AI/ML Data Scientist II- Remote, USA

Compensation: $120,000-$140,000 per year. You are eligible to a Short-Term Incentive Plan with the target at 7.5% of your annual earnings, terms and conditions apply.   AI/ML Data Scientist II -Remote, USA     This position is focused on applying advanced data science, AI, and machine learning techniques to solve complex research and business problems at the intersection of clinical genomics testing and computational biology. You will join a dynamic team that explores cutting-edge AI/ML techniques, including large language models (LLMs), to drive process modernizations and automations for business operations as well as R&D bioinformatics workflows. The primary focus of this role is on the development and implementation of AI/ML models to streamline business processes, improve efficiency, and drive innovation. While bioinformatics knowledge is beneficial, the core responsibilities center around data science and machine learning applications across diverse datasets.   Essential Functions

• Design and implement advanced machine learning models, statistical methods, and predictive algorithms to address business and research challenges
• Conduct exploratory data analysis (EDA), feature engineering, and data preprocessing to uncover insights, trends, and patterns in complex, large-scale datasets
•  Work with a cross-functional team to integrate machine learning and AI models into operational workflows, business systems, and research applications
• Contribute to the development of automated tools and systems that support clinical, genomic, and other research applications, facilitating process improvements  and decision-making
•  Leverage state-of-the-art AI/ML techniques, including large language models (LLMs), to automate documentation, data processing, and other key business functions
• Collaborate with domain experts to understand the business and research objectives, translating them into scalable data science solutions
• Other duties as assigned 

  Qualifications

• PhD degree in Bioinformatics, Data Science, Machine Learning, Computer Science, Statistics, Biophysics, Computational Biology or a related discipline, with 2+ years of post-doctoral or industry experience.
• Alternatively, MS degree in a related field with 4+ years of industry experience
• Familiarity with bioinformatics concepts, molecular biology, and genomics is preferred, but not required.
• Strong expertise in data science and AI/ML methodologies, including supervised and unsupervised learning, deep learning, and natural language processing (NLP)
• Proficiency in Python, R, SQL, or similar programming languages used for data analysis and model development.
• Experience with machine learning frameworks (e.g., TensorFlow, PyTorch, Scikit-learn, XGBoost).
• Experience working with large language models (LLMs) and other advanced AI/ML models is a strong bonus.
• Proficiency in statistical analysis, data visualization, and the use of relevant tools (e.g., pandas, NumPy, Matplotlib, Seaborn)
• Familiarity with cloud-based services (AWS, GCP) and building end-to-end machine learning pipelines.
• Excellent written and verbal communication skills with the ability to clearly present technical results to non-technical stakeholders
• Ability to work both independently and collaboratively within multidisciplinary teams.
• 3+ years of experience in research or industry, applying data science and machine learning techniques to solve complex problems
• Proven track record of building and deploying machine learning models in real-world applications
• Experience in analyzing large and complex datasets, with a focus on data wrangling and feature engineering

  Preferred

• Experience with high-performance computing (HPC) and large-scale data processing frameworks (e.g., Spark, Dask) is a plus
• Familiarity with bioinformatics tools and techniques (e.g., Illumina sequencing data, NGS pipelines) is preferred but not required
• Familiarity with large-scale data platforms and cloud-based infrastructure (AWS, Azure, GCP) is a plus
• Experience with language models (LLMs) is a strong bonus
• Experience in working with clinical or biological data is preferred, but not mandatory 

  About Us:  

Ambry Genetics Corporation