Data Scientist

We are hiring - Data Scientist

About Client:

We are an innovative, stealth-mode startup at the forefront of applying next-generation AI to chemistry and scientific reasoning. As a sister concern of Laxai Life Sciences and working closely with our clients, we are uniquely positioned to revolutionize how groundbreaking molecules are discovered and developed, initially focusing on the pharmaceutical industry with broader ambitions in the materials space. The company is US-incorporated, with a significant part of the team in India.

Our team comprises seasoned experts from both the pharmaceutical and technology sectors, tackling significant technical challenges with the potential for substantial real-world impact. Our founders are Vamsi Maddipatla and Nivedita Ratakonda, both serial entrepreneurs. Vamsi is the founder of Laxai Life Sciences and group companies and has 20+ years of experience in the technology and biopharma industries. Nivedita is a tech entrepreneur and Stanford graduate, a repeat founder with 20+ years of experience. Our advisors are seasoned experts in the pharmaceutical space: Dr. Abigaile Doyle of UCLA and Dr. John Dillon. The founders and advisors are all based in the US.

We are developing the cutting edge of applied AI and scientific automation and are in an exciting phase of growth. We are looking for talented individuals to join us who can thrive in a fast-paced, agile startup environment, working towards a bold vision of a moonshot.

Role Summary:

As a Data Scientist, you will be an instrumental part in building client's AI product. The role is pivotal in driving innovation, integrating AI/ML methodologies, and fostering collaboration across interdisciplinary teams to achieve organizational goals in pharmaceutical development.

Key Responsibilities:

● Platform Development

- Develop and enhance AI-powered prediction models to predict and optimize chemical formulations.

- Collaborate with software engineers to integrate advanced computational models into the AI platform.

● Data Analytics and Modeling

- Analyze large datasets from chemistry data and R&D experiments to uncover patterns, trends, and optimization opportunities.

- Develop and validate statistical and machine learning models to improve prediction accuracy and reliability.

● Optimization and Scalability

- Improve the computational efficiency and scalability of existing models to handle diverse customer needs.

- Drive efficient use of computational and cloud resources, minimizing redundancy and controlling operational expenses.

- Ensure all computational tools and methodologies comply with industry standards and best practices.

● Cross-Functional Collaboration

- Work closely with domain experts, software engineers, and project managers to ensure seamless integration of scientific methods into practical applications.

- Communicate findings and recommendations effectively to technical and non-technical stakeholders.

● Customer Engagement:

- Collaborate with customers to understand their R&D challenges and aid in tailoring the platform to address specific use cases.

- Deliver insights and solutions based on predicted outputs, ensuring alignment with customer sustainability and performance goals.

Qualifications:

● Education:

- Bachelor's or Master's in Computer Science| Data Science or Cheminformatics or Computational Chemistry

- Course Certificates in Data Science

● Experience:

- 6+ years of total experience, 3+ relevant drug discovery experience with demonstrated impactful contributions to small-molecule programs.

- 4+ years of experience in data modeling, computational analysis, or similar roles, preferably in manufacturing, R&D, or chemical industries.

- Proficiency in statistical and machine learning techniques.

- Background or project work in materials physics/chemistry or a related field is an added advantage, not mandatory

● Technical Skills:

- Mandatory: Programming experience in Python (preferred), R, or similar languages.

- Mandatory: Hands-on experience with AI/ML tools like TensorFlow, PyTorch, or sci-kit-learn.

- Mandatory: Expertise in cheminformatics data analysis and large-scale data handling.

- Desired: Familiarity with cloud platforms (AWS, Azure, or GCP) for large-scale computations.

- Experience with databases (SQL/NoSQL) and data visualization tools.

● Soft Skills:

- Strong problem-solving and critical-thinking abilities.

- Excellent communication skills to convey complex ideas to varied audiences.

- Team player with a collaborative mindset.

- Efficient and flexible disposition, able to rapidly learn new fields and use data science and machine learning to improve decision-making and workflows

Interested candidates can apply by sharing their resume at or apply via LinkedIn job post.