Lead Data Scientist

Acldigital; Bengaluru; On-site; INR 1,200,000 - 1,800,000; Full time

Job summary

Acldigital is seeking a passionate ML/AI Lead Data Scientist in Bengaluru, India. This role requires expertise in developing analytics-focused products utilizing machine learning and data visualization tools. Candidates must possess a Bachelor’s or Master’s degree in a quantitative field and 7+ years of experience solving complex business problems. Responsibilities include mentoring teams, translating business needs into machine learning solutions, and ensuring data integrity. The company fosters a collaborative environment with a focus on AI ethics and scalable solutions.

Qualifications

• 7+ years of experience in solving complex business problems using machine learning.
• Hands-on experience in deploying machine learning solutions to production.
• In-depth understanding of supervised, unsupervised, and deep learning models.

Responsibilities

• Translate business problems into identifiable machine learning problems.
• Collaborate with teams to monitor outcomes and improve models.
• Own the code review process and mentor Data Science engineers.

Skills

Machine learning

Natural language processing

Statistical modeling

Python

R

Data visualization

Education

Bachelor's or Master's degree in Computer Science, Statistics or Mathematics

Tools

Pytorch

Scikit-Learn

TensorFlow

Amazon SageMaker

Azure ML Studio

Tableau

Job description

We are looking for a passionate ML /AI Lead Data Scientist with demonstrated thought‑leadership & proven ability to lead the development of analytics‑focused products and utilizing cutting edge machine learning, natural language processing, and mathematical techniques to drive powerful business results. You will have the opportunity to work with a wide range of stakeholders and functional teams to help them discover insights hidden in data sets and enable stakeholders to improve business. AI ethics, fairness and secure development practices are also our focus areas.

Responsibilities

• Partners with lines of business to understand business problems and translate them into identifiable machine learning problems which can be delivered as technical solutions and actionable recommendations across the organization
• Coordinate with business teams to monitor outcomes and refine/ improve the machine learning models
• Work across the spectrum of statistical modelling including supervised, unsupervised, & deep learning techniques to apply the right level of solution to the right problem
• Collaborate & share best practices with data and software engineers to enable consistent deployment of high‑quality models that will scale across the company’s ecosystem
• Own the code review process to ensure stringent coding guidelines are met by other data scientists & data engineers
• Mentor & lead Data Science engineers in choosing the right machine learning approach/models & utilizing open source languages such as R, Python, etc.
• Lead data mining and collection procedures for all business use cases and guarantee data quality and integrity
• Utilize Data visualization tools to deliver insights to stakeholders and present technical solutions to non‑technical audience in a simple and clear manner
• Track emerging developments w.r.t technology, tools, practices, etc in the open source, data science/machine learning/chatbot domain and leverage same for Schneider Electric
• Build frameworks leveraging APIs to industrialize AI models across the organization
• Adhere to stringent quality assurance and documentation standards using version control and code repositories (e.g., Git, GitHub, Markdown)

Requirements and Skills

• You should have bachelor’s or Master’s degree in Computer Science, Statistics or Mathematics, Informatics, Information Systems or another quantitative field
• You should have 7+ years of experience in solving real life complex business problems using machine learning. Hands‑on experience in deploying these machine learning solutions to production is mandatory.
• In‑depth understanding and modeling experience in supervised, unsupervised, reinforcement and deep learning models; hands‑on knowledge of data wrangling, data cleaning/preparation, dimensionality reduction is required
• Knowledge of vector algebra, statistical and probabilistic modelling is highly desirable
• Exploratory data analysis and hypothesis testing to identify ML opportunities is a plus
• Experience in major machine learning frameworks such as Pytorch, Scikit-Learn, Tensorflow, Pandas, SparkML etc.
• Fluency in programming skills such as Python, R, or other equivalent languages
• Familiarity with databases like MySQL, Oracle, SQL Server, NoSQL, etc. is desirable
• Experience working with Amazon SageMaker or Azure ML Studio for deployments is required
• Experience in data visualization software such as Tableau, ELK, etc is a plus
• Strong analytical and critical thinking skills. You should also have a business mindset, swift to identify risk situations and opportunities, and able to generate creative solutions to business problems
• Effective communication skills (written and verbal) to properly articulate complicated statistical models/ reports to management and other IT development partners