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162 Field Industrial Supplies Jobs

Senior Lead Data Scientist (Data Scientist, ML/Python)

Field Industrial Supplies

4-9 years

Pune

1 vacancy

Field Industrial Supplies

posted 12hr ago

Job Role Insights

Key skills for the job

Data Science Computer Science Data Analysis Python Machine Learning Clinical Data Management

+ 4 more

Job Description

You will be a part of the FIS Compliance Suite (formerly Protegent) next generation product development initiative, joining a team of highly motivated and focused developers to develop our next generation compliance product
As a Senior Data Scientist at FIS Global, you will play a key role in extracting actionable insights from complex datasets and developing predictive models to support business objectives
Leveraging your expertise in statistical analysis, machine learning, and data visualization, you will collaborate with cross-functional teams to solve challenging problems and drive strategic initiatives
You will be responsible to devise and utilize algorithms and models to mine big-data stores; perform data and error analysis to improve models; clean and validate data for uniformity and accuracy, analyze data for trends and patterns, and interpret data with clear objectives in mind
You will get an opportunity to work with multiple products and businesses and develop a good understanding of the interesting world of trading and compliance

What you bring:

Knowledge / Experience

- Minimum of seven years of experience in data science or a closely related field, with a proven track record of delivering impactful solutions.

- Proficiency in programming languages such as Python, R, or Scala, as well as experience with data manipulation libraries (e.g., pandas, NumPy) and machine learning frameworks (e.g., scikit-learn, TensorFlow, PyTorch).

- Strong analytical and problem-solving skills, with the ability to translate business requirements into analytical solutions.

- Excellent communication and presentation skills, with the ability to convey complex technical concepts to non-technical stakeholders.

- Experience working with big data technologies (e.g., Hadoop, Spark) and cloud platforms (e.g., AWS, Azure, GCP) is a plus.

- Demonstrated ability to work effectively in a collaborative team environment and manage multiple priorities in a fast-paced, dynamic setting.

Skills

Define strategies to leverage existing large datasets and integrate new datasets to extend product capabilities and work closely with the data engineers and product engineering teams in the development of data products.

- Lead the end-to-end development of predictive models and machine learning algorithms to solve business problems and optimize processes.

- Perform exploratory data analysis, data preprocessing, and feature engineering to uncover hidden patterns and trends in large datasets.

- Collaborate with stakeholders to define project objectives, develop analytical solutions, and communicate findings effectively.

Work closely with product and solution management teams to understand business use cases and convert into machine learning or gen-AI solutions.

- Conduct rigorous model evaluation and validation to ensure the robustness and reliability of predictive models.

- Stay abreast of the latest advancements in data science, machine learning, and artificial intelligence to continuously improve methodologies and techniques.

- Contribute to the development and implementation of best practices for data management, analysis, and model deployment.

Qualifications

Bachelors or master s degree in computer science, Statistics, Mathematics, or a related field.

Competencies

Fluent in English
Excellent communicator - ability to discuss functional and commercial solutions to internal and external parties and adapt depending on the technical or business focus of the discussion.
Attention to detail and quality focus.
Organized approach - manage and adapt priorities according to client and internal requirements.
Self-starter but team mindset - work autonomously and as part of a global tea

Employment Type: Full Time, Permanent

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