About Fractal
Fractal is one of the most prominent providers of Artificial Intelligence to Fortune 500 companies. Fractal’s mission is to power every human decision in the enterprise. Fractal has more than 4000 employees across 16 global locations, including the United States, UK, Ukraine, India, Singapore, and Australia. Fractal has been consistently rated as India’s best companies to work for by Economic Times and has been recognized as a "Leader" in AI consulting by Forrester Research.
About the Team
As a Data Scientist, you will be a critical part of our AI & Engineering team, working with clients across various industries, including CPG, Retail, Financial Services, Insurance, Healthcare, and Life Sciences. You will be instrumental in solving complex business problems using state-of-the-art AI/ML techniques.
Responsibilities
- Design, develop, and deploy advanced machine learning models and algorithms to solve complex business problems.
- Analyze large datasets to extract actionable insights and identify trends.
- Collaborate with cross-functional teams to understand business requirements and translate them into technical solutions.
- Stay up-to-date with the latest advancements in AI/ML and explore new technologies.
- Communicate technical concepts and findings effectively to both technical and non-technical stakeholders.
- Mentor junior data scientists and contribute to a culture of continuous learning and improvement.
Requirements
- Education: Bachelor's or Master's degree in a quantitative field such as Computer Science, Statistics, Mathematics, Engineering, or a related discipline.
- Experience: 3-8 years of experience in Data Science or a related field.
- Technical Skills:
- Proficiency in programming languages such as Python or R.
- Strong understanding of machine learning algorithms (e.g., supervised, unsupervised, reinforcement learning).
- Experience with deep learning frameworks (e.g., TensorFlow, PyTorch, Keras).
- Familiarity with natural language processing (NLP), computer vision (CV), or generative AI techniques.
- Experience with MLOps practices and tools.
- Proficiency in SQL for data manipulation and extraction.
- Experience with big data technologies like Spark, Databricks, etc.
- Experience with cloud platforms (e.g., AWS, Azure, GCP).
- Familiarity with various ML libraries (e.g., Scikit-learn, XGBoost, LightGBM).
- Strong statistical modeling skills, including hypothesis testing and A/B testing.
- Soft Skills:
- Excellent communication and interpersonal skills.
- Strong problem-solving abilities and a keen eye for detail.
- Ability to work independently and collaboratively in a fast-paced environment.