{"id":3462479,"url":"https://alion.io/job/devsinc-senior-data-scientist-2","title":"Senior Data Scientist","company":{"id":3374,"name":"Devsinc","domain":"devsinc.com","url":"https://alion.io/company/devsinc","size_band":"1001-5000","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Workable","truth_index":{"grade":"B","score":79,"open_postings":14,"ghost_share":0,"stale_share":0.786,"repost_share":0.071,"time_to_fill_p50_days":29,"computed_at":"2026-11-03T05:54:40Z"}},"role":"Data Science","role_family":"Data Science","seniority":"senior","employment_type":"full_time","work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Lahore, Pakistan"],"countries":["PK"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":16000,"max_usd":42000,"period":"year","method":"global_role_cell_scaled_by_country","sample_n":2679},"experience_years_min":3,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"AWS","optional":false},{"name":"Azure","optional":false},{"name":"Docker","optional":false},{"name":"FastAPI","optional":false},{"name":"Flask","optional":false},{"name":"GCP","optional":false},{"name":"Git","optional":false},{"name":"Hugging Face","optional":false},{"name":"Keras","optional":false},{"name":"LangChain","optional":false},{"name":"LlamaIndex","optional":false},{"name":"Machine Learning","optional":false},{"name":"Matplotlib","optional":false},{"name":"MLFlow","optional":false},{"name":"NumPy","optional":false},{"name":"Pandas","optional":false},{"name":"Prompt Engineering","optional":false},{"name":"Python","optional":false},{"name":"PyTorch","optional":false},{"name":"RAG","optional":false},{"name":"Rest API","optional":false},{"name":"Scikit-learn","optional":false},{"name":"Seaborn","optional":false},{"name":"SQL","optional":false},{"name":"TensorFlow","optional":false},{"name":"CI/CD","optional":true},{"name":"Computer Vision","optional":true},{"name":"Embeddings","optional":true},{"name":"NLP","optional":true},{"name":"OpenAI","optional":true},{"name":"Recommender Systems","optional":true},{"name":"Time Series","optional":true}],"status":"live","first_seen_at":"2026-10-29T14:22:09Z","employer_posted_date":"2026-10-29","last_verified_at":"2026-11-04T00:19:20Z","board_verified":true,"closed_at":null,"days_open":5,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":5},"description":"We are looking for a skilled and results-driven Senior Data Scientist with 3+ years of professional experience in data science, machine learning, artificial intelligence, and predictive analytics. The ideal candidate should have strong expertise in Python, machine learning frameworks, statistical modeling, and AI-powered tools, with the ability to transform complex datasets into actionable business insights.\nThe candidate will be responsible for developing, training, evaluating, and deploying machine learning models, leveraging modern AI tools and frameworks to build scalable, data-driven solutions. Experience with Generative AI, Large Language Models (LLMs), and cloud-based AI services will be considered a strong advantage.\nKey Responsibilities\nCollect, clean, process, and analyze structured and unstructured datasets to identify patterns, trends, and business opportunities.\nDevelop, train, evaluate, and optimize machine learning and deep learning models for real-world applications.\nBuild predictive models, classification and regression systems, recommendation engines, and forecasting solutions.\nUse Python libraries such as Pandas, NumPy, Scikit-learn, Matplotlib, and Seaborn for data analysis, visualization, and model development.\nWork with machine learning and deep learning frameworks, including TensorFlow, PyTorch, and Keras.\nLeverage AI tools, Generative AI, LLMs, and prompt engineering techniques to develop intelligent applications and automate workflows.\nApply statistical analysis, hypothesis testing, feature engineering, and model validation techniques to improve model performance.\nDevelop data pipelines and integrate machine learning models into production applications through APIs and backend services.\nCollaborate with software engineers, data engineers, product managers, and business stakeholders to deliver AI-driven solutions.\nMonitor deployed models, evaluate performance, identify data drift, and implement improvements.\nDocument technical processes, model architectures, experiments, and analytical findings.\nStay updated with emerging AI technologies, machine learning methodologies, and industry best practices.\nRequirements\nBachelor’s or Master’s degree in Computer Science, Data Science, Artificial Intelligence, Statistics, Mathematics, or a related field.\nStrong proficiency in Python, Pandas, NumPy, and Scikit-learn.\nHands-on experience with Machine Learning, Deep Learning, TensorFlow, or PyTorch.\nKnowledge of Generative AI, LLMs, prompt engineering, RAG, and AI tools/frameworks such as LangChain, LlamaIndex, or Hugging Face.\nStrong understanding of statistics, data analysis, feature engineering, and model evaluation.\nExperience with SQL, data visualization tools, and REST APIs using FastAPI or Flask.\nFamiliarity with AWS, Azure, or GCP, Docker, Git, and MLOps tools such as MLflow.\nExcellent analytical, problem-solving, and communication skills.\nPreferred Qualifications\nExperience with Generative AI, LLMs, RAG (Retrieval-Augmented Generation), embeddings, and vector databases.\nFamiliarity with AI frameworks and tools such as LangChain, LlamaIndex, Hugging Face, OpenAI APIs, or equivalent technologies.\nExposure to cloud platforms such as AWS, Microsoft Azure, or Google Cloud Platform (GCP).\nKnowledge of MLOps practices, model monitoring, CI/CD pipelines, MLflow, or similar experiment-tracking tools.\nExperience processing large datasets and working with data engineering pipelines.\nFamiliarity with NLP, computer vision, recommendation systems, or time-series 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