Engineer

At IKS, we are a forward-thinking technology company at the forefront of AI innovation. Our mission is to leverage cutting-edge artificial intelligence to solve complex challenges and create intelligent solutions that redefine our industry. We are looking for a talented and driven Data Scientist to join our growing team.

As an AI Data Scientist, you will be a key hands-on contributor to our AI initiatives. You will be responsible for designing, developing, and deploying machine learning models that solve critical business problems. This role requires a strong foundation in data science, a passion for AI, and the ability to turn data into impactful products and insights. You will work collaboratively with a team of scientists and engineers to bring innovative AI solutions to life.

1. Advanced Model Development: Design, build, train, and validate state-of-the-art AI models, with a special focus on Deep Learning, Natural Language Processing (NLP), and Generative AI (including LLMs).


2. Data Analysis & Preprocessing: Perform in-depth data exploration, analysis, and feature engineering on large, complex datasets to prepare them for modeling.


3. Problem Formulation: Work with stakeholders to understand business problems and translate them into well-defined data science projects.


4. Collaboration: Partner closely with AI engineers, product managers, and other data scientists to deploy models into production and integrate them into our products.


5. Model Validation & Iteration: Rigorously test and evaluate models for performance, fairness, and robustness. Continuously iterate and improve model performance over time.


6. Innovation & Research: Stay current with the latest advancements in AI and machine learning. Apply new techniques and research to solve business challenges.


7. Communicate Insights: Clearly communicate complex findings and the value of your work to both technical and non-technical stakeholders.

• Educational Background: Master s degree in Computer Science, AI, Statistics, or a related quantitative field.


• Professional Experience: 3+ years of hands-on experience in building and deploying data science and machine learning models.


• Technical Expertise:


• Strong expertise in machine learning, deep learning, NLP, and statistical modeling.


• High proficiency in Python and common AI/ML libraries (e.g., PyTorch, TensorFlow, Scikit-learn, Hugging Face, Pandas).


• Experience with data querying languages (e.g., SQL).


• Problem-Solving: Excellent analytical and problem-solving skills with a creative and curious mindset.


• Communication: Strong verbal and written communication skills.

• Experience with large-scale data processing frameworks like Apache Spark.


• Hands-on experience with a major cloud platform (e.g., AWS, GCP, Azure).


• A portfolio of data science projects (e.g., via GitHub, Kaggle).


• Experience working in a fast-paced, product-driven tech environment.