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