Strategic
- Actively support the philosophy, values and key strategic initiatives of organization and the department.
- Efficient contribution to the overall success of RDIT by driving innovation and team performance according to objectives and targets.
- Innovate solutions using Artificial Intelligence and machine learning.
- Collaborate with cross-functional teams to understand business requirements and provide data-driven solutions.
- Fulfilling requirements as set by Group Leader and Team Leader, e. g. within specific Research Projects
Operational
- Execute and manage advanced analytics and data science projects, focusing on data visualization and machine learning model development and deployment.
- Implement and manage ETL processes to ensure efficient extraction, transformation, and loading of data from various sources, such as internal databases and third party platforms.
- Ensure data quality and accuracy in all analytical processes.
- Use programming and scripting skills to automate the process, and enhance the effectiveness and productivity. Eg. R, Perl, Bash, Python, JAVA, mySQL
- Use statistical techniques and machine learning models to analyze large datasets with software such as Python (scikit-learn, TensorFlow) and R.
- Create and maintain Power BI dashboards to visualize data and communicate findings to stakeholders.
- Set up and maintain CI/CD pipelines for data science projects.
- Work closely with cross-functional teams to understand and address business requirements.
- Communicate complex technical concepts to non-technical stakeholders.
- Develop and implement algorithms for predictive modelling of agrochemical based active ingredients.
- Participate in the assessment and introduction of new data technology supporting digitalization and automation efforts for application to a broader practice within the organization.
- Carry out advanced statistical analysis in combination with machine learning and artificial intelligence and build group capability.
- Updating self with respect to new tools for digitization and data analytics using the online and print literature, attending national and international conferences.
Educational Qualification
- PhD or Masters in data science / statistics / computational sciences / informatics or related discipline from a reputed University / Institute from India or overseas with excellent academic credentials
- Should have an experience in creating interactive dashboard/data app, AI/ML model building, cloud platforms, big data analytics platform.
- High quality research publications and/or patents appreciated.
Experience
- Experience of > 3 years from relavent industries and/or high-ranking academic institutes in handling scientific data in order to support, improve and direct design in the area of drug discovery, exploration and optimization in life sciences.
- Must be able to communicate with key stakeholders on a high level of understanding of contents.
- Experience in predictive modelling, statistics, machine learning to collect, explore and extract insight from structured and unstructured data.
- Proficiency in Power BI and creating interactive dashboards.
- Proficiency in scripting and programming languages like R, Perl, Bash, Python, JAVA, mySQL to build efficient AI/ML applications
- Well versed with working on Cloud (AWS), HPC servers on LINUX/UNIX environemnt.
- Experience with big data technologies e.g., Hadoop, Spark.
- Experience with CI/CD tools and practices
- Ability to communicate technical results to non-statisticians.
- Experience in agro-chemical space would be an additional advantage.
Interested candidates are requested to share their resumes directly on shubhi.chandnani@piind.com