Meesho Recruitment Of Data Scientist III | Great Opportunity

A Data Scientist III leverages statistical evaluation, gadget reading techniques, and programming talents to extract insights and solve complicated troubles from large datasets. They interpret information, broaden models, and speak findings to stakeholders. Key responsibilities encompass information cleaning, analysis, and the development of predictive fashions to power records-driven decision-making.

Job Role: Data Scientist III
Salary: ₹40 Lakhs to ₹75 Lakhs per year
Location: Bengaluru, Karnataka
Company: Meesho
Qualification: Bachelor’s/Master’s degree

About Company:

Data Scientist III

Meesho is an Indian social trade platform founded in 2015 with the aid of manner of Vidit Aatrey and Sanjeev Barnwal. It lets individuals start their online stores through social channels like WhatsApp, Facebook, and Instagram. Meesho connects carriers with resellers, regular housewives, small groups, and those searching out extra profits. The platform gives a massive range of merchandise which includes fashion, splendor, and a circle of relatives gadgets. With a focal point on empowering marketers and leveraging social networks for sales, Meesho has grown unexpectedly, attracting sizeable investment and expanding its consumer base throughout India. It performs a pivotal function in transforming traditional change via virtual channels.

Role Overview:

Join Meesho as a Data Scientist III in Bengaluru to beautify productivity through statistics insights. Solve unique disturbing situations in fraud detection, stock optimization, and greater. Enjoy a balanced professional and private life, competitive repayment, and comprehensive well-being blessings. Experience in ML, Neural Networks, and Big Data tech stacks is vital. Be part of our task to democratize net commerce for all.

Roles and Responsibilities Of Data Scientist III:

Data Collection and Cleaning:

Gathering relevant statistics from various assets along with databases, APIs, and data lakes. This entails ensuring facts quality through cleaning, preprocessing, and reworking facts into usable formats.

Exploratory Data Analysis (EDA):

Performing EDA to apprehend facts patterns, and choose out tendencies, outliers, and relationships. This includes using statistical methods and visualization equipment to advantage insights that inform further analysis.

Model Development and Machine Learning:

Building predictive fashions and leveraging gadget mastering algorithms (e.g., regression, category, clustering) to solve organization issues. This includes function engineering, model desire, and assessment using techniques like move validation.

Data Visualization and Communication:

Creating visualizations (e.g., charts, dashboards) to talk insights efficiently to stakeholders. This involves using gear like Tableau, Power BI, or Python libraries (matplotlib, seaborn) to offer findings sincerely.

Deployment and Monitoring:

Deploying fashions into production environments and monitoring their performance over time. This includes participating with software program engineers to mix models into packages and enforcing techniques for version renovation and updates.

Qualification:

Bachelor’s/Master’s degree in computer science (or similar degrees)

4-7 years of experience as a Data Scientist in a fast-paced organization, preferably B2C

Data Scientist III

Skills Required For Data Scientist III:

Statistical Analysis and Mathematics:

Data Scientists should have a robust basis in information and mathematics to recognize and interpret complicated facts units. This consists of understanding of opportunity idea, hypothesis trying out, and statistical modeling strategies like regression, clustering, and class.

Programming Skills:

Proficiency in programming languages including Python, R, and SQL is essential for fact manipulation, evaluation, and constructing device learning fashions. Knowledge of libraries like Pandas, NumPy, Scikit-Learn (for Python), and ggplot2, (for R) is important.

Machine Learning and AI:

Data Scientists want to be skilled in applying device reading algorithms and strategies which include supervised and unsupervised reading, deep learning, and herbal language processing (NLP). They need to recognize model assessment, tuning, and deployment.

Data Visualization:

Communicating insights efficaciously calls for knowledge in facts visualization equipment like Tableau, Power BI, or programming libraries together with Matplotlib and Seaborn. Data Scientists need to be capable of creating clean and informative visualizations.

Domain Knowledge:

Understanding the particular area wherein they work (e.g., finance, healthcare, e-alternate) is critical. This includes knowledge of industry dispositions, commercial enterprise techniques, and applicable hints. Domain know-how permits Data Scientists to ask the proper questions and derive considerable insights.