meet you.
In this role, you will not just analyze data; you will architect solutions that redefine industry standards. You will work closely with cross-functional teams of engineers, product managers, and designers to build scalable machine learning models that solve real-world problems.
Why Join Us?
- Impactful Work: Your algorithms will directly influence business strategies and user experiences.
- Top-Tier Team: Collaborate with world-class engineers and researchers.
- Competitive Package: Comprehensive benefits, equity, and continuous learning opportunities.
Responsibilities
- Model Development & Deployment: Design, develop, and deploy scalable machine learning models and statistical algorithms using Python and modern frameworks (TensorFlow, PyTorch).
- Data Engineering: Extract, clean, and transform massive datasets from various sources to ensure high data quality and integrity.
- Feature Engineering: Develop innovative feature extraction techniques to improve model accuracy and predictive power.
- Stakeholder Collaboration: Translate complex technical findings into clear, compelling insights for non-technical stakeholders and executive leadership.
- Research & Innovation: Stay at the forefront of AI research, experiment with new techniques (NLP, Computer Vision), and implement them in our production environment.
- Mentorship: Guide junior data scientists and data engineers, fostering a culture of technical excellence and continuous improvement.
Qualifications
- Education: Master’s or Ph.D. in Computer Science, Statistics, Mathematics, or a related quantitative field.
- Experience: 5+ years of professional experience in data science, machine learning, or a related role.
- Technical Skills: Strong proficiency in Python (Pandas, NumPy, Scikit-learn), SQL, and Big Data technologies (Spark, Hadoop).
- Modeling: Deep experience with deep learning frameworks and experience deploying models via cloud platforms (AWS, GCP, or Azure).
- Communication: Exceptional ability to communicate complex data concepts to diverse audiences.
- Problem Solving: Proven track record of tackling ambiguous problems and delivering robust solutions under tight deadlines.