Experienced Data Scientist

Company Description

Moative, an Applied AI company, designs and builds transformation AI solutions for traditional industries in energy, utilities, healthcare & lifesciences, and more. Through Moative Labs, we build AI micro-products and launch AI startups with partners in vertical markets that align with our theses.

Our Past:

Our Team:

Role Description

As a data scientist, you will lead data-driven projects, design and develop advanced analytical frameworks and AI/ML solutions to address business problems. You will collaborate with product managers, engineers and domain experts to deliver intelligent solutions and products. You’ll analyze new opportunities and ideas, evaluate new Al/ ML models/ frameworks/ platforms , conduct experiments, develop PoCs and prototypes.

As a Data Scientist, you will provide your advanced expertise on statistical and mathematical concepts and guide the team in AI/ML algorithms and model development. You will stay up-to-date with the latest advancements in data science and machine learning, and AI.

The ideal candidate will have a strong background in statistics, machine learning, and programming, as well as excellent business understanding and product design thinking skills. If you are passionate about data and have a proven track record of delivering impactful data solutions, we would love to hear from you.

Qualifications

• 3 - 5 years of experience in applying data science methods to develop models that extract business value from real-world data.
• Deep familiarity with a range of data science methods and algorithms (time-series analysis, regression analysis, experimental design, optimization, etc.)
• Strong understanding of ML algorithms including areas such as deep learning, NN, NLP, and more.
• Experience with AI foundational models and associated architectural and solution development frameworks
• Proficient Knowledge of cloud platforms (e.g., AWS, Azure, GCP), ML frameworks (e.g., TensorFlow, PyTorch) and MLOps practices and platforms like MLflow.
• Broad understanding of data structures, data engineering and architectures.
• Strong communication skills and teamwork.
• Strong interpersonal skills, result-oriented, self-motivated, proactive, and capable of handling multiple projects.
• Ability to work in collaborative settings, take accountability, and stay composed under stress.