What Jobs are available for Data Mining Techniques in Mumbai?

Hi,

We are having an opening for Manager / Senior Manager 2 Data Science at our Mumbai location

Job Summary :

The role would work as an integral part of the Data & Analytics team at SUN Pharma. It involves leading and managing business critical data science projects and AI/ ML Initiatives. The role requires an understanding of business processes related to Pharma industry and data science and analytics, and the ability to communicate effectively to both technical and functional stakeholders.

Position offers a significant opportunity for an all-round business understanding and impact working with the in-house teams as well as business and corporate functions as well as technology consultants and partners

Areas of Responsibility :

For designated complex and business critical digital and technology based data & AI related projects,

• Building and expanding the Data Analytics CoE and Data Architecture for Global Use cases
• Clear understanding of the expected business outcome, business value and specific outputs / deliverables
• Managing stakeholders and expectations from use of data science and analytics
• Working in tandem with Data guardians from different functions, in-line with their requirements and vision
• Monitoring any proof of concept for new requirement, coordinating with involved stakeholders and partners, ensuring timely completeness for the objectives pre-decided
• Planning benefits realization for Data Science projects and execution strategy
• Reusability of data streams, wherever applicable, to eliminate duplication in data foot print
• Managing a team of data engineers, cloud architects, MLOps engineers and Database engineers
• Structuring delivery team organization, managing the engagement with relevant partner ecosystem
• Managing CI-CD pipelines and building ML products for internal teams
• Managing budgets, managing scope, time and quality, measuring and managing change
• Targeted communication, orchestration and governance
• System/solution usage and adoption, benefit realization and measurement

Educational Qualification : B. Tech / MBA

Skills :

• Knowledge of Data Science, ML, Statistical Techniques, Data Modelling, Data Transformation, Use of Cloud Hyperscaler environment.
• Use of cloud based tools for automating ML pipelines and deploying cloud based models for end users
• Ability to understand and interpret complex datasets and formulate means for merging disparate data sources
• Strong fundamentals in cloud services and data lake architecture.
• Work involves handling sensitive data and confidential information requiring discretion on the role holder's part.
• Ability to work under deadlines and comfortable with certain level of ambiguity
• Ability to multi task, successfully adapt to changes in work priorities.
• Should be comfortable to operate at a strategic level, and also have an eye for detail.
• Should be a self motivated

Experience :

7-12 years (preferably, IT Services / Pharma Industry Experience, from organizations of repute)

Experience in handling data/ data models for different functions

• Assist in collecting and cleaning large datasets from various sources.
• Learn to perform exploratory data analysis (EDA) to understand data patterns and characteristics.
• Support data scientists in building and validating predictive models using machine learning algorithms.
• Develop data visualizations to communicate findings effectively.
• Gain exposure to programming languages commonly used in data science, such as Python and R.
• Learn about database management and querying using SQL.
• Participate in team meetings and contribute ideas for data-driven solutions.
• Understand and apply statistical methods for data analysis.
• Assist in the documentation of data science processes and findings.
• Collaborate with cross-functional teams to understand business requirements and data needs.
• Learn to deploy and monitor machine learning models in production environments.
• Work with big data technologies and cloud platforms.
• Receive mentorship and guidance from senior data science professionals.
• Develop a strong portfolio of data science projects.
• Contribute to the continuous improvement of data science workflows and tools.
• Understand ethical considerations and best practices in data handling and analysis.
• Gain practical experience in feature engineering and model selection.

• Recent graduate with a Bachelor's or Master's degree in a quantitative field such as Computer Science, Statistics, Mathematics, Economics, Physics, or a related discipline.
• Strong analytical and problem-solving skills.
• Basic understanding of programming concepts, preferably in Python or R.
• Familiarity with basic statistical concepts.
• Eagerness to learn and a strong passion for data science and machine learning.
• Excellent communication skills, both written and verbal.
• Ability to work independently and as part of a remote team.
• Proactive attitude and a willingness to take on new challenges.
• Basic knowledge of SQL is a plus.
• Experience with data visualization tools is a plus.
• Understanding of data ethics and privacy principles is beneficial.
• A keen interest in uncovering patterns and insights from data.

• Develop and deliver high-quality lectures and course materials for undergraduate and postgraduate programs in Data Science.
• Design and implement innovative pedagogical approaches to effectively teach complex data science concepts.
• Conduct independent research in Data Science or a related field, publishing findings in reputable journals and presenting at conferences.
• Supervise student research projects, dissertations, and theses.
• Mentor and advise students on academic and career development.
• Contribute to curriculum development and enhancement for the Data Science programs.
• Engage in academic service, including committee work and program administration.
• Collaborate with faculty members across departments to foster interdisciplinary research and teaching initiatives.
• Stay abreast of the latest advancements and trends in data science, artificial intelligence, and machine learning.
• Promote a positive and inclusive learning environment for all students.
• Participate in departmental and institutional events and initiatives.
• Contribute to the growth and reputation of the Data Science department.

• Ph.D. in Data Science, Computer Science, Statistics, Mathematics, or a closely related quantitative field.
• A strong publication record in peer-reviewed journals and conferences.
• Minimum of 5 years of teaching experience at the university level, with a proven ability to engage students.
• Demonstrated expertise in core data science areas such as machine learning, statistical modeling, data mining, big data analytics, and data visualization.
• Proficiency in programming languages commonly used in data science (e.g., Python, R) and relevant libraries/frameworks.
• Excellent communication, presentation, and interpersonal skills.
• Ability to inspire and motivate students.
• Experience in curriculum development and academic administration is desirable.
• A passion for research and a commitment to academic excellence.
• Ability to work collaboratively within a faculty team.

• Assist in collecting, cleaning, and pre-processing large datasets from various sources.
• Support data scientists in developing and implementing machine learning models for classification, regression, and clustering tasks.
• Conduct exploratory data analysis (EDA) to identify trends, patterns, and insights.
• Help in creating data visualizations and reports to communicate findings to stakeholders.
• Learn and apply statistical techniques and data mining methods.
• Participate in team meetings, brainstorming sessions, and training workshops.
• Contribute to documentation of data science processes and methodologies.
• Gain hands-on experience with programming languages like Python or R and relevant libraries (e.g., Pandas, NumPy, Scikit-learn).
• Support the testing and validation of data models.
• Work collaboratively with a remote team to achieve project goals.

• Recent graduate (within the last 12 months) with a Bachelor's or Master's degree in Computer Science, Statistics, Mathematics, Data Science, or a related quantitative field.
• Strong analytical and problem-solving skills.
• Basic understanding of programming concepts, preferably with exposure to Python or R.
• Familiarity with basic statistical concepts and machine learning algorithms is a plus.
• Excellent communication skills, both written and verbal, with the ability to work effectively in a remote setting.
• Eagerness to learn and a proactive attitude towards acquiring new skills.
• Ability to work independently and manage time effectively in a remote environment.
• Must have reliable internet access and a dedicated workspace for remote work.

Role-Machine Learning Engineer

Skills required- Python, AI, ML

Location- Bangalore, Mumbai

Year of experience - 6 to 10 years

Job description:

• Machine Learning Engineers will work on all AI and ML technologies - machine learning, knowledge graphs, cognitive etc. – to Design, develop and implement solutions.
• Experience with Machine Learning algorithms.
• Expertise in Python
• Deep understanding of data structures and algorithms.

We are looking for a skilled Machine Learning Engineer with expertise in Python and hands-on experience in building, training, and deploying machine learning and deep learning models. The ideal candidate will have prior experience taking models from experimentation to production, along with knowledge of modern ML/DL frameworks and cloud environments.

Key Responsibilities:

• Design, train, and fine-tune machine learning and deep learning models
• Perform model inference, testing, and optimization for production-scale applications
• Deploy ML models using Docker and AWS cloud services
• Work closely with cross-functional teams to translate business needs into ML solutions
• Manage databases (SQL, MongoDB) and build efficient data pipelines
• Monitor deployed models to ensure accuracy, scalability, and reliability

Requirements:

• 2–5 years of experience as an ML Engineer or in a related role
• Strong proficiency in Python and ML/DL libraries (TensorFlow, PyTorch, Scikit-learn)
• Proven experience with model training, inference, and deployment
• Experience with AWS, Docker, and working with SQL/MongoDB databases
• Bachelor’s degree in Computer Science, Engineering, or related field (Master’s degree is a plus)