We are looking for a talented dynamic and curios candidate to join our data team. As a Junior Data Scientist, you will leverage your analytical skills and expertise in machine learning to extract insights from complex datasets and drive data\-driven decision\-making across our projects. You will collaborate closely with cross\-functional teams to develop predictive models, uncover actionable insights, and solve challenging business problems.
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This is a\nfull\-time internship for a duration of 3 months. Please note that this is an\nunpaid internship<\/b>; however, based on performance, candidates may be offered\na paid contract role upon successful completion of the internship. High\nPotential for Permanent Role: Top performers will have a strong opportunity to\ntransition into a full\-time permanent position.<\/b><\/span>
<\/p>Responsibilities
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<\/div>- Data Analysis and Exploration<\/span><\/b>
<\/li>- Analyze large, complex datasets to identify trends, patterns,\n and relationships.<\/span>
<\/li>- Conduct exploratory data analysis (EDA) to gain insights and\n formulate hypotheses.<\/span>
<\/li>- Utilize statistical methods and data visualization techniques\n to communicate findings effectively.<\/span>
<\/li><\/ul>- Predictive Modeling and Machine Learning
<\/span><\/b> o <\/span><\/span><\/span><\/span><\/span>Experience and knowledge in\nanalyzing and developing forecasting models using time series data<\/span>
<\/li>- Develop predictive models using machine learning algorithms.<\/span>
<\/li>- Perform feature engineering, model selection, and hyper\-parameter\n tuning to optimize model performance.<\/span>
<\/li>- Ensure that model always meet the relevant evaluation metrics.<\/span>
<\/li><\/ul>- Data Mining and Pattern Recognition<\/span><\/b>
<\/li>- Apply data mining techniques to extract actionable insights\n from structured and unstructured data.<\/span>
<\/li>- Identify patterns and anomalies in data to detect fraud,\n predict customer behavior, or optimize business processes.<\/span>
<\/li>- Implement clustering, classification, regression, and other\n machine learning algorithms as needed.<\/span>
<\/li><\/ul>- Collaboration and Communication<\/span><\/b>
<\/li>- Excellent story telling and presentation skills <\/span>
<\/li>- Collaborate with cross\-functional teams, including engineers,\n product managers, and business stakeholders.<\/span>
<\/li>- Translate technical findings into actionable insights and\n recommendations for non\-technical audiences.<\/span>
<\/li>- Present findings and proposals in clear, concise, and\n compelling ways.<\/span>
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Requirements<\/h3>\u2022\tDiploma in Computer Science/Electronics or bachelor\u2019s in computer science/Statistics
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\u2022\t0 to 1 years of with knowledge in data science, machine learning, generative AI
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\u2022\tCandidates who completed certified courses in data science/AI is preferred
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\u2022\tPassionate Learner, with curiosity to explore and find insights from large datasets
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\u2022\tStrong understanding of statistical analysis, hypothesis testing, and experimental design.
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\u2022\tExperience with machine learning libraries and frameworks (e.g., TensorFlow, scikit\-learn, PyTorch, etc.).
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\u2022\tFamiliarity with data visualization tools and techniques (e.g., Matplotlib etc.).
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\u2022\tExcellent problem\-solving and analytical skills with attention to detail.
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\u2022\tEffective communication and collaboration abilities in a team environment.
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Benefits<\/h3>- Opportunities for high\-speed professional growth and\n development.<\/span>
<\/li>- Collaborative and supportive work environment.<\/span>
<\/li>- Training (Technical & Soft skills)<\/span>
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