Job Title

Company DescriptionMoative, 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:We have built and sold two companies, one of which was an AI company. Our founders and leaders are Math PhDs, Ivy League University Alumni, Ex-Googlers, and successful entrepreneurs.Our Team:Our team of 20+ employees consist of data scientists, AI/ML Engineers, and mathematicians from top engineering and research institutes such as IITs, CERN, IISc, University of Zurich, Ph.Ds. Our team includes academicians, IBM Research Fellows, and former founders.Role DescriptionAs 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.