Data scientist

Job Description

Position Overview:
As a Data Scientist, you will be responsible for extracting valuable insights and knowledge from large and complex data sets to drive informed decision-making and solve business problems. You will apply advanced analytical and statistical techniques, along with machine learning algorithms, to analyze and interpret data, build predictive models, and develop data-driven solutions. Your role will involve collaborating with cross-functional teams and stakeholders to understand their data needs and provide actionable recommendations based on your findings. This position requires a strong blend of analytical, technical, and communication skills.

Key Responsibilities:

Data Analysis and Interpretation:
Collect, clean, preprocess, and analyze large data sets using statistical techniques, data mining, and machine learning algorithms.
Identify patterns, trends, and correlations in data to derive meaningful insights.
Conduct exploratory data analysis to discover new opportunities or potential issues.
Create data visualizations, dashboards, and reports to effectively communicate findings to non-technical stakeholders.

Model Development and Evaluation:
Develop and implement predictive models, machine learning algorithms, and statistical models to solve business problems.
Utilize tools and libraries like Python, R, or other programming languages to build and train models.
Evaluate model performance and iterate on models to improve accuracy and effectiveness.
Apply feature engineering techniques to optimize model performance and interpretability.

Data-driven Solutions:
Collaborate with cross-functional teams, including business analysts, engineers, and product managers, to understand business requirements and translate them into data-driven solutions.
Provide insights and recommendations to support strategic decision-making, product development, and process improvement initiatives.
Conduct A/B testing and experimentation to validate hypotheses and measure the impact of data-driven solutions.

Data Management and Governance:
Ensure data integrity, quality, and security throughout the data lifecycle.
Develop and maintain data pipelines and workflows for efficient data extraction, transformation, and loading.
Stay updated with the latest industry trends, advancements, and best practices in data science, machine learning, and artificial intelligence.

Qualifications and Skills:

Bachelor's or Master's degree in Data Science, Computer Science, Statistics, Mathematics, or a related field.
Must have Experience in Natural Language processing /Natural language generation
Strong proficiency in programming languages such as Python or similar languages commonly used in data science.
Proficiency in data manipulation, analysis, and visualization using Basic Python libraries like Tensorow, Pytorch, Keras, Scikit-learn, Spacy, Numpy, Pandas, genism
Solid understanding of statistical concepts, hypothesis testing, and experimental design.
Experience with machine learning algorithms, predictive modeling, and data mining techniques.
Familiarity with deep learning frameworks & Algorithms like FaceBook's DeepText, FastText, RoBERTa, Word2Vec, RNN, CNN, R-CNN, LSTM, GRU, Sequence-to-Sequence, Reinforcement Learning
Proficiency in SQL and working with relational databases.
Strong problem-solving skills and the ability to think analytically.
Excellent communication skills to effectively present complex data-driven insights to both technical and non-technical stakeholders.
Experience with big data technologies such as HHadoop, MapReduce, Hbase, Thrift, HDFS, Oozie, Apache Spark, Storm, Hive, Kafka, Cassandra is a plus.
Familiarity with cloud platforms like AWS, Azure, or Google Cloud is desirable.